News Archives

Dissertation defense, April 7: Ala Jararweh

March 31, 2025

Student Name: Ala Jararweh
Program: PhD Computer Science
Date: Monday 4/7/25
Time: 10:00 am
Place: Farris 3100
Committee Chair: Dr. Mueen Abdallah

"Leveraging Attention Mechanism to Unlock Gene and Protein Attributes"

by Ala Jararweh

B.S., Computer Science, Jordan University of Science & Technology, 2018
M.Sc., Computer Science, University of New Mexico, 2025
Ph.D., Computer Science, University of New Mexico, 2025

Abstract

Advancing personalized medicine depends on e↵ectively integrating and interpreting the vast, heterogeneous landscape of biological data, from genomic sequences and transcriptomics to the insights embedded in scientific literature. Current machine learning models often focus on single data modalities, limiting their capacity to capture the multifaceted nature of biological systems. We address this gap by developing three attention-based machine-learning models that integrate diverse biological data. Firstly, DeepVul is a multi-task model that leverages cancer transcriptome data to predict genes critical for cancer survival and their corresponding drugs. Subsequently, LitGene refines gene representations by integrating textual information from the scientific literature. Finally, Protein2Text is a large language model that translates protein sequences into natural language descriptions, making complex biochemical data accessible and interpretable. These models echo a comprehensive approach to integrating diverse data modalities to provide a diverse view of biological systems, paving the way for truly personalized medicine for everyone.