Research Conference

The 21st International Conference on Bioinformatics (InCoB2022)

Computational Bioscience Research Center
Monday, November 21, 2022, 09:00
- 17:00
Virtual
Contact Person
Takashi Gojobori
The Computational Bioscience Research Center (CBRC) at King Abdullah University of Science and Technology (KAUST) is pleased to host the International Conference on Bioinformatics 2022 (InCoB2022).  This year’s conference theme will be “Accelerating innovation to meet biological challenges: The role of bioinformatics”.
Seminar

SEMINAR: Plastics and microbiomes: from lignocellulolytic bacterial consortia to mangrove soils - Prof. Diego Avella

Associate Professor Diego Javier Jiménez Avella
Wednesday, October 05, 2022, 11:00
- 12:00
Building 3, Level 5, Room 5209
Contact Person
Alexandre Soares Rosado

Abstract

In the Anthropocene, plastic pollution is a worldwide concern that must be tackled from d

PhD Dissertation Defense

Drug Repositioning through the Development of Diverse Computational Methods using Machine Learning, Deep Learning, and Graph Mining

Thursday, June 30, 2022, 08:30
- 10:30
KAUST
Contact Person
Xin Gao
In this dissertation, we combined artificial intelligence and machine/deep learning with chemical and biological properties to develop several computational methods to solve biomedical domain problems, specifically drug repositioning, and demonstrated their efficiencies and capabilities. We developed three network-based DTI prediction methods using machine learning, graph embedding, and graph mining. These methods significantly improved prediction performance, and the best-performing method even reduces the error rate by more than 33% across all datasets compared to the best state-of-the-art method. As it is more insightful to predict continuous values that indicate how tightly the drug binds to a specific target, we conducted a comparison study of current regression-based methods that predict drug-target binding affinities (DTBA). Our methods demonstrated their efficiency and capability by achieving high prediction performance and identifying therapeutic targets for several cancer types. We further conducted a lung cancer case study of findings that support the novel predicted targets.
Poster Competition

Student Poster Competition: KAUST Research Conference on Advances in Metagenomics and its Applications

Prof. Takashi Gojobori, Computational Bioscience Research Center, KAUST
Tuesday, May 24, 2022, 12:00
- 14:00
Building 19, Hall 3
Contact Person
Takashi Gojobori
The Computational Bioscience Research Center (CBRC) will be holding a student poster competition as part of its yearly conference. Core Labs booths will also be featured in this session.
Research Conference

KAUST Research Conference: Advances in Metagenomics and its Applications

Prof. Takashi Gojobori, Computational Bioscience Research Center, KAUST
Monday, May 23, 2022, 08:00
- 16:30
Building 19, Hall 1
Contact Person
Takashi Gojobori
The Computational Bioscience Research Center (CBRC) is pleased to invite the KAUST community to the KAUST Research Conference on Advances in Metagenomics and its Applications.
Seminar

CBRC Dual Seminar - Designing Organ Allocation - The Genome of the Ocean

Michal Mankowski , Assistant Professor, Erasmus University Rotterdam; Elisa Laiolo, PhD Student, Red Sea Research Center
Tuesday, April 26, 2022, 13:00
- 14:00
KAUST
Contact Person
Mikhail Moshkov
Elisa Laiolo: In her talk, Elisa will provide insights in to the KAUST Metagenomic Analyses Platform (KMAP), which is the first catalogue of the global ocean genome and its partitioning among taxonomical and functional groups, providing insights in its high diversity and functional variety. Michal Mankowski: In his talk, Michal will explain the techniques of using simulation with optimization, in order to design boundaries-free CAS that aims to maintain the prioritization of organ transplant for pediatric, different blood types, and status 1 candidates while minimizing the overall deaths.
Seminar

CBRC Dual Seminar - Analysis of COVID-19 Severity - DeepSVP computational method

Sakhaa Al-Saedi, PhD Student; Azza Althagafi, PhD Student
Tuesday, April 12, 2022, 13:00
- 14:00
KAUST
Contact Person
Sakhaa Alsaedi
Sakhaa Al-Saedi: We conduct a systematic genetic analysis of risk variants related to increasing the severity of COVID-19. It leads to a better understanding of its genetic basis and identifies the host genes to be targeted to tackle the COVID-19 pandemic and reduce its death toll. Azza Althagafi: We developed DeepSVP, a computational method to prioritize structural variants involved in genetic diseases by combining genomic and gene functions information. DeepSVP significantly improves the success rate of finding causative variants in several benchmarks and can identify novel pathogenic structural variants in consanguineous families.
Seminar

Population genomics of indigenous inhabitants in Arabian Peninsula

Monday, April 11, 2022, 11:00
- 12:00
KAUST
Contact Person
Takashi Gojobori
Dr. Katsuhiko Mineta will give a talk on "Population genomics of indigenous inhabitants in Arabian Peninsula". This talk will highlight the research conducted in areas of population genomic profiling of 957 unrelated individuals who self-identify with 28 large tribes in Saudi Arabia. The result of this research disclose a granular map of population structure in Arabia and what implications this will have for future genetic studies into diseases.
PhD Dissertation Defense

