Theses

Theses produced by BORG members at KAUST.

PhD theses

  • Imane Boudellioua (, Computer Science) — Semantic Prioritization of Novel Causative Variants
  • Mona Alshahrani (, Computer Science) — Multi-modal learning on biological knowledge graphs
  • Maxat Kulmanov (, Computer Science) — Prediction of protein functions and phenotypes
  • Sarah Alghamdi (, Computer Science) — Ontology design patterns for integrating phenotype ontologies
  • Azza Althagafi (, Computer Science) — Prioritizing Causative Variants by Integrating Molecular and Functional Annotations from Multiple Biomedical Ontologies
  • Sumyyah Toonsi (, Computer Science) — Data Driven Mining of Causal Disease Relations to Enhance Disease Centric Predictions
  • Rund Tawfiq (, Bioengineering) — Computational Methods for Functional Characterization of Microbial Communities
  • Yang Liu (, Bioengineering) — Reference Bias and Variant Interpretation in Human Disease Genomics
  • Fernando Zhapa-Camacho (, Computer Science) — Neuro-symbolic methods for embedding ontologies, and applications in life sciences

MSc theses

  • Sakhaa Alsaedi (, Computer Science) — Evaluating the Application of Allele Frequency in the Saudi Population Variant Detection
  • Abeer Almutairi (, Computer Science) — Unsupervised Method for Disease Named Entity Recognition
  • Sumyyah Toonsi (, Computer Science) — Automatic annotation of protein functions through text mining
  • Sarah Alghamdi (, Computer Science) — Ontology design patterns for aging mouse ontologies
  • Sara Althubaiti (, Computer Science) — Ontology-based identification of cancer driver genes
  • Azza Althagafi (, Computer Science) — Simulation and visualization of human genomes
  • Daulet Toibazar (, Bioengineering) — Context-aware protein function prediction in bacterial genomes
  • Maria G Gomez Castillo (, Bioengineering) — Heatstroke multi-omics analysis
  • Amal Alhelal (, Bioengineering) — Protein functional domain identification methodology
  • Md Nurul Muttakin (, Computer Science) — 3D conformation-based protein function prediction
  • Hatoon Al Ali (, Bioengineering) — Predicting effects of non-coding genomic variants
  • Shahad Qatan (, Computer Science) — Predicting Protein Functions From Interactions Using Neural Networks and Ontologies
  • Kexin Niu (, Bioscience) — De novo genome-scale prediction of protein-protein interaction networks using ontology-based background knowledge
  • Yang Liu (, Bioengineering) — Rare variant collapsing analysis on UK Biobank
  • Xi Peng (, Computer Science) — Description Logic EL++ Embeddings with Intersectional Closure
  • Fernando Zhapa-Camacho (, Computer Science) — Embedding Ontologies using Category Theory Semantics
  • Zhenwei Tang (, Computer Science) — Towards Quality and General Knowledge Representation Learning
  • Safana Bakheet (, Bioengineering) — An Inductive, Supervised Gene-Disease Associations Method
  • Melissa Rios Zertuche (, Bioscience) — Establishment and Evaluation of a Computational Workflow for the Design and Optimization of Nanobodies
  • Sawsan Al Boeisa (, Bioengineering) — Differential Effects of p38 MAPK Inhibition on Chemoresistance in Patients with Colorectal Cancer
  • Mahdi Bu Ali (, Computer Science) — Automated Theorem Proving with Large Language Models in Lean: An Exploration of Specialized In-Context Learning and General-Purpose Hierarchical Architectures
  • Mohammed Ashhad (, Bioengineering) — Machine learning methods for survival analysis: from outcome-conditioned data synthesis to decoupled ranking and calibration
  • Asaad Mohammedsaleh (, Computer Science) — Genome-Scale Protein Function Adjustment using Constraint Optimization