Articles & Book Chapters
2022
Journal Papers:
298. L. Zhou, X. Meng, Y. Huang, K. Kang, J. Zhou, Y. Chu, H. Li, D. Xie, J. Zhang, W. Yang, N. Bai, Y. Zhao, M. Zhao, G. Wang, L. Carin, X. Xiao, K. Yu, Z. Qiu, and X. Gao. (2022). “An Interpretable deep learning workflow for discovering sub-visual abnormalities in CT scans of COVID-19 inpatients and survivors”. Nature Machine Intelligence. 4: 494-503.
297. J. Chan, B. Zhang, X. Chew, A. Salhi, Z. Kwok, C. Lim, N. Desi, N. Subramaniam, A. Siemens, T. Kinanti, S. Ong, A. Sanchez-Mejias, P. Thao Ly, O. An, R. Sundar, X. Fan, S. Wang, B. Siew, K. Lee, C. Chong, B. Lieske, W. Cheong, Y. Goh, W. Fam, M. Ooi, B. TH Koh, S. Ganpathi Iyer, W. Ling, J. Chen, B. Yoong, R. Chanwat, G. Bonney, B. KP Goh, W. Zhai, M. Fullwood, W. Wang, K. Tan, W. Chng, Y. Dan, J. Pitt, X. Roca, E. Guccione, L. Vardy, L. Chen, X. Gao, P. KH Chow, H. Yang, and Y. Tay. (2022). “Pan-cancer, pervasive upregulation of 3’UTR splicing drives tumorigenesis”. Nature Cell Biology. 24: 928-939.
296. N. Fei, Z. Lu, Y. Gao, G. Yang, Y. Huo, J. Wen, H. Lu, R. Song, X. Gao, T. Xiang, H. Sun, and J.-Rong Wen*. (2022). “Towards artificial general intelligence via a multimodal foundation model”. Nature Communications. 13: 3094.
295. H. Cui, H. Yi, H. Bao, Y. Tan, C. Tian, X. Shi, D. Gan, B. Zhang, W. Liang, R. Chen, Q. Zhu, L. Fang, X. Gao, H. Huang, R. Tian, S. Rickert-Sperling, Y. Hu, and W. Chen. (2022). “The SWI/SNF chromatin remodeling factor DPF3 regulates metastasis of ccRCC by modulating TGF-β signaling”. Nature Communications. In press.
294. L. Xiong, K. Tian, Y. Li, W. Ning, X. Gao, and Q. Cliff Zhang. (2022). “Online single-cell data integration through projecting heterogeneous datasets into a common cell-embedding space”. Nature Communications. In press.
293. Z. Chen, X. Liu, P. Zhao, C. Li, Y. Wang, F. Li, T. Akutsu, C. Bain, R. Gasser, J. Li, Z. Yang, X. Gao, L Kurgan, J. Song. (2022). “iFeatureOmega – an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets”. Nucleic Acids Research. In press.
292. S. Tian, B. Zhang, Y. He, Z. Sun, J. Li, Y. Li, H. Yi, Y. Zhao, X. Zou, Y. Li, H. Cui, L. Fang, X. Gao, Y. Hu, and W. Chen. (2022). “CRISPR-iPAS: a novel dCAS13-based method for alternative polyadenylation interference”. Nucleic Acids Research. 50(5): e26.
291. Y. Li, S. Chen, T. Rapakoulia, H. Kuwahara, K. Yip, and X. Gao. (2022). “Deep learning identifies and quantifies recombination hotspot determinants”. Bioinformatics. 38(10): 2683-2691.
290. Y. Li, G. Qiao, X. Gao, and G. Wang. (2022). “Supervised graph co-contrastive learning for drug-target interaction prediction”. Bioinformatics. 38(10): 2847-2854.
289. W. Han, Y. Cheng, J. Chen, H. Zhong, Z. Hu, S. Chen, L. Zong, L. Hong, T.-Fung Chan, I. King, X. Gao, and Y. Li. (2022). “Self-supervised contrastive learning for integrative single cell RNA-seq data analysis”. Briefings in Bioinformatics. In press.
288. X. Peng, X. Wang, T. Akutsu, F. Li, X. Gao, and J. Song. (2022). “RBP-TSTL is a two-stage transfer learning framework for genome-scale prediction of RNA-binding proteins”. Briefings in Bioinformatics. In press.
287. R. Guan, H. Pang, Y. Liang, Z. Shao, X. Gao, D. Xu, and X. Feng. (2022). “Discover the trends and hotspots of biosafety and biosecurity research from the literature via machine learning”. Briefings in Bioinformatics. In press.
286. C. Li, H. Zheng, H. Jin, J. Xiong, H. Li, Y. Huang, S. Ai, Y. Wang, T. Su, G. Sun, X. Xiao, T. Fu, Y. Wang, X. Gao, and P. Liang. (2022). “miR-596-3p suppresses brain metastasis of non-small cell lung cancer by modulating YAP1 and IL-8”. Cell Death and Disease. In press.
285. X. Luo, X. Wang, Y. Yao, X. Gao, and L. Zhang. (2022). “Unveiling the “Template-dependent” Inhibition on the Viral Transcription of SARS-CoV-2”. The Journal of Physical Chemistry Letters. In press.
284. M. Thafar, M. Alshahrani, S. Albaradei, T. Gojobori, M. Essack, and X. Gao. (2022). “Affinity2Vec: drug-target binding affinity prediction through representation learning, graph mining, and machine learning”. Scientific Reports. 12: 4751.
283. X. Yan, Y. Lu, Z. Li, Q. Wei, X. Gao, S. Wang, S. Wu, and S. Cui. (2022). “PointSite: a point cloud segmentation tool for identification of protein ligand binding atoms”. Journal of Chemical Information and Modeling. 62(11): 2835-2845.
282. Ming Fan, Chengcheng Yuan, Maosheng Xu, Shiwei Wang, Xin Gao, and Lihua Li. (2022). “A framework for deep multitask learning with multiparametric magnetic resonance imaging for the joint prediction of histological characteristics in breast cancer”. IEEE Journal of Biomedical and Health Informatics. In press.
281. Yongfang Li, Dong Zhang, Xin Gao, Xiaowei Wang, Lu Zhang. (2022). “The 2- and 3-Ribose Modifications of Nucleotide Analogues Establish the Structural Basis to Inhibit the Viral Replication of SARS-CoV2”. The Journal of Physical Chemistry Letters. 13(18): 4111-4118.
280. X. Chen, M. Li, S. Gao, Z. Chan, D. Zhao, X. Gao, X. Zhang, and R. Yan. (2022). “Follow the timeline! Generating abstractive and extractive timeline summary in chronological order”. ACM Transactions on Information Systems (TOIS). In press.
279. B. Yu, X. Wang, Y. Zhang, H. Gao, Y. Liu, and X. Gao. (2022). “RPI-MDLStack: predicting RNA-protein interactions through deep learning with stacking strategy and LASSO”. Applied Soft Computing. 120: 108676.
278. B. Yu, Y. Zhang, X. Wang, H. Gao, J. Sun, Q. Wei and X. Gao. (2022). “Identification of DNA N4-methylcytosine sites and N6-methyladenine sites through elastic net and bidirectional gated recurrent unit with convolutional neural network”. Biomedical Signal Processing and Control. 75: 103566.
277. S. Albaradei, A. Albaradei, A. Alsaedi, M. Uludag, M. A. Thafar, T. Gojobori, M. Essack, X. Gao. (2020). “MetastaSite: Predicting Metastasis to Different Sites using Deep Learning with Gene Expression Data”. Frontiers in Molecular Biosciences, section Molecular Diagnostics and Therapeutics. In press.
276. S. Chandra, M. Kumar Gourisaria, H. GM, D. Konar, X. Gao, T. Wang, and M. Xu. (2022). “Prolificacy assessment of spermatozoan via state-of-the-art deep learning frameworks”. IEEE Access. 10: 13715-13727.
275. H. Baig, A. Rasool, S. Zajif Hussain, J. Iqbal, R. Shahid Ashraf, A.-Hamid Emwas, M. Alazmi, X. Gao, G. Abbas Chotana, H.-ur-Rehman, R. Shah Zaib Saleem. (2022). “Synthesis, photophysical, electrochemical and computational studies of novel 2-aminoimidazolones with D-π-A framework”. Journal of Photochemistry and Photobiology A: Chemistry. 429: 113918.
274. S. Laref, B. Wang, S. Inal, S. Al-Ghamdi, X. Gao, and T. Gojobori*. (2022). “A peculiar binding characeterization of DNA(RNA) nucleobases at MoOS-based janus biosensor: dissimilar facets role on selectivity and sensitivity”. Biosensors. In press.
273. X. Luo, T. Xu, X. Gao, L. Zhang*. (2022). “An alternative role of Motif B in the template dependent polymerase inhibition”. Chinese Journal of Chemical Physics. In press.
Conference Papers:
272. C. Ma, Q. Yang, X. Gao, and X. Zhang. (2022). “DEMO: disentangled molecular graph generation via an invertible flow model”. The 31st International Conference on Information and Knowledge Management (CIKM2022). Atlanta, USA, October 2022.
271. X. Zhou, X. Liu, D. Zhai, J. Jiang, X. Gao, and X. Ji. (2022). “Prototype-anchored learning for learning with imperfect annotations”. The Thirty-ninth International Conference on Machine Learning (ICML 2022). Baltimore, USA, July 2022.
270. X. Chen, H. Alamro, M. Li, S. Gao, R. Yan, X. Gao and X. Zhang. (2022). “Target-aware Abstractive Related Work Generation with Contrastive Learning”. The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2022). Madrid, Spain, July 2022.
269. X. Zhou, X. Liu, D. Zhai, J. Jiang, X. Gao, and X. Ji. (2022). “Learning towards the largest margins”. The International Conference on Learning Representations (ICLR2022). Virtually online, April 2022.
268. X. Chen, M. Li, R. Yan, X. Gao, and X. Zhang. (2022). “Unsupervised mitigation of gender bias by character components: a case study of Chinese word embedding”. The 4th Workshop on Gender Bias in Natural Language Processing. Seattle, USA, July 2022.
2021
Journal Papers:
267. H. Kuwahara, and X. Gao. (2021). “Stable maintenance of a hidden switch as a way to increase the gene expression stability”. Nature Computational Science. 1: 62-70.
