We explore efficient ways to mine new knowledge from a variety of sources to improve human health.
Vladimir Bajic Professor AMCS


  • Building 3, Room 4219


Education Profile

  • D.Eng.Sc. Electrical Engineering, University of Zagreb, Yugoslavia, 1989
  • M.Sc. Electical Engineering, University of Belgrade, Yugoslavia, 1979
  • Dipl.Eng. Electical Engineering, University of Belgrade, Yugoslavia, 1976


Molecular Biomarker Set for Early Detection of Ovarian Cancer

  • U.S. Patent 9057107
  • Europe (EPO) Patent 2683835
  • Australia Patent 2012226530
  • U.S. Patent 9914974
  • U.K. Patent 2683835
  • France Patent 2683835
  • Germany Patent 2683835
  • Switzerland Patent 2683835

Treatment of Sickle Cell Disease

  • U.S. Patent 9655905

Composite Biomarkers For Non-Invasive Screening, Diagnosis And Prognosis Of Colorectal Cancer

  • U.S. Patent 9994900
  • Europe (EPO) Patent 2768980
  • Germany Patent 08750289L
  • U.K. Patent 2768980
  • France Patent 2768980

Methylation Biomarkers for Prostate Cancer

  • U.S. Patent 9976187
  • Europe (EPO) Patent 2861766
  • U.S. Patent 9982307

Methylation Biomarkers for Ovarian Cancer

  • U.S. Patent 10041124

Combination Comprising Parthenolide for Use in the Treatment of Alzheimer's Disease and Other Neurodegenerative Disorders

  • Australia Patent 2013264943

Professor Vladimir Bajic has authored over 400 research publications, 100+ bioinformatics & AI/ML/DL software tools/products. He has 19 granted patents in the medical field. His primary interest is in facilitating biomedical discoveries using computational systems combined with data modeling and artificial intelligence (AI). Emphasis is on the inference of new information not explicitly present in biomedical data, the development of systems with such capabilities and their industrial applications.

Education and early career

Professor Bajic received his D.Eng.Sc. degree in electrical engineering from the University of Zagreb (Croatia) in 1989.  He joined KAUST in May 2009 as the Founding Director of the Computational Bioscience Research Center (CBRC) and Professor of Applied Mathematics and Computer Science. Previously, he was a Professor of Bioinformatics, as well as Acting and then Deputy Director of the South African National Bioinformatics Institute (SANBI) at the University of the Western Cape, South Africa.

Areas of expertise and current scientific interests

His current research interests focus on: AI & health informatics; biomedical knowledge-, text-, & data-mining; AI/ML/DL modeling; drug repositioning; diagnostic, screening, & prognostic biomarkers; information integration.  

Career recognitions

Professor Bajic is an elected member of the Academy of Nonlinear Sciences in Russia for his work on the stability theory of singular differential systems. For his bioinformatics work, he was awarded the first DST/NRF South African (Tier 1) Research Chair in Bioinformatics and Human Health.

Editorial activities

He has served on the Editorial Board of numerous journals throughout his career. Among those he still works with are:

  • Briefings in Bioinformatics
  • Scientific Reports
  • PLoS ONE
  • Peer J
  • Journal of Bioinformatics & Computational Biology
  • Genomics, Proteomics & Bioinformatics
  • Journal of Translational Medicine
  • BioMed Research International
  • Frontiers in Statistical Genetics and Methodology
  • Genomics Discoveries

Why Computational Bioscience?

As research in life sciences has progressed, the data produced has grown dramatically. Moreover, the complexity of the information contained in this data is enormous. Analyzing this large volume of data and complex information in it without sophisticated computational methods is impossible. As a computational scientist, I stand between the data, the meaning of information contained in the data, and their meaningful interpretation. I develop methods and tools to achieve these goals through Artificial Intelligence combined with Bioinformatics and Computational Biology.


KAUST offers a top-notch research framework that I would not be able to find elsewhere. It has provided me an opportunity to do the research I love: Knowledge Mining.

