Rund Tawfiq

In Other Words: Learning When to Trust Generated Protein Function Descriptions

The paper introduces a method to assess the reliability of generated protein function descriptions using a judge model and shows it improves performance across multiple methods.

Phased genome assemblies and pangenome graphs of human populations of Japan and Saudi Arabia

The paper constructs a pangenome graph reference for Japanese and Saudi Arabian populations, showing improved variant detection compared to linear references and comparable performance to existing pangenome graphs.

Beyond protein functions: evaluating completeness, coherence, and consistency of genome-scale function annotations

The paper evaluates genome-scale protein function annotations for completeness, coherence, and consistency, finding that computational methods fail to produce biologically plausible annotations despite high individual protein accuracy.

DeepGOMeta: Predicting functions for microbes

DeepGOMeta predicts protein functions for microbes using a deep learning model trained on microbial data, improving function prediction for novel proteins.

A personal, reference quality, fully annotated genome from a Saudi individual

The paper presents a fully annotated reference genome from a Saudi individual using de novo assembly and AI-based annotation, making all data publicly available.