266. Y. Li, Z. Xu, W. Han, H. Cao, R. Umarov, A. Yan, M. Fan, H. Chen, C. Duarte, L. Li, P. Ho, and X. Gao. (2021). “HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes”. Microbiome. 9: 40.
265. R. Han, G. Li, and X. Gao. (2021). “Robust and ultrafast fiducial marker correspondence in electron tomography by a two-stage algorithm considering local constraints”. Bioinformatics. In press.
264. X. Liao, K. Hu, A. Salhi, Y. Zou, J. Wang, and X. Gao. (2021). “msRepDB: a comprehensive repetitive sequence database of over 80,000 species”. Nucleic Acids Research. In press.
263. X. Liao, M. Li, K. Hu, F. Wu, X. Gao, and J. Wang. (2021). “A sensitive repeat identification framework based on short and long reads”. Nucleic Acids Research. In press.
262. F. Napolitano, X. Xu, and X. Gao. (2021). “'Impact of computational approaches in the fight against COVID-19: an AI guided review of 17,000 studies”. Briefings in Bioinformatics. In press.
261. W. He, Y. Jiang, J. Jin, Z. Li, J. Zhao, B. Manavalan, R. Su, X. Gao, and L. Wei. (2021). “'Accelerating Bioactive Peptide Discovery via Mutual Information-based Meta-learning”. Briefings in Bioinformatics. In press.
260. S. Zhang, B. Yuan, J. Lam, J. Zhou, X. Zhou, G. Ramos-Mandujano, X. Tian, Y. Liu, R. Han, Y. Li, X. Gao, M. Li, M. Yang. (2021). “Structural and functional studies of the pyroptosis-related human Pannexin1 channel”. Cell Discovery. In press.
259. F. Napolitano, T. Rapakoulia, P. Annunziata, A. Hasegawa, M. Cardon, S. Napolitano, L. Vaccaro, A. Iuliano, L. Wanderlingh, T. Kasukawa, D. Medina, D. Cacchiarelli, X. Gao,D. Bernardo, and E. Arner. (2021). “Automatic identification of small molecules that promote cell conversion and reprogramming”. Stem Cell Reports. In press.
258. S. Chen, Y. Li, T. Zhang, X. Zhu, S. Sun, and X. Gao. (2021). “Lunar features detection for energy discovery via deep learning”. Applied Energy. In press.
257. J. Yin, J. Shen, X. Gao, and D. Crandall. (2021). “Graph Neural Network and Spatiotemporal Transformer Attention for 3D Video Object Detection from Point Clouds”. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). In press.
256. S. Albaradei, C. Neste, M. Thafar, A. Alsaedi, T. Gojobori, M. Essack, and X. Gao. “MetaCancer: A deep learning-based pan-cancer metastasis prediction model developed using multi-omics data”. Computational and Structural Biotechnology Journal. In press.
255. H. Kuwahara, X. Gao. (2021). “Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach”. Journal of Cheminformatics. In press.
254. M. Thafar, R. Olayan, S. Albaradei, V. Bajic, T. Gojobori, M. Essack, and X. Gao. (2021). “Drug-target interaction prediction using network embedding and ensemble learning”. Journal of Cheminformatics. In press.
253. I. Unarta, S. Cao, S. Kubo, W. Wang, P. Cheung, X. Gao, S. Takada, and X. Huang. (2021). “Role of bacterial RNA polymerase gate opening dynamics in DNA loading and antibiotics inhibition elucidated by quasi-Markov state model”. Proceedings of the National Academy of Sciences (PNAS). In press.
252. L. Zhu, H. Jiang, S. Cao, I. Unarta, X. Gao, and X. Huang. (2021). “Critical Role of Backbone Coordination in the mRNA recognition of RNA Induced Silencing Complex Elucidated by quasi-Markov State Model”. Communications Biology. In press.
251. N. Huang, F. Nie, P. Ni, X. Gao, F. Luo, and J. Wang. (2021). “BlockPolish: accurate polishing of long-read assemblyvia block divide-and-conquer”. Briefings in Bioinformatics. In press.
250. N. Huang, F. Nie, P. Ni, F. Luo, X. Gao, and J. Wang. (2021). “NeuralPolish: a novel Nanopore polishing method based on alignment matrix construction and orthogonal Bi-GRU networks”. Bioinformatics. In press.
249. H. Shamseldin, L. Al-Abdi, S. Maddirevula, H. Alsaif, F. Alzahrani, N. Ewida, M. Hashem, F. Abdulwahab, O. Abuyousef, H. Kuwahara, X. Gao, M. Consortium, F. Alkuraya. (2021). “Lethal variants in humans: Lessons learned from a large molecular autopsy cohort”. Genome Medicine. In press.
248. X. Zhang, Q. Yang, S. Albaradei, X. Lyu, A. Salhi, C. Ma, H. Alamro, M. Alshehri, I. Jaber, F. Tifratene, W. Wang, T. Gojobori, C. Duarte, and X. Gao. (2021). “Rise and fall of the global conversation and shifting sentiments during the COVID-19 pandemic”. Humanities and Social Sciences Communications (Nature Publishing Group). In press.
247. R. Umarov, Y. Li, T. Arakawa, S. Takizawa, X. Gao, and E. Arner. (2021). “ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation”. PLOS Computational Biology. In press.
246. S. Albaradei, F. Napolitano, M. Thafar, T. Gojobori, M. Essack, X. Gao. (2021). “Machine learning and deep learning methods that use omics data for metastasis prediction”. Computational and Structural Biotechnology Journal. In press.
245. K. Wang, R. Stevens, R. Khomtchouk, H. Alachram, Y. Li, L. Soldatova, R. King, S. Ananiadou, M. Li, F. Christopoulou, J. Ambite, S. Garg, U. Hermjakob, D. Marcu, E. Sheng, T. Beibarth, E. Wingender, A. Galstyan, X. Gao, B. Chambers, J. Evans, and A. Rzhetsky. (2021). “NERO: a biomedical named entity (recognition) ontology with a large, annotated corpus reveals meaningful associations through text embedding”. npj Systems Biology and Applications. In press.
244. H. Li, J. Zhou, Y. Zhou, Q. Chen, Y. She, F. Gao, Y. Xu, J. Chen, X. Gao. (2021). “An interpretable computer-aided diagnosis method for periodontitis from panoramic radiographs”. Frontiers in Physiology, section Computational Physiology and Medicine. In press.
243. M. Fan, Y. Cui, Y. Chao, L. Liu, Y. Gu, W. Peng, Q. Bai, X. Gao, and L. Li. (2021). “Radiogenomic signatures of Oncotype DX recurrence score predict survival in estrogen receptor-positive breast cancer: a multicohort study”. Radiology. In press.
242. M. Fan, W. Yuan, W. Liu, X. Gao, M. Xu, S. Wang, and L. Li. (2021). “A deep matrix factorization framework for identifying underlying tissue-specific patterns of DCE-MRI: applications for molecular subtype classification in breast cancer”. Physics in Medicine and Biology. In press.
241. D. Wu, W. Ye, G. Lin, X. Gao, and J. Shen. (2021). “Person re-identification by context-aware part attention and multi-head collaborative learning”. IEEE Transactions on Information Forensics & Security. In press.
240. D. Zhang, L. Yao, K. Chen, Z. Yang, X. Gao, and Y. Liu. (2021). “Preventing sensitive information leakage from mobile sensor signals via integrative transformation”. IEEE Transactions on Mobile Computing. In press.
239. L. Zhang, M. Fan, F. Napolitano, X. Gao, Y. Xu, and L. Li. (2021). “Transcriptomic analysis identifies organ-specific metastasis genes and pathways across different primary sites”. Journal of Translational Medicine. 19: 31.
238. S. Albaradei, M. Uludag, M. Thafar, T. Gojobori, M. Essack, X. Gao. (2021). “Predicting Bone Metastasis using Gene Expression-based Machine Learning Models”. Frontiers in Genetics, section Computational Genomics. In press.
237. M. Fan, H. Chen, C. You, L. Liu, Y. Gu, W. Peng, X. Gao, and L. Li. (2021). “Radiomics of tumor heterogeneity during longitudinal dynamic contrast-enhanced magnetic resonance imaging for predicting response to neoadjuvant chemotherapy in breast cancer”. Frontiers in Molecular Biosciences, section Molecular Diagnostics and Therapeutics. 7: 599333.
236. M. Aldosari, K. Yalamanchi, X. Gao, and M. Sarathy. (2021). “Predicting entropy and heat capacity of hydrocarbons using machine learning”. Energy and AI. 4: 100054.
235. K. Konovalov, W. Wang, G. Wang, E. Goonetilleke, X. Gao, D. Wang, X. Huang. (2021). “Markov State Models Reveal that 5-Carboxylcytosine Pauses Transcription by Directly Interacting with RNA Polymerase II and Indirectly Reducing Bridge Helix Kinking”. Journal of Biological Chemistry. In press.
234. L. Zhang, D. Zhang, X. Wang, C. Yuan, Y. Li, X. Jia, X. Gao, H. Yen, P. Cheung, and X. Huang. (2021). “Role of 1’-ribose cyano substitution for remdesivir to effectively inhibit nucleotide addition and proofreading in SARS-CoV-2 viral RNA replication”. Physical Chemistry Chemical Physics. In press.
233. A. Jameel, V. Oudenhoven, N. Naser, A. Emwas, X. Gao, S. Sarathy. (2021). “Predicting ignition quality of oxygenated fuels using artificial neural networks”. SAE International Journal of Fuels and Lubricants. In press.
232. C. Li, X. Gao, and Q. Sun. (2021). “Introduction of progress in education under recent technology revolution”. Mobile Networks and Applications. In press.
231. M. Fan, Z. Fu, M. Xu, S. Wang, X. Gao, Y. Wang and L. Li. (2021). “A Deep Matrix Completion Method for Imputing Missing Histological Data in Breast Cancer by Integrating DCE-MRI Radiomics”. Medical Physics. In press.
Conference Papers:
2020
Journal Papers:
229. F. Alzahrani, H. Kuwahara, Y. Long, M. Al-Owain, M. Tohary, M. AlSayed, M. Mahnashi, L. Fathi, M. Alnemer, M. Al-Hamed, G. Lemire, K. Boycott, M. Hashem, W. Han, A. Al-Maawali, F. Mzhrizi, K. Al-Thihli, X. Gao, and F. Alkuraya. Recessive deleterious variants in SMG8 expand the role of nonsense-mediated decay in developmental disorders in humans. The American Journal of Human Genetics. (2020) 117(6): 1178-1185.