Selected Publications

Raies, A.B., & Bajic, V. B. (2016). In silico toxicology: computational methods for the prediction of chemical toxicity. Wiley Interdiscip Rev Comput Mol Sci. 2016 Mar;6(2):147-172. DOI: 10.1002/wcms.1240
Medvedeva, Y.A., Khamis, A.M., Kulakovskiy, I.V., Ba-Alawi, W., Bhuyan, M.S., Kawaji, H., Lassmann, T., Harbers, M., Forrest, A.R., Bajic, V.B.; FANTOM consortium (2014) Effects of cytosine methylation on transcription factor binding sites. BMC Genomics. 2014; 15: 119. doi: 10.1186/1471-2164-15-119.
Ma, L., Bajic, V. B., & Zhang, Z. (2013). On the classification of long non-coding RNAs. RNA Biology, 10(6), 924–933. doi:10.4161/rna.24604
Soufan, O., Ba-Alawi, W., Afeef, M., Essack, M., Kalnis, P., & Bajic, V. B. (2016). DRABAL: novel method to mine large high-throughput screening assays using Bayesian active learning. Journal of Cheminformatics, 8(1). doi:10.1186/s13321-016-0177-8
Ba-alawi Wail, Soufan, O., Essack, M., Kalnis, P., & Bajic, V. B. (2016). DASPfind: new efficient method to predict drug–target interactions. Journal of Cheminformatics, 8(1). doi:10.1186/s13321-016-0128-4
Soufan, O., Ba-alawi Wail, Afeef, M., Essack, M., Rodionov, V., Kalnis, P., & Bajic, V. B. (2015). Mining Chemical Activity Status from High-Throughput Screening Assays. PLOS ONE, 10(12), e0144426. doi:10.1371/journal.pone.0144426
Ravasi, T., Suzuki, H., Cannistraci, C. V., Katayama, S., Bajic, V. B., Tan, K., … Hayashizaki, Y. (2010). An Atlas of Combinatorial Transcriptional Regulation in Mouse and Man. Cell, 140(5), 744–752. doi:10.1016/j.cell.2010.01.044
Soufan, O., Kleftogiannis, D., Kalnis, P., & Bajic, V. B. (2015). DWFS: A Wrapper Feature Selection Tool Based on a Parallel Genetic Algorithm. PLOS ONE, 10(2), e0117988. doi:10.1371/journal.pone.0117988
Salhi, A., Negrão, S., Essack, M., Morton, M. J. L., Bougouffa, S., Razali, R., … Bajic, V. B. (2017). DES-TOMATO: A Knowledge Exploration System Focused On Tomato Species. Scientific Reports, 7(1). doi:10.1038/s41598-017-05448-0
Ashoor, H., Louis-Brennetot, C., Janoueix-Lerosey, I., Bajic, V. B., & Boeva, V. (2017). HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics. Nucleic Acids Research, gkw1319. doi:10.1093/nar/gkw1319
Simões, M. F., Antunes, A., Ottoni, C. A., Amini, M. S., Alam, I., Alzubaidy, H., … Bajic, V. B. (2015). Soil and Rhizosphere Associated Fungi in Gray Mangroves (Avicennia marina) from the Red Sea — A Metagenomic Approach. Genomics, Proteomics & Bioinformatics, 13(5), 310–320. doi:10.1016/j.gpb.2015.07.002
Ashoor, H., Kleftogiannis, D., Radovanovic, A., & Bajic, V. B. (2015). DENdb: database of integrated human enhancers. Database, 2015, bav085. doi:10.1093/database/bav085
Khamis, A. M., Hamilton, A. R., Medvedeva, Y. A., Alam, T., Alam, I., Essack, M., … Bajic, V. B. (2015). Insights into the Transcriptional Architecture of Behavioral Plasticity in the Honey Bee Apis mellifera . Scientific Reports, 5(1). doi:10.1038/srep11136
Alam, T., Medvedeva, Y. A., Jia, H., Brown, J. B., Lipovich, L., & Bajic, V. B. (2014). Promoter Analysis Reveals Globally Differential Regulation of Human Long Non-Coding RNA and Protein-Coding Genes. PLoS ONE, 9(10), e109443. doi:10.1371/journal.pone.0109443
Ashoor, H., Hérault, A., Kamoun, A., Radvanyi, F., Bajic, V. B., Barillot, E., & Boeva, V. (2013). HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data. Bioinformatics, 29(23), 2979–2986. doi:10.1093/bioinformatics/btt524