To Encourage or to Restrict: the Label Dependency in Multi-Label Learning

Wednesday, March 30, 2022, 17:30
- 19:30
KAUST
Contact Person
Zhuo Yang
Multi-label learning addresses the problem that one instance can be associated with multiple labels simultaneously. More or less, these labels are usually dependent on each other in different ways. Understanding and exploiting the Label Dependency (LD) is well-accepted as the key to build high-performance multi-label classifiers, i.e., classifiers having abilities including but not limited to generalizing well on clean data and being robust under evasion attack.
PhD Dissertation Defense

Omics-based Metastasis Prediction using Machine Learning and Deep Learning

Wednesday, March 30, 2022, 14:00
- 15:00
KAUST
Contact Person
Xin Gao
Knowing metastasis is the primary cause of cancer-related deaths incentivized research to unravel the complex cellular processes that drive the metastasis. Advancement in technology and specifically the advent of high-throughput sequencing provides knowledge of such processes. This knowledge led to the development of therapeutic and clinical applications. In this regard, predicting metastasis onset has also been explored using artificial intelligence (AI) approaches that are machine learning (ML), and more recently, deep learning (DL).
Seminar

CBRC Dual Seminar

Juexiao Zhou, MS Student and Manola Moretti, Research Scientist
Tuesday, March 29, 2022, 14:00
- 15:00
Building 9, Level 2, Room 2322
Contact Person
Xin Gao
Talk 1: PPML-Omics: a Privacy-Preserving federated Machine Learning system protects patients’ privacy from omic data. Talk 2: Peptide biopolymers in medical and environmental applications: an AFM and Raman spectroscopy perspective
Master Thesis Defense

MS Thesis Defense | SARS-CoV-2 Intra-host Evolution In Immunocompromised Patients for the Emergence of Variants of Concerns by Azari Ibrahim Bantan

Tuesday, March 29, 2022, 10:30
- 12:30
Building 3, Level 5, Conference Room 5209
Contact Person
Azari Ibrahim Bantan

Abstract:

Unexpected high mutations detected in new emerging variants of concern (VOCs) of 

Graduate Seminar

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining - 2022-03-03

Thursday, March 03, 2022, 12:00
- 13:00
Building 9, Level 2, Room 2325
Dynamic programming is an efficient technique to solve optimization problems. It is based on decomposing the initial problem into simpler ones and solving these sub-problems beginning from the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects. We developed extensions of dynamic programming which allow us (i) to describe the set of objects under consideration, (ii) to perform a multi-stage optimization of objects relative to different criteria, (iii) to count the number of optimal objects, (iv) to find the set of Pareto optimal points for the bi-criteria optimization problem, and (v) to study the relationships between two criteria. The considered applications include optimization of decision trees and decision rule systems as algorithms for problem-solving, as ways for knowledge representation, and as classifiers, optimization of element partition trees for rectangular meshes which are used in finite element methods for solving PDEs, and multi-stage optimization for such classic combinatorial optimization problems as matrix chain multiplication, binary search trees, global sequence alignment, and shortest paths.
Seminar

Renewal of the Zebrafish Intestine from a Simplified Crypt-like Structure, What a Zebrafish might tell us about tissue engineering

Professor Paul Matsudaira, National University of Singapore
Tuesday, February 15, 2022, 16:30
- 17:30
KAUST

Abstract

In the mammalian intestine, stem cells (ISCs) located in basal crypts, replicate and tran

Seminar

De novo construction of signal transduction networks using single-cell transcriptomic data for better understanding of cell-cell communication

Prof. Yuxuan Hu, Xidian University, China
Thursday, December 23, 2021, 12:30
- 14:00
KAUST
Contact Person
Xin Gao
Signal transduction is the primary mechanism for cell-cell communication and scRNA-seq technology holds great promise for studying this communication at high levels of resolution. Signaling pathways are highly dynamic and cross-talk among them is prevalent. Due to these two features, simply examining expression levels of ligand and receptor genes cannot reliably capture the overall activities of signaling pathways and the interactions among them.
Seminar

Organic Electrochemical Transistors for Analyte Detection

Sahika Inal, Associate Professor, Bioscience, Organic Bioelectronics Laboratory, Computational Bioscience Research Center
Tuesday, September 28, 2021, 15:00
- 16:00
Building 9, Level 2, Hall 2
Contact Person
Sahika Inal
In this talk, I will show how these materials are used in organic electrochemical transistors (OECTs) to detect biological species in physiological media. I will introduce two types of OECT based sensors; one that detects Alzheimer’s disease biomarkers with performance exceeding the state-of-the-art,1,2 and the other that detects coronavirus spike proteins at the physical limit.3 Having challenged these sensors with patient samples, I will discuss areas where proof-of-concept organic biosensor platforms may fail. By tackling each of these problems, we improve device performance to a level that marks a considerable step toward biochemical sensing of infectious and noninfectious disease biomarkers. I will highlight how computational methods can aid in sensor development and organic semiconductor research.
Seminar

Artificial Intelligence methods for precision health: Applications to rare disease and cancer research

Sunday, June 27, 2021, 10:00
- 11:00
Building 9, Level 2, Room 2325
Contact Person
Robert Hoehndorf

Abstract

The life sciences have invested significant resources in the development and application