228. L. Zhou, Z. Li, J. Zhou, H. Li, Y. Chen, Y. Huang, D. Xie, L. Zhao, M. Fan, S. Hashmi, F. AbdelKareem, R. Eiada, X. Xiao, L. Li, Z. Qiu, and X. Gao. A rapid, accurate and machine-agnostic segmentation and quantification method for CT-based COVID-19 diagnosis. IEEE Transactions on Medical Imaging. (2020) 39(8): 2638-2652.
227. S. Maddirevula, H. Kuwahara, N. Ewida, H. Shaseldin, N. Patel, F. Alzahrani, T. AlSheddi, E. AlObeid, M. Alenazi, H. Alsaif, M. Alqahtani, M. AlAli, H. AlAli, R. Helaby, N. Ibrahim, F. Abdulwahab, M. Hashem, N. Hanna, D. Monies, N. Derar, A. Alsagheir, A. Alhashem, B. Alsaleem, H. Alhebbi, S. Wali, R. Umarov, X. Gao, and F. Alkuraya. Analysis of transcript-deleterious variants in Mendelian disorders: implications for RNA-based diagnositics. Genome Biology. (2020) 21: 145.
226. T. Yu, Z. Mu, Z. Fang, X. Xiu, X. Gao, and J. Liu. TransBorrow: genome-guided transcriptome assembly by borrowing assemblies from different assemblers. Genome Research. (2020) 30(8): 1181-1190.
225. L. Ding, Y. Liu, L. Liu, F. Zhu, Y. Yao, L. Shao, and X. Gao. Approximate kernel selection via matrix approximation. IEEE Transactions on Neural Networks and Learning Systems (TNNLS). (2020) 31(11): 4881-4891.
224. C. Bi, L. Wang, B. Yuan, X. Zhou, Y. Li, S. Wang, Y. Pang, X. Gao, Y. Huang, and M. Li. Long-read individual-molecule sequencing reveals CRSPR-induced genetic heterogeneity in human ESCs. Genome Biology. (2020) 21: 213.
223. M. Kulmanov, F. Smaili, X. Gao, and R. Hoehndorf. Semantic similarity and machine learning with biomedical ontologies. Briefings in Bioinformatics. In press.
222. G. Messa, F. Napolitano, S. Elsea, D. di Bernardo, and X. Gao. Siamese neural networks for the prioritization of metabolic disorders by integrating real and simulated data. Bioinformatics. (2020) 36(2): i787-i794.
221. Y. Li, S. Wang, C. Bi, Z. Qiu, M. Li, and X. Gao. DeepSimulator1.5: a more powerful, quicker and lighter simulator for Nanopore sequencing. Bioinformatics. (2020) 36(8): 2578-2580.
220. T. Yu, J. Liu, X. Gao, and G. Li. iPAC: a genome-guided assembler of isoforms via phasing and combing paths. Bioinformatics. (2020) 36(9): 2712-2717.
219. F. Smaili, X. Gao, and R. Hoehndorf. Formal axioms in biomedical ontologies improve analysis and interpretation of associated data. Bioinformatics. (2020) 36(7): 2229-2236.
218. R. Li, L. Yu, B. Zhou. X. Zeng, Z. Wang, X. Yang, J. Zhang, X. Gao, R. Jiang, and M. Xu. Few-shot learning for classification of novel macromolecular structures in cryo-electron tomograms. PLOS Computational Biology. (2020) 16(11): e1008227.
217. Y. Zheng, H. Wang, Y. Zhang, X. Gao, E. Xing, and M. Xu. Poly(A)-DG: a deep-learning-based domain generalization method to identify cross-species poly(A) signal without prior knowledge from target species. PLOS Computational Biology. (2020) 16(11): e1008297.
216. H. Li, S. Tian, Y. Li, Q. Fang, R. Tian, Y. Pan, C. Huang, Y. Xu, and X. Gao. Modern deep learning in bioinformatics. Journal of Molecular Cell Biology. In press.
215. Z. Li, Y. Li. B. Zhang, Y. Li, Y. Long, J. Zhou, X. Zou, M. Zhang, Y. Hu, W. Chen, and X. Gao. DeeReCT-APA: prediction of alternative polyadenylation site usage through deep learning. Genomics, Proteomics, and Bioinformatics. In press.
214. H. Naveed, C. Kuttenberger, T. Schubert, X. Gao, S. Arold, and M. Maitland. A computational framework for constructing drug-binding site signatures to identify novel drug targets: a case study of kinase inhibitors. Genomics, Proteomics, and Bioinformatics. In press.
213. O. Motwalli, M. Uludag, I. Mijakovic, M. Alazmi, V. Bajic, T. Gojobori, X. Gao, and M. Essack. PATHcre8: a tool that facilitates the searching for heterologous biosynthetic routes. ACS Synthetic Biology. (2020) 9(12): 3217-3227.
212. A. Abdel-Haleem, V. Ravikumar, B. Ji, K. Mineta, X. Gao, J. Nielsen, T. Gojobori, and I. Mijakovic. Integrated metabolic modeling, culturing and transcriptomics explains enhanced virulence of V. cholerae during co-infection with ETEC. mSystems. (2020) 5(5): e00491-20.
211. M. Fan, Z. Liu, M. Xu, S. Wang, T. Zeng, X. Gao, and L. Li. Generative adversarial network-based super-resolution of diffusion-weighted imaging: application to tumour radiomics in breast cancer. NMR in Biomedicine. (2020) 33(8): e4345.
210. M. Fan, W. Zhao, W. Yuan, S. Wang, M. Xu, X. Gao, and L. Li. Joint prediction of breast cancer histological grade and Ki-67 expression level based on DCE-MRI and DWI radiomics. IEEE Journal of Biomedical and Health Informatics. (2020) 24(6): 1632-1642.
209. H. Li, J. Zhou, H. Sun, Z. Qiu, X. Gao, and Y. Xu. CaMeRe: a novel tool for inference of cancer metabolic reprogramming. Frontiers in Oncology, section Cancer Metabolism. (2020) 10: 207.
208. M. Fan, H. Zheng, S. Zheng, C. You, Y. Gu, X. Gao, W. Peng, and L. Li. Mass detection and segmentation in digital breast tomosynthesis using 3D-mask region-based convolutional neural network: a comparative analysis. Frontiers in Molecular Bioscience, section Molecular Diagnostics and Therapeutics. (2020) 7: 599333.
207. X. Liao, X. Gao, X. Zhang, F-X Wu, and J. Wang. RepAHR: an improved approach for de novo repeat identification by assembly of the high-frequency reads. BMC Bioinformatics. (2020) 20: 443.
206. C. Wang, X. Gao, and J. Liu. Impact of data preprocessing on cell-type clustering based on single-cell RNA-seq data. BMC Bioinformatics. (2020) 21: 440.
205. S. Liu, X. Ban, X. Zeng, F. Zhao, Y. Gao, W. Wu, H. Zhang, F. Chen, T. Hall, X. Gao, and M. Xu. A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulation. BMC Bioinformatics. (2020) 21: 399.
204. Y. Lu, X. Zeng, X. Tian, X. Shi, H. Wang, X. Zheng, X. Liu, X. Zhao, X. Gao, and M. Xu. Spark-based parallel calculation of 3D Fourier shell correlation for macromolecule structure local resolution estimation. BMC Bioinformatics. (2020) 20: 443.
203. R. Tan, H. Li, Z. Huang, Y. Zhou, M. Tao, X. Gao, and Y. Xu. Neural functions play different roles in triple negative breast cancer (TNBC) and non-TNBC. Scientific Reports. (2020) 10: 3065.
202. G. Othman, S. Prigent, A. Derouiche, L. Shi, A. Bokhari, S. Alamoudi, S. Bougouffa, X. Gao, R. Hoehndorf, S. Arold, T. Gojobori, H. Hirt, F. Lafi, J. Nielsen, V. Bajic, I. Mijakovic, and M. Essack. Comparative genomics study reveals Red Sea Bacillus with characteristics associated with potential microbial cell factories. Scientific Reports. (2020) 9: 19254.
201. H. Wang, C. Yang, X. Zhang, and X. Gao. Efficient locality-sensitive hashing over high-dimensional streaming data. Neural Computing and Applications. In press.
200. Z. Xu, Y. Ke, X. Cao, C. Zhou, P. Wei, and X. Gao. A unified linear convergence analysis of k-SVD. Memetic Computing. (2020) 12: 343-353.
199. T. Zhang, Y. Li, Y. Li, S. Sun, and X. Gao. A self-adaptive deep learning algorithm for accelerating multi-component flash calculation. Computer Methods in Applied Mechanics and Engineering. (2020) 369: 113207.
198. S. Rauf, K. Kahin, S. Alshehri, S. Abdelrahman, H. Susapto, J. Lam, S. Asad, S. Jhadav, D. Sunderamoorthy, X. Gao, and C. Hauser. Self-assembling tetrameric peptides allow in situ 3D bioprinting under physiological conditions. Journal of Materials Chemistry B. In press.
197. S. Albaradei, F. Napolitano, M. UUludag, M. Thafar, S. Napolitano, M. Essack, V. Bajic, and X. Gao. Automated counting of colony forming units using deep transfer learning from a model for congested scenes analysis. IEEE Access. (2020) 8: 164340-164346.
196. K. Yalamanchi, M. Monge-Palacios, V. van Oudenhoven, X. Gao, and M. Sarathy. A data science approach to estimate enthalpy of formation of cyclic hydrocarbons. The Journal of Physical Chemistry A. (2020) 124(31): 6270-6276.
195. M. Thafar, R. Olyan, H. Ashoor, S. Albaradei, V. Bajic, X. Gao, T. Gojobori, and M. Essack. DTiGEMS+: drug-target interaction prediction using graph embedding, graph mining, and similarity-based techniques. Journal of Cheminformatics. (2020) 12: 44.
194. K. Niu, J. Guo, Y. Pan, X. Peng, H. Li, X. Gao, and N. Li. Multi-channel deep attention neural networks for the classification of autism spectrum disorder using neuroimaging and personal characteristic data. Complexity. (2020) 2020: 1357853.
193. F. Chen, Y. Jiang, X. Zeng, J. Zhang, X. Gao, and M. Xu. PUB-SalNet: a pre-trained unsupervised self-aware backpropagation network for biomedical salient segmentation. Algorithms. (2020) 13(5): 126.
