Shafayat Ahmed

Predicting Antibody Self-Association with Sequence Structure Fusion Models: The Central Role of CSI-BLI in Early Developability Screening

The paper develops a sequence-structure fusion model to predict antibody self-association using CSI-BLI data, achieving high performance in distinguishing high and low self-interacting clones.

ACCURATE PREDICTION OF ASPARAGINE DEAMIDATION IN BIOLOGICS USING ADVANCED MACHINE LEARNING MODELS

This study develops machine learning models to predict asparagine deamidation in proteins, showing improved accuracy over existing methods and reducing development costs.

Resistance genes are distinct in protein-protein interaction networks according to drug class and gene mobility

The paper introduces a pipeline using PPINs and machine learning to identify ARGs, showing improved discrimination of ARGs from nonARGs and their association with mobile genetic elements.

ProtAlign-ARG: Antibiotic Resistance Gene Characterization Integrating Protein Language Models and Alignment-Based Scoring

ProtAlign-ARG improves antibiotic resistance gene detection by combining protein language models with alignment-based scoring, achieving higher recall than existing methods.

ARGContextProfiler: Extracting and Scoring the Genomic Contexts of Antibiotic Resistance Genes using Assembly Graphs

ARGContextProfiler improves accuracy in identifying antibiotic resistance gene contexts in metagenomic data using assembly graphs and read mapping.

Fast-Part: Fast and Accurate Data Partitioning for Biological Sequence Analysis

Fast-Part partitions biological sequence data efficiently while maintaining homology separation and stratification ratios.

CIWARS: a web server for waterborne antibiotic resistance surveillance using longitudinal metagenomic data

CIWARS is a web server for analyzing longitudinal metagenomic data to detect antibiotic resistance genes and assess AR risks in environmental samples.

NORTH: a highly accurate and scalable Naive Bayes based ORTHologous gene cluster prediction algorithm

NORTH is a Naive Bayes-based algorithm for orthologous gene clustering that achieves high accuracy and scalability across diverse organisms and large datasets.