192. S. Kanwal, N. Ann, S. Fatima, A. Emwas, M. Alazmi, X. Gao, M. Ibrar, R. Saleem, and G. Chotana. Facile synthesis of NH-free 5-(Hetero)Aryl-Pyrrole-2-Carboxylates by catalytic C-H borylation and Suzuki coupling. Molecules. (2020) 25(9): 2106.
191. Y. Yang, Y. Ma, J. Zhang, X. Gao, and M. Xu. AttPNet: attention-based deep neural network for 3D point set analysis. Sensors. (2020) 20(19): 5455.
Conference Papers:
190. G. Messa, F. Napolitano, S. Elsea, D. di Bernardo, and X. Gao. Siamese neural networks for the prioritization of metabolic disorders by integrating real and simulated data. The 19th European Conference on Computational Biology (ECCB2020). Virtually held, August 2020.
189. H. Li, J. Zhou, Y. Zhou, J. Chen, F. Gao, Y. Xu, and X. Gao. Automatic and interpretable model for periodontitis diagnosis in panoramic radiographs.The 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2020). Virtually held, October 2020.
188. X. Chen, H. Dai, Y. Li, X. Gao, and L. Song. Learning to stop while learning to predict. The Thirty-seventh International Conference on Machine Learning (ICML 2020). Virtually held, July 2020.
187. X. Chen, Y. Li, R. Umarov, X. Gao, and L. Song. RNA secondary structure prediction by learning unrolled algorithms. The International Conference on Learning Representations (ICLR2020). Addis Ababa, Ethiopia, April 2020. (Oral. Acceptance rate 1.88%).
186. Y. Lu, X. Zeng, X. Tian, X. Shi, H. Wang, X. Zheng, X. Liu, X. Zhao, X. Gao, and M. Xu. Spark-based parallel calculation of 3D Fourier shell correlation for macromolecule structure local resolution estimation. The 18th Asia Pacific Bioinformatics Conference (APBC 2020). Seoul, Korea, February 2020.
2019
Journal Papers:
185. J.H. Lam, Y. Li, L. Zhu, R. Umarov, H. Jiang, A. Heliou, F.K. Sheong, T. Liu, Y. Long, Y. Li, L. Fang, R. Altman, W. Chen, X. Huang, and X. Gao. A deep learning framework to predict binding preference of RNA constituents on protein surface. Nature Communications. (2019) 10: 4941.184. G. Jia, Y. Li, H. Zhang, I. Chattopadhyay, A.B. Jensen, D. Blair, L. Davis, P. Robinson, T. Dahlen, S. Brunak, M. Benson, G. Edgren, N. Cox, X. Gao, and A. Rzhetsky. Estimating heritability and genetic correlations from large health datasets in the absence of genetic data. Nature Communications. (2019) 10: 5508.
183. C. Tse, J. Xu, L. Xu, F.K. Sheong, S. Wang, H.Y. Chow, X. Gao, X. Li, P. Cheung, D. Wang, Y. Zhang, and X. Huang. Intrinsic cleavage of RNA polymerase II adopts a nucleobase-independent mechanism assisted by transcript phosphate. Nature Catalysis. (2019) 2, 228-335.
182. J. Lei, G. Sheng, P. Cheung, S. Wang, Y. Li, X. Gao, Y. Zhang, Y. Wang, and X. Huang. Two symmetric arginine residues play distinct roles in thermus thermophilus argonaute DNA guide strand-mediated DNA target cleavage. Proceedings of the National Academy of Sciences of the United States of America (PNAS). (2019) 116(3): 845-853.
181. R. Han, S. Wang, and X. Gao. Novel algorithms for efficient subsequence searching and mapping in nanopore raw signals towards targeted sequencing. Bioinformatics. In press.180. T. Alam, M. Alazmi, R. Naser, F. Huser, A. Momin, V. Astro, S. Hong, K. Walkiewicz, C. Canlas, R. Huser, A. Ali, J. Merzaban, A. Adamo, M. Jaremko, L. Jaremko, V. Bajic, X. Gao, and S. Arold. Proteome-level assessment of origin, prevalence and function of Leucine-Asparrtic Acid (LD) motfis. Bioinformatics. In press.
179. R. Han, L. Li, P. Yang, F. Zhang, and X. Gao. A novel constrained reconstruction model towards better information fusion in high-resolution subtomogram averaging. Bioinformatics. In press.
178. R. Han, Z. Bao, X. Zeng, T. Niu, F. Zhang, M. Xu, and X. Gao. A joint method for marker-free alignment of tilt series in electron tomography. Bioinformatics. (2019) 35(14): i249-i259.
177. M. Alazmi, H. Kuwahara, O. Soufan, L. Ding, and X. Gao. Systematic selection of chemical fingerprint features improves the Gibbs energy prediction of biochemical reactions. Bioinformatics. (2019) 35(15): 2634-2643.
176. Z. Xia, Y. Li, B. Zhang, Z. Li, Y. Hu, W. Chen, and X. Gao. DeeReCT-PolyA: a robust and generic deep learning method for PAS identification. Bioinformatics. (2019) 35(14): 2371-2379. 175. F. Napolitano, D. Carrella, X. Gao, and D. di Bernardo. gep2pep: a Bioconductor package for the creation and analysis of pathway-based expression profiles. Bioinformatics. In press.
174. R. Umarov, H. Kuwahara, Y. Li, X. Gao, and V. Solovyev. Promoter analysis and prediction in the human genome using sequence-based deep learning models. Bioinformatics. (2019) 35(16): 2730-2737. 173. F. Smaili, X. Gao, and R. Hoehndorf. OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction. Bioinformatics. (2019) 35(12): 2133-2140.
172. C. Mottini, F. Napolitano, Z. Li, X. Gao, and L. Cardone. Computer-aided drug repurposing for cancer therapy: approaches and opportunities to challenge anticancer targets. Seminars in Cancer Biology. In press.
171. U. Hameed, C. Liao, A. Radhakrishnan, F. Huser, S. Aljedani, X. Zhao, A. Momin, F. Melo, X. Guo, C. Brooks, Y. Li, X. Cui, X. Gao, J. Ladbury, L. Jaremko, M. Jaremko, J. Li, and S. Arold. H-NS uses an autoinhibitory conformational switch for environment-controlled gene silencing. Nucleic Acids Research. (2019) 47(5): 2666-2680.
170. F. Smaili, S. Tian, A. Roy, M. Alazmi, S. Arold, S. Mukherjee, S. Hefty, W. Chen, and X. Gao. QAUST: protein function prediction using structure similarity search, protein interaction and functional sequence motifs. Genomics, Proteomics, and Bioinformatics. In press.
169. X. Zou, X. Gao, and W. Chen. Deep learning deepens the analysis of alternative splicing. Genomics, Proteomics, and Bioinformatics. (2019) 17(2): 219-221.
168. Z. Zhang, J. Yu, F. Eisenhaber, X. Gao, and T. Gojobori. In memory of Vladimir B. Bajic (1952-2019). Genomics, Proteomics, and Bioinformatics. (2019) S1672-0229: 30165-2.
167. M. Fan, P. Xia, B. Liu, L. Zhang, Y. Wang, X. Gao, and L. Li. Tumor heterogeneity revealed by unsupervised decomposition of dynamic contrast-enhanced magnetic resonance imaging is sssociated with underlying gene expression patterns and poor survival in breast cancer patients. Breast Cancer Research. (2019) 21(1): 112.
166. M. Fan, Z. Liu, S. Xie, M. Xu, S. Wang, X. Gao, and L. Li. Integration of dynamic contrast-enhanced magnetic resonance imaging and T2-weighted imaging radiomic features by a canonical correlation analysis-based feature fusion method to predict histological grade in ductal breast carcinoma. Physics in Medicine and Biology. (2019) 64(21): 215001.
165. Y. Li, T. Zhang, S. Sun, and X. Gao. Accelerating flash calculation through deep learning methods. Journal of Computational Physics. (2019) 394: 153-165.
164. Y. Li, C. Huang, L. Ding, Z. Li, Y. Pan, and X. Gao. Deep learning in bioinformatics: introduction, application and perspective in big data era. Methods. (2019) 166: 4-21.
163. W. Wang, and X. Gao. Deep learning in bioinformatics. Methods. (2019) 166: 1-3.
162. K. Yalamanchi, V. van Oudenhoven, F. Tutino, M. Monge-Palacios, A. Alshehri, X. Gao, and M. Sarathy. Machine learning to predict standard enthalpy of formation of hydrocarbons. The Journal of Physical Chemistry. (2019) 123(38): 8305-8313.
161. Z. Zou, S. Tian, X. Gao, and Y. Li. mIDEEPre: multi-function enzyme function prediction with hierarchical multi-label deep learning. Frontiers in Genetics, section Bioinformatics and Computational Biology. (2019) 9: 714.
160. M. Fan, P. Zhang, S. Wang, X. Gao, W. Peng, Y. Wang, M. Xu, and L. Li. Radiomic analysis of imaging heterogeneity in tumors and the surrounding parenchyma based on unsupervised decomposition of DCE-MRI for predicting molecular subtypes in breast cancer. European Radiology. (2019) 29(8): 4456-4467.
159. Y. Lu, X. Zeng, X. Zhao, S. Li, H. Li, X. Gao, and M. Xu. Fine-grained alignment of cryo-electron subtomograms based on MPI parallel optimization. BMC Bioinformatics. (2019) 20: 443.
158. S. Kanwal, N. Ann, A-H. Emwas, M. Alazmi, S. Fatima, X. Gao, G. Chotana. Synthesis of 5-Aryl 1H-Pyrrole-2-Carboxylate esters by Iridium-catalyzed borylation and suzuki coupling. ChemistrySelect. (2019) 4(5): 1753-1756.
Conference Papers:
157. R. Han, Z. Bao, X. Zeng, T. Niu, F. Zhang, M. Xu, and X. Gao. A joint method for marker-free alignment of tilt series in electron tomography. The 27th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2019), Basel, Switzerland, July 2019. (Acceptance rate 18.9%).
156. P. Han, P. Yang, P. Zhao, S. Shang, Y. Liu, J. Zhou, X. Gao, and P. Kalnis. GCN-MF: disease-gene association identification by graph convolutional networks and matrix factorization. The 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019), Anchorage, U.S., August 2019. (Oral presentation, acceptance rate 9.2%).
155. Z. Li, C. Ni, J. Xu, X. Gao, S. Cui, and S. Wang. Transmembrane topology identification by fusing evolutionary and co-evolutionary information with cascaded bidirectional transformers. ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2019 (ACM-BCB2019), Niagara Falls, U.S., September 2019. (Acceptance rate 26.1%).
154. C. Che, Z. Xian, X. Zeng, X. Gao, and M. Xu. Domain randomization for macromolecule structure classification and segmentation in electron cryo-tomograms. The 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019). San Diego, U.S., November 2019. (Acceptance rate 18%).
153. X. Wu, Y. Mao, H. Wang, X. Zeng, X. Gao, E. Xing, and M. Xu. Regularized adversarial training (RAT) for robust cellular electron cryo tomograms classification. The 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2019). San Diego, U.S., November 2019. (Acceptance rate 18%).
152. P. Yang, P. Zhao, J. Zhou, and X. Gao. Second order online multitask learning. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, U.S., January 2019. (Acceptance rate 16.2%).
151. L. Ding, Z. Liu, Y. Li, S. Liao, Y. Liu, P. Yang, G. Yu, L. Shao, and X. Gao. Linear kernel tests via emperical likelihood for high dimensional data. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, U.S., January 2019. (Acceptance rate 16.2%).
150. L. Ding, S. Liao, Y. Liu, P. Yang, Y. Li, Y. Pan, C. Huang, L. Shao, and X. Gao. Approximate kernel selection with strong approximate consistency. The Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), Honolulu, U.S., January 2019. (Acceptance rate 16.2%).
2018
Journal Papers:
149. S. Wang, S. Fei, Z. Wang, Y. Li, J. Xu, F. Zhao, and X. Gao. PredMP: a web server for de novo prediction and visualization of membrane proteins. Bioinformatics. (2018) 35(4): 691-693.
148. R. Han, X. Wan, L. Li, A. Lawrence, P. Yang, Y. Li, S. Wang, F. Sun, Z. Liu, X. Gao, and F. Zhang. AuTom-dualx: a toolkit for fully automatic fiducial marker-based alginment of dual-axis tilt series with simultaneous reconstruction. Bioinformatics. 35(2): 319-328.
147. R. Han, Y. Li, X. Gao, and S. Wang. An accurate and rapid continuous wavelet dynamic time warping algorithm for end-to-end mapping in ultra-long nanopore sequencing. Bioinformatics. (2018). 34(17): i722-i731.
146. Y. Li, R. Han, C. Bi, M. Li, S. Wang, and X. Gao. DeepSimulator: a deep simulator for Nanopore sequencing. Bioinformatics. (2018). 34(17): 2899-2908.
145. J. Kim, X. Gao, and A. Rzhetsky. RIDDLE: Race and ethnicity Imputation from Disease history with dDeep LEarning. PLOS Computational Biology. (2018). 14(4): e1006106.
144. A. Khamis, O. Motwalli, R. Oliva, B. Jankovic, Y. Medvedeva, H. Ashoor, M. Essack, X. Gao, and V. Bajic. A novel method for improved accuracy of transcription factor binding site prediction. Nucleic Acids Research. (2018). 46(12): e72.
143. Y. Li, F. Xu, F. Zhang, P. Xu, M. Zhang, M. Fan, L. Li, X. Gao, and R. Han. DLBI: deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy. Bioinformatics, (2018). 34(13): i284-i294.
142. F. Smaili, X. Gao, and R. Hoehndorf. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations. Bioinformatics, (2018). 34(13): i52-i60.
141. Y. Li, S. Wang, R. Umarov, B. Xie, M. Fan, L. Li, and X. Gao. DEEPre: sequence-based enzyme EC number prediction by deep learning. Bioinformatics. (2018). 34(5): 760-769.
140. R. Han, F. Zhang, and X. Gao. A fast fiducial marker tracking model for fully automatic alignment in electron tomography. Bioinformatics. (2018). 34(5): 853-863.
139. A. Abdel-Haleem, H. Hefzi, K. Mineta, X. Gao, T. Gojobori, B. Palsson, N. Lewis, and N. Jamshidi. Functional interrogation of Plasmodium genus metabolism identifies species- and stage-specific differences in nutrient essentiality and drug targeting. PLOS Computational Biology. (2018). 14(1): e1005895.
138. S. Wang, Z. Li, Y. Yu, and X. Gao. WaveNano: a signal-level nanopore base-caller via simultaneous prediction of nucleotide labels and move labels through bi-directional WaveNets. Quantitative Biology. 6(4): 359-368.
137. G. Othoum, S. Bougouffa, R. Razali, A. Bokhari, S. Alamoudi, A. Antunes, X. Gao, R. Hoehndorf, S. Arold, T. Gojobori, H. Hirt, I. Mijakovic, V. Bajic, F. Lafi, and M. Essack. In silico exploration of red sea bacillus genomes for natural product biosynthesis gene clusters. BMC Genomics. (2018). 19: 382.
136. M. Fan, T. He, P. Zhang, H. Cheng, J. Zhang, X. Gao, and L. Li. Diffussion-weighted imaging features of breast tumours and the surrounding stroma reflect intrinsic heterogeneous characteristics of molecular subtypes in breast cancer. NMR in Biomedicine. (2018). 31: e3869.
135. M. Fan, H. Cheng, P. Zhang, X. Gao, J. Zhang, G. Shao, and L. Li. DCE-MRI texture analysis with tumor subregion partitioning for predicting Ki-67 of estrogen receptor-positive breast cancers. Journal of Magnetic Resonance Imaging. (2018). 48(1): 237-247.
134. M. Alazmi, A. Abbas, X. Guo, M. Fan, L. Li, and X. Gao. A slice-based 13C-detected NMR spin system forming and resonance assignment method. IEEE/ACM Transactions on Computational Biology and Bioinformatics. (2018). 15(6): 1999-2008.
133. S. Manzoor, A. Bilal, S. Khan, R. Ullah, S. Iftikhar, A. Emwas, M. Alazmi, X. Gao, A. Jawaid, R. Saleem, and A. Faisal. Identification and characterization of SSE15206, a microtubule depolymerizing agent that overcomes multidrug resistance. Scientific Reports. (2018). 8: 3305.
132. A. Emwas, E. Saccenti, X. Gao, R. McKay, V. dos Santos, R. Roy, and D. Wishart. Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine. Metabolomics. (2018). 14(3): 31.
131. S. Farrukh, I. Javed, A. Ather, A. Emwas, M. Alazmi, X. Gao, G. Chotana, T. Davis, P. Ke, R. Saleem. Synthesis and identification of novel pryidazinylpyrazolone based diazo compounds as inhibitors of human islet amyloid polypeptide aggregation. Bioorganic Chemistry. (2018). 84: 339-346.
Conference Papers:
130. Y. Li, F. Xu, F. Zhang, P. Xu, M. Zhang, M. Fan, L. Li, X. Gao, and R. Han. DLBI: deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopy. The 26th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2018), Chicago, U.S., July 2018. (Acceptance rate 19.6%).
129. F. Smaili, X. Gao, and R. Hoehndorf. Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations. The 26th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2018), Chicago, U.S., July 2018. (Acceptance rate 19.6%).
128. R. Han, Y. Li, X. Gao, and S. Wang. An accurate and rapid continuous wavelet dynamic time warping algorithm for end-to-end mapping in ultra-long nanopore sequencing. The 17th European Conference on Computational Biology (ECCB 2018), Athens, Greece, September 2018. (Acceptance rate 17%).
127. Z. Xu, X. Cao, and X. Gao. Convergence analysis of gradient descent for top-k eigenspace computation. The 27th International Joint Conference on Artificial Intelligence and The 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-18), Stockholm, Sweden, July 2018. (Acceptance rate 20.46%).
126. P. Yang, P. Zhao, and X. Gao. Bandit online learning on graphs via adaptive optimization. The 27th International Joint Conference on Artificial Intelligence and The 23rd European Conference on Artificial Intelligence (IJCAI-ECAI-18), Stockholm, Sweden, July 2018. (Acceptance rate 20.46%).
125. P. Yang, P. Zhao, V. Zheng, L. Ding, and X. Gao. Robust asymmetric recommendation via min-max optimization. The 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR 2018), Ann Arbor, U.S., July 2018. (Acceptance rate 30%).
124. L. Ding, S. Liao, Y. Liu, P. Yang, and X. Gao. Randomized kernel selection with spectra of multilevel circulant matrices. The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, U.S., February 2018. (Acceptance rate 25%).
123. Z. Xu, Y. Ke, and X. Gao. On the truly block eigensolvers via first-order Riemannian optimization. The 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018). Playa Blanca, Canary Islands, April 2018. (Acceptance rate 33.2%).
122. P. Yang, P. Zhao, Y. Liu, and X. Gao. Robust cost-sensitive learning for recommendation with implicit feedback. SIAM International Conference on Data Mining (SDM18), San Diego, U.S., May 2018. (Acceptance rate 23.2%).
121. B. Zhou, Q. Guo, K. Wang, X. Zeng, X. Gao, and M. Xu. Feature decomposition-based saliency detection in electron cryo-tomograms. The 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2018), Madrid, Spain, December 2018.
2017
Journal Papers:
120. H. Dai, R. Umarov, H. Kuwahara, Y. Li, L. Song, and X. Gao. Sequence2Vec: a novel embedding approach for modeling transcription factor binding affinity landscape. Bioinformatics. (2017) 33(22): 3575-3583.
119. T. Rapakoulia, X. Gao, Y. Huang, M. de Hoon, M. Okada-Hatakeyama, H. Suzuki, E. Arner. Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment. Bioinformatics. (2017). 33(23): 3696-3700.
118. M. Alzahrani, H. Kuwahara, W. Wang, and X. Gao. Gracob: a novel graph-based constant-column biclustering method for mining growth phenotype data. Bioinformatics. (2017). 33(16): 2523-2531.
117. P. Yang, P. Zhao, and X. Gao. Robust online multi-task learning with correlative and personalized structures. IEEE Transactions on Knowledge and Data Engineering (TKDE). (2017). 29(11): 2510-2521.
116. S. Wu, D. Wang, J. Liu, Y. Feng, J. Weng, Y. Li, X. Gao, J. Liu, and W. Wang. The dynamic multisite interactions between two intrinsically disordered proteins. Angewandte Chemie. (2017). 56(26): 7515-7519.
115. H. Kuwahara, X. Cui, R. Umarov, R. Grunberg, C. Myers, and X. Gao. SBOLme: a repository of SBOL parts for metabolic engineering. ACS Synthetic Biology. (2017). 6(4): 732-736.
114. J. Wang, I. Tsang, X. Cui, Z. Lu, and X. Gao. Multi-instance dictionary learning via multivariate performance measure optimization. Pattern Recognition. (2017) 66: 448-459.
113. H. Kuwahara, R. Umarov, I. Almasri, and X. Gao. ACRE: absolute concentration robustness exploration in module-based combinatorial networks. Synthetic Biology. (2017) 2(1): ysx001.
112. R. Han, X. Wan, Z. Wang, Y. Hao, Y. Chen, X. Gao, Z. Liu, F. Ren, F. Sun, and F. Zhang. AuTom: a novel automatic platform for electron tomography reconstruction. Journal of Structural Biology. (2017). 199(3): 196-208.
111. S. Pandit, V. Ravikumar, A. Abdel-Haleem, A. Derouiche, V. Mokkapati, C. Sihlbom, K. Mineta, T. Gojobori, X. Gao, F. Westerlund, and I. Mijakovic. Low concentrations of vitamin C reduce the synthesis of extracellular polymers and destabilize bacterial biofilms. Frontiers in Microbiology, section Antimicrobials, Resistance and Chemotherapy. (2017). 8: 2599.
110. A. Abdel-Haleem, N. Lewis, N. Jamshidi, K. Mineta, X. Gao, and T. Gojobori. The emerging facets of noncancerous Warburg effect. Frontiers in Endocrinology, section Cellular Endocrinology. (2017). 8: 279.
109. J. Wang, X. Cui, G. Yu, L. Guo, and X. Gao. When sparse coding meets ranking: a joint framework for learning sparse coding and ranking scores. Neural Computing and Applications. (2017). 31(3): 701-710.
108. S. Najibi, M. Maadooliat, L. Zhou, J. Huang, and X. Gao. Protein structure classification and loop modeling using multiple Ramachandran distributions. Computational and Structural Biotechnology Journal. (2017) 15: 243-254.
107. J. Weng, S. Gu, X. Gao, X. Huang, and W. Wang. Maltose binding protein effectively stabilizes the partially closed conformation of the ATP-binding cassette transporter MalFGK2. Physical Chemistry Chemical Physics. (2017). 19: 9366-9373.
106. O. Motwalli, M. Essack, B. Jankovic, B. Ji, X. Liu, H. Rahman, R. Hoehndorf, X. Gao, S. Arold, K. Mineta, J. Archer, T. Gojobori, I. Mijakovic, and V. Bajic. In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria. BMC Genomics. (2017) 18: 33.
105. S. Lftikhar, S. Khan, A. Bilal, S. Manzoor, M. Abdullah, A. Emwas, S. Sioud, X. Gao, G. Chotana, A. Faisal, and R. Saleem. Synthesis and evaluation of modified chalcone based p53 stabilizing agents. Bioorganic & Medicinal Chemistry Letters. (2017) 27(17):4101-4106.
104. L. Zhu, H. Jiang, F.K. Sheong, X. Cui, Y. Wang, X. Gao, and X. Huang. Understanding the core of RNA interference: the dynamic aspects of Argonaute-mediated processes. Progress in Biophysics and Molecular Biology. (2017). 128: 39-46.
103. F. Batool, A. Emwas, X. Gao, M. Munawar, and G. Chotana. Synthesis and Suzuki cross-coupling reactions of 2,6-Bis(trifluoromethyl)pyridine-4-boronic acid pinacol ester. Synthesis. (2017) 49(6): 1327-1334.
102. X. Cui, and X. Gao. K-nearest uphill clustering in the protein structure space. Neurocomputing. (2017) 220: 52-59.
101. C. Fujii, H. Kuwahara, G. Yu, L. Guo, and X. Gao. Learning gene regulatory networks from gene expression data using weighted consensus. Neurocomputing. (2017) 220: 23-33.
Conference Papers:
100. Z. Xu, Y. Ke, and X. Gao. A fast algorithm for matrix eigen-decomposition. The 33rd Conference on Uncertainty in Artificial Intelligence (UAI2017), Sydney, Australia, August 2017. (Acceptance rate 31%).
99. Y. Niu, Z. Lu, S. Huang, X. Gao, J. Wen, and A. Zhao. FeaBoost: Joint feature and label refinement for semantic segmentation. The Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), San Francisco, U.S., February 2017. (Acceptance rate 24.63%).
2016
Journal Papers:
98. L. Da, F. Pardo-Avila, L. Xu, D. Silva, L. Zhang, X. Gao, D. Wang, and X. Huang. Bridge helix bending promoters RNA polymerase II backtracking through a critical and conserved Threonine residue. Nature Communications. (2016) 7:11244. [Highlighted by EurekAlert!: https://www.eurekalert.org/pub_releases/2016-05/hkuo-srh050316.php]
97. Y. Feng, L. Zhang, S. Wu, Z. Liu, X. Gao, X. Zhang, M. Liu, J. Liu, X. Huang, and W. Wang. Comformational dynamics of apo-GlnBP revealed by experimental and computational analysis. Angewandte Chemie. (2016) 55: 13990-13994.
96. H. Kuwahara, M. Alazmi, X. Cui, and X. Gao. MRE: a web tool to suggest foreign enzymes for the biosynthesis pathway design with competing endogenous reactions in mind. Nucleic Acids Research. (2016) 44(W1): W217-25. [Highlighted by PHYS.ORG: https://phys.org/news/2016-07-metabolic-route-explorer-optimize-pathways.html]
95. A. Salhi, M. Essack, A. Radovanvic, B. Marchand, S. Bougouffa, A. Antunes, M. Simoes, F. Lafi, O. Motwalli, A. Bokhari, T. Malas, S. Al Amoudi, G. Othoum, I. Alam, K. Mineta, X. Gao, R. Hoehndorf, J. Archer, T. Gojobori, and V. Bajic. DESM: Portal for microbial knowledge exploration systems. Nucleic Acids Research. (2016) 44(D1): D624-D633.
94. X. Cui, Z. Lu, S. Wang, J. Wang, and X. Gao. CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction. Bioinformatics. (2016) 32(12): 332-340.
93. Z. Lu, Z. Fu, T. Xiang, P. Han, L. Wang, and X. Gao. Learning from weak and noisy labels for semantic segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI). (2016) 39(3): 486-500.
92. E. Smirnova, J. Kwan, R. Siu, X. Gao, G. Zoidl, B. Demeler, V. Saridakis, and L. Donaldson. A new mode of SAM domain mediated oligomerization observed in the CASKIN2 neuronal scaffolding protein. Cell Communication and Signaling. (2016) 14:17.
91. L. Zhu, H. Jiang, F. K. Sheong, X. Cui, X. Gao, Y. Wang, and X. Huang. A flexible domain-domain hinge promotes an induced-fit dominant mechanism for the loading of guide-DNA into Argonaute protein in Thermus Thermophilus. Journal of Physical Chemistry B. (2016) 120(10): 2709-2720.
90. A. Emwas, R. Roy, R. McKay, D. Ryan, L. Brennan, L. Tenori, C. Luchinat, X. Gao, A. Zeri, N. Gowda, D. Raftery, C. Steinbeck, R. Salek, and D. Wishart. Recommendations and standardization of biomarker quantification using NMR-based metabolomics with particular focus on urinary analysis. Journal of Proteome Research. (2016) 15(2): 360-373.
89. T. Ryu, L. Seridi, L. Moitinho-Silva, M. Otates, Y. Liew, H. Marvromatis, X. Wang, A. Haywood, F. Lafi, M. Kupresanin, R. Sougrat, M. Alzahrani, E. Giles, Y. Ghoseh, C. Schunter, S. Baumgarten, M. Berumen, X. Gao, M. Aranda, S. Foret, J. Gough, C. Voolstra, U. Hentschel, and T. Ravasi. Hologenome analysis of two marine sponges with different microbiomes. BMC Genomics. (2016) 17:158.
88. I. Alabdulmohsin, M. Cisse, X. Gao, and X. Zhang. Large margin classification with indefinite similarities. Machine Learning. (2016) 103(2): 215-237.
Conference Papers:
87. X. Cui, Z. Lu, S. Wang, J. Wang, and X. Gao. CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction. The 24th Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2016), Orlando, U.S., July 2016. (Acceptance rate 21%).
86. J. Wang, I. Tsang, and X. Gao. Optimizing multivariate performance measures from multi-view data. The Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, U.S., February 2016. (Acceptance rate 25.75%).
2015
Journal Papers:
85. H. Naveed, U. Hameed, D. Harrus, W. Bourguet, S. Arold, and X. Gao. An integrated structure- and system-based framework to identify new targets of metabolites and known drugs. Bioinformatics. (2015) 31(24): 3922-3929. [Highlighted by Nature Middle East: http://www.natureasia.com/en/nmiddleeast/article/10.1038/nmiddleeast.2015.153]
84. H. Jiang, F. K. Sheong, L. Zhu, X. Gao, J. Bernauer, and X. Huang. Markov state models reveal a two-step mechanism of miRNA loading into the human Argonaute protein: selective binding followed by structural re-arrangement. PLOS Computational Biology. (2015) 11(7): e1004404.
83. X. Cui, H. Naveed, and X. Gao. Finding optimal interaction interface alignments between biological complexes. Bioinformatics. (2015) 31(12): i133-i141.
82. M. Fan, H. Kuwahara, X. Wang, S. Wang, and X. Gao. Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comprative study. Briefings in Bioinformatics. (2015) 16(6): 987-999.
81. A. Khamis, M. Essack, X. Gao, and V. Bajic. Distinct profiling of antimicrobial peptide families. Bioinformatics. (2015) 31(6): 849-856.
80. M. Maadooliat, L. Zhou, S. Najibi, X. Gao, and J. Huang. Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling. Journal of the American Statistical Association (JASA). (2015) 111(513): 43-56.
79. H. Kuwahara, S. Arold, and X. Gao. Beyond initiation-limited translational bursting: the effects of burst size distributions on the stability of gene expression. Integrative Biology. (2015) 7:1622-1632.
78. P. Chen, B. Wang, J. Zhang, X. Gao, J. Li, and J. Xia. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics. (2015) 13(5): 901-912.
77. F. Batool, S. Perveen, A. Emwas, S. Sioud, X. Gao, M. Munawar, and G. Chotana. Synthesis of fluoroalkoxy substituted aryl boronic esters by iridium catalyzed aromatic C-H borylation. Organic Letters. (2015) 17(17): 4256-9.
76. S. Sun, X. Wang, X. Gao, L. Ren, X. Sun, D. Bu, and K. Ning. Preprocess and condensation of Raman spectrum for single-cell phenotype analysis. BMC Bioinformatics. (2015) 16(S18): S15.
75. C. Cannistraci, A. Abbas, and X. Gao. Median modified Wiener filter for nonlinear adaptive spatial denoising of protein NMR multidimensional spectra. Scientific Reports. (2015) 5:8017.
74. J. Wang, and X. Gao. Max-min distance nonnegative matrix factorization. Neural Networks. (2015) 61: 75-84.
73. J. Wang, Y. Wang, B.-Y. Jing, and X. Gao. Regularized maximum correntropy machine. Neurocomputing. (2015) 160: 85-92.
72. J. Wang, Y. Wang, S. Zhao, and X. Gao. Maximum mutual information regularized classification. Engineering Applications of Artificial Intelligence. (2015). 37: 1-8.
71. J. Wang, J. Huang, Y. Sun, and X. Gao. Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization. Expert Systems with Applications. (2015). 42(3): 1278-1286.
70. X. Hou, Y. Liu, H. Liu, X. Chen, M. Liu, H. Che, F. Guo, C. Wang, D. Zhang, J. Wu, X. Chen, C. Shen, C. Li, F. Peng, Y. Bi, Z. Yang, G. Yang, J. Ai, X. Gao, and S. Zhao. PERK silence inhibits glioma cell growth under low glucose stress by blockage of p-AKT and subsequent HK2's mitochondria translocation. Scientific Reports. (2015) 5:9065.
69. P. Chen, J. Huang, and X. Gao. LigandRFs: random forest ensemble to identify ligand-binding residues from sequence information alone. BMC Bioinformatics. (2015) S15: S4.
68. J. Wang, Y. Sun and X. Gao. Sparse structure regularized ranking. Multimedia Tools and Applications. (2015) 74(2): 635-654.
Conference Papers:
67. X. Cui, H. Naveed, and X. Gao. Finding optimal interaction interface alignments between biological complexes. The 23rd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2015), Dublin, Ireland, July 2015. (Acceptance rate 20%).
66. I. Alabdulmohsin, X. Gao, and X. Zhang. Efficient active learning of halfspaces via query synthesis. The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, U.S., January 2015. (Acceptance rate 26.67%).
65. Z. Lu, X. Gao, L. Wang, J. Wen, and S. Huang. Noise-robust semi-supervised learning by large-scale sparse coding. The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), Austin, U.S., January 2015. (Acceptance rate 26.67%).
64. Z. Lu, X. Gao, L. Wang, S. Huang, and J. Wen. Social image parsing by cross-modal data refinement. The International Joint Conference on Artificial Intelligence (IJCAI-15), Buenos Aires, Argentina, July 2015. (Acceptance rate 28.8%).
63. J. Wang, and X. Gao. Partially labeled data tuple can optimize multivariate performance measures. ACM International Conference on Information and Kowledge Management (CIKM2015). Melbourne, Australia, October 2015. (Acceptance rate 25.6%).
62. X. Cui, H. Kuwahara, S. Li, and X. Gao. Compare local pocket and global protein structure models by small structure patterns. ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2015 (ACM-BCB2015). Atlanta, U.S., September 2015. (Acceptance rate 34%).
61. S. Sun, X. Wang, X. Gao, L. Ren, X. Sun, D. Bu, and K. Ning. Preprocess and condensation of Raman spectrum for single-cell phenotype analysis. The 26th International Conference on Genome Informatics (GIW2015). Tokyo, Japan, September 2015.
2014
Journal Papers:
60. X. Wang, H. Kuwahara, and X. Gao. Modeling DNA affinity landscape through two-round support vector regression with weighted degree kernels. BMC Systems Biology. (2014). 8(S5): S5.
59. G. Yang, C. Li, X. Chen, Y. Liu, D. Han, X. Gao, K. Kawamoto, and S. Zhao. Large capillary hemangioma of the temporal bone with a dural tail sign: A case report. Oncology Letters. (2014). 8(1): 183-186.
58. A. Abbas, X. Guo, B. Jing, and X. Gao. An automated framework for NMR resonance assignment through simultaneous slice picking and spin system forming. Journal of Biomolecular NMR. (2014). 59(2): 75-86.
57. T. Alam, M. Alazmi, X. Gao, and S. Arold. How to find a Leucine in a Haystack? Structure, ligand recognition and regulation of Leucine-Aspartic acid (LD) motifs. Biochemical Journal. (2014). 460(3): 317-329.
56. D. Zhang, G. Yang, X. Chen, C. Li, L. Wang, Y. Liu, D. Han, H. Liu, X. Hou, W. Zhang, C. Li, Z. Han, X. Gao, and S. Zhao. mir-300 promotes self-renewal and inhibits the differentiation of glioma stem-like cells. Journal of Molecular Nueroscience. (2014). 53(4): 637-644.
55. J. Wang, H. Bensmail, and X. Gao. Feature selection and multi-kernel learning for sparse representation on manifold. Neural Networks. (2014). 51: 9-16.
54. Y. Cheng, X. Gao, and F. Liang. Bayesian peak picking for NMR spectra. Genomics, Proteomics, and Bioinformatics. (2014). 12(1): 39-47.
53. J. Wang, and X. Gao. Beyond cross-domain learning: multiple-domain nonnegative matrix factorization. Engineering Applications of Artificial Intelligence. (2014). 28:181-189.
52. J. Wang, Y. Shi, and X. Gao. Semi-supervised transductive hot spot predictor working on multiple assumptions. Current Bioinformatics. (2014). 9(3): 258-267.
51. G. Yang, D. Han, X. Chen, D. Zhang, L. Wang, C. Shi, W. Zhang, C. Li, X. Chen, H. Liu, D. Zhang, J. Kang, F. Peng, Z. Liu, J. Qi, X. Gao, J. Ai, C. Shi, and S. Zhao. MiR-196a exerts its oncogenic effect in glioblastoma multiforme by inhibition of IkBa both in vitro and in vivo. Neuro-Oncology. (2014). 16(5): 652-661.
Conference Papers:
50. M. Al-Shedivat, J. Wang, M. Alzahrani, J. Huang, and X. Gao. Supervised transfer sparse coding. The Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI-14), Quebec City, Canada, July 2014. (Acceptance rate 28%)
49. I. Alabdulmohsin, X. Gao, and X. Zhang. Support vector machines with indefinite kernels. The 6th Asian Conference on Machine Learning (ACML2014). Nha Trang City, Vietnam, November 2014.
48. J. Wang, and X. Gao. Minimum information loss based multi-kernel for Flagellar protein recognition in Trypanosoma brucei. ICDM 2014 Workshop on Biological Data Mining and Its Applications in Healthcare (BioDM2014). Shenzhen, China, December 2014.
47. I. Almasri, X. Gao, and N. Fedoroff. Quick mining of isomorphic exact large patterns from large graphs. ICDM 2014 Workshop on Data Mining in Networks (DaMNet2014). Shenzhen, China, December 2014.
46. X. Wang, H. Kuwahara, and X. Gao. Modeling DNA affinity landscape through two-round support vector regression with weighted degree kernels. The 25th International Conference on Genome Informatics (GIW / ISCB-Asia 2014). Tokyo, Japan, December 2014.
45. I. Alabdulmohsin, X. Gao, and X. Zhang. Adding robustness to support vector machines against adversarial reverse engineering. ACM International Conference on Information and Knowledge Management (CIKM 2014). Shanghai, China, November 2014. (Acceptance rate 20.8%).
44. J. Wang, M. Alzahrani, and X. Gao. Large margin image set representation and classification. The 2014 International Joint Conference on Neural Networks (IJCNN2014), Beijing, China, July 2014.
43. J. Wang, and X. Gao. Semi-supervised sparse coding. The 2014 International Joint Conference on Neural Networks (IJCNN2014), Beijing, China, July 2014.
2013
Journal Papers:
42. H. Kuwahara, M. Fan, S. Wang, and X. Gao. A framework for scalable parameter estimation of gene circuit models using structural information. Bioinformatics. (2013). 29(13): i98-i107. [https://www.natureasia.com/en/nmiddleeast/article/10.1038/nmiddleeast.2013.118]
41. B. Xie, B. Jankovic, V. Bajic, L. Song, and X. Gao. Poly(A) motif prediction using spectral latent features from human DNA sequences. Bioinformatics. (2013). 29(13): i316-i325.
40. H. Kuwahara, and X. Gao. Stochastic effects as a force to increase the complexity of signaling networks. Scientific Reports. (2013). 3:2297. doi: 10.1038/srep02297.
39. J. Wang, H. Bensmail, and X. Gao. Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification. Pattern Recognition. (2013). 46(12): 3249-3255. [Highlighted by Advances in Engineering: http://advanceseng.com/electrical-engineering/joint-learning-weighting-visual-vocabulary-bag-feature-based-tissue-classification/]
38. J. Wang, H. Bensmail, and X. Gao. Multiple graph regularized nonnegative matrix factorization. Pattern Recognition (2013). 46(10): 2840-2847.
37. P. Chen, J. Li, L. Wong, H. Kuwahara, J. Huang, and X. Gao. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences. PROTEINS. (2013). 81(8): 1351-1362.
36. J. Wang, X. Wang, and X. Gao. Non-negative matrix factorization by maximizing correntropy for cancer clustering. BMC Bioinformatics (2013). 14:107.
35. X. Gao. Recent advances in computational methods for nuclear magnetic resonance data processing. Genomics, Proteomics, and Bioinformatics (2013). 11(1):29-33. doi: 10.1016/j.gpb.2012.12.003.
34. A. Abbas, X. Kong, Z. Liu, B. Jing, and X. Gao. Automatic peak selection by a Benjamini-Hochberg-based algorithm. PLOS ONE (2013). 8(1): e53112. doi:10.1371/journal.pone.0053112.
33. J. Wang, H. Bensmail, N. Yao, and X. Gao. Discriminative Sparse Coding on Multi-Manifolds. Knowledge-Based Systems. (2013). 54: 199-206.
Conference Papers:
32. H. Kuwahara, M. Fan, S. Wang, and X. Gao. A framework for scalable parameter estimation of gene circuit models using structural information. The 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2013), Berlin, Germany, July 2013. (Acceptance rate 16%)
31. B. Xie, B. Jankovic, V. Bajic, L. Song, and X. Gao. Poly(A) motif prediction using spectral latent features from human DNA sequences. The 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2013), Berlin, Germany, July 2013. (Acceptance rate 16%)
2012
Journal Papers:
30. M. Messih, M. Chitale, V. Bajic, D. Kihara and X. Gao. Protein domain recurrence and order can enhance prediction of protein functions. Bioinformatics (2012), 28(18): i444-i450.
29. Z. Liu, A. Abbas, B. Jing, and X. Gao. WaVPeak: picking NMR peaks through wavelet transform and volume-based filtering. Bioinformatics (2012), 28(7): 914-920. [PDF] [Source code]
28. M. Maadooliat, X. Gao, and J. Huang. Assessing protein conformational sampling methods based on bivariate lag-distributions of backbone angles. Briefings in Bioinformatics (2012). 14(6): 724-736.
27. M. Fan, K. Wong, T. Ryu, T. Ravasi, and X. Gao. SECOM: a novel hash seed and community detection-based approach for genome-scale protein domain identification. PLOS ONE (2012), 7(6): e39475. doi:10.1371/journal.pone.0039475. [Source code]
26. L. Dai, X. Gao, Y. Guo, J. Xiao and Z. Zhang. Bioinformatics clouds for big data manipulation. Biology Direct (2012). 7: 43. doi:10.1186/1745-6150-7-43.
25. X. Gao. Mathematical approaches to the NMR peak-picking problem. Journal of Applied and Computational Mathematics. (2012), 1:1.
24. J. Wang, Y. Li, Q. Wang, J. Zhang, X. You, J. Man, C. Wang, and X. Gao. ProClusEnsem: predicting membrane protein types by fusing different models of pseudo amino acid composition. Computers in Biology and Medicine (2012), 42(5): 564-574. [PDF]
23. J. Wang, X. Gao, Q. Wang, Q. Wang, and Y. Li. ProDis-ContSHC: learning protein dissimilarity measures and hierarchical context coherently for protein-protein comparison in protein database retrieval. BMC Bioinformatics (2012), 13(S7): S2. [PDF]
22. J. Wang, H. Bensmail, and X. Gao. Multiple graph regularized protein domain ranking. BMC Bioinformatics (2012). 13:307. doi:10.1186/1471-2105-13-307.
21. R. Jang, X. Gao, and M. Li. Combining automated peak tracking in SAR by NMR with structure-based backbone assignment from 15N-NOESY. BMC Bioinformatics (2012), 12(S3):S4. [PDF]
Conference Papers:
20. J. Wang, I. Almasri, and X. Gao. Adaptive graph regularized nonnegative matrix factorization via feature selection. The 21st International Conference on Pattern Recognition (ICPR2012). Tsukuba, Japan. November 2012.
19. M. Messih, M. Chitale, V. Bajic, D. Kihara and X. Gao. Protein domain recurrence and order can enhance prediction of protein functions. The 11th European Conference on Computational Biology (ECCB2012). Basel, Switzerland, September 2012. (Acceptance rate of 14%).
2011
Journal Papers:
18. Md. S. Bhuyan, and X. Gao. A protein-dependent side-chain rotamer library. BMC Bioinformatics (2011), 12(S14): S10. [PDF]
17. R. Jang, X. Gao, and M. Li. Towards fully automated structure-based NMR resonance assignment of 15N-labeled proteins from automatically picked peaks, Journal of Computational Biology, vol. 18(3), (2011), pp 347-363. Equally Contributed to the First Author. [PDF]
16. B. Alipanahi, X. Gao, E. Karakoc, F. Balbach, S. Li, G. Feng, L. Donaldson, and M. Li. Error tolerant NMR backbone resonance assignment for automated structure generation. Journal of Bioinformatics and Computational Biology, vol. 9, (2011), pp 15-41. Equally Contributed to the First Author. [PDF]
Conference Papers:
15. Md. S. Bhuyan, and X. Gao. A protein-dependent side-chain rotamer library. The 22nd International Conference on Genome Informatics (GIW2011). Busan, Korea, December 2011.
14. H. Kuwahara, and X. Gao. An efficient parallel stochastic simulation method for analysis of nonviral gene delivery systems. The 9th International Conference on Computational Methods in Systems Biology (CMSB2011). Paris, France, September 2011. [PDF]
13. R. Jang, X. Gao, and M. Li. Combined structure-based backbone and NOE assignment from N-HSQC chemical shift mapping and N-NOESY NMR spectra. ACM Conference on Bioinformatics, Computational Biology and Biomedicine 2011 (ACM-BCB2011). Chicago, U.S., August 2011. (Acceptance rate 19%).
Before 2010
Journal Papers:
12. B. Alipanahi, X. Gao, E. Karakoc, L. Donaldson, and M. Li. PICKY: a novel SVD-based NMR spectra peak picking method. Bioinformatics, vol. 25, no. 12, (2009), pp. i268-i275. Equally Contributed First Author. [PDF]
11. S. C. Li, D. Bu, X. Gao, J. Xu, and M. Li. Designing succinct structural alphabets. Bioinformatics, vol. 24, no. 13, (2008), pp. i182-i189. [PDF]
10. X. Gao, J. Xu, S. C. Li, and M. Li. Predicting local quality of a sequence-structure alignment. Journal of Bioinformatics and Computational Biology, vol. 7, (2009), pp. 789-810. [PDF]
9. X. Gao, D. Bu, J. Xu, and M. Li. Improving consensus contact prediction via server correlation reduction. BMC Structural Biology, 2009, 9:28. [PDF]
8. X. Gao, D. Bu, S. C. Li, J. Xu, and M. Li. FragQA: predicting local fragment quality of a sequence-structure alignment. Genome Informatics, vol. 19, no. 1, (2007), pp. 27-39. [PDF]
Conference Papers:
7. R. Jang, X. Gao, and M. Li. Towards automated structure-based NMR resonance assignment, The Fourteenth Annual International Conference on Research in Computational Molecular Biology (RECOMB2010). Lisbon, Portugal, April 2010. (Acceptance rate 20%). Equally Contributed First Author.
6. B. Alipanahi, X. Gao, E. Karakoc, L. Donaldson, A. Gutmanas, C. Arrowsmith, and M. Li. PICKY: a novel SVD-based NMR spectra peak picking method. The Seventeenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB2009). Stockholm, Sweden, June 2009. (Acceptance rate 18%). Equally Contributed First Author.
5. S. C. Li, D. Bu, X. Gao, J. Xu, and M. Li. Designing succinct structural alphabets. The Sixteenth Annual International Conference on Intelligent Systems for Molecular Biology (ISMB 2008), Toronto, Canada, July 2008. (Acceptance rate 15%).
4. J. Zhang, X. Gao, J. Xu, and M. Li. Rapid and accurate protein side-chain prediction with local backbone information. The Twelfth Annual International Conference on Research in Computational Molecular Biology (RECOMB2008), Singapore, April 2008. (Acceptance rate 15%). Equally Contributed to the First Author.
3. X. Gao, D. Bu, S. C. Li, J. Xu, and M. Li. FragQA: predicting local fragment quality of a sequence-structure alignment. The Eighteenth International Conference on Genome Informatics (GIW 2007), Singapore, December 2007. (Acceptance rate 29%). Best Paper Award.
2. X. Gao, D. Bu, S. C. Li, J. Xu, and M. Li. Consensus contact prediction by linear programming, in Proceedings of the Sixth Annual International Conference on Computational Systems Bioinformatics (CSB 2007), pp. 323-334, San Diego, U.S., August 2007. (Acceptance rate 22%).
1. X. Gao, S. C. Li, and Y. Lu. New algorithms for the spaced seeds. International Frontiers of Algorithmics Workshop 2007 (FAW 2007), LanZhou, P.R. China, August 2007. (Acceptance rate 23%). Lecture Notes in Computer Science, vol. 4613, (2007), pp. 50-61.
Book Chapters:
3. H. Jiang, L. Zhu, A. Heliou, X. Gao, J. Bernauer, and X. Huang. Elucidating mechanisms of molecular recognition between human Argonaute and miRNA using computational approaches. In Methods in Molecular Biology, Eds: Marco F. Schmidt, Vol. 1517, Springer, 2016.
2. R. Chowdhary, B. Jankovic, R. Stankowski, J. Archer, X. Zhang, X. Gao, and V. Bajic. Automated mining of disease-specific protein interaction networks based on biomedical literature. Invited book chapter, in Biological Data Mining and Its Applications in Healthcare, Eds: Xiao-Li Li, See-Kiong Ng, and Jason Wang, 2013.
1. D. Bu, S. C. Li, X. Gao, L. Yu, J. Xu, and M. Li. Consensus approaches to protein structure prediction. Invited book chapter, in Machine Learning in Bioinformatics, Chapter 8, Eds: Yanqing Zhang and Jagath C. Rajapakse, John Wiley & Sons, 2007.
Non-refereed Conference Publications:
5. H. Kuwahara, and X. Gao. A hybrid model decomposition framework for parameter estimation of gene circuit models. The 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'15). Milano, Italy, August 2015.
4. X. Gao. Automated protein structure determination from NMR multidimensional spectra. The 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'15). Milano, Italy, August 2015.
3. H. Kuwahara, M. Fan, S. Wang and X. Gao. A scalable approach to parameter estimation for statistical thermodynamic-based models of gene regulation using structural information. The First Annual Winter q-bio Meeting. Hawaii, USA, February 2013.
2. X. Gao, M. Li, and J. Xu. RAPTORESS: an atom-level refinement approach for protein structure prediction. The 7th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP7), pp. 96-97. Long abstract, Pacific Grove, USA, November 2007.
1. L. Yu, D. Bu, S. C. Li, X. Gao, J. Xu, and M. Li. RAPTOR-ACE: an integer linear programming based consensus fold recognition method, The 7th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP7), pp. 94-95. Long abstract, Pacific Grove, USA, November 2007.
Thesis:
1. X. Gao. Towards automating protein structure determination from NMR data. Ph.D. Thesis, University of Waterloo, Waterloo, Canada. September, 2009.