Anika Bushra Lamisa

A meta-analysis of bulk RNA-seq datasets identifies potential biomarkers and repurposable therapeutics against Alzheimers disease

A meta-analysis of bulk RNA-seq datasets identifies 12 differentially expressed genes in Alzheimer's disease, with TTR showing potential as a biomarker and suggesting Levothyroxine as a repurposable therapeutic.

AITeQ: A machine learning framework for Alzheimer's prediction using a distinctive 5-gene signature

This paper develops AITeQ, a machine learning framework for Alzheimer's disease prediction using a 5-gene signature identified from RNA-Seq data.

A Non-invasive Detection of Parkinson's Disease using PitArray: An Integrative Meta-Analysis and Machine Learning Approach

This study identifies potential biomarkers for Parkinson's disease using blood-based gene expression data and develops a machine learning classifier called PitArray for non-invasive detection.

An Integrated Comparative Genomics, Subtractive Proteomics and Immunoinformatics Framework for the Rational Design of a Pan-Salmonella Multi-Epitope Vaccine

This study designs a pan-Salmonella multi-epitope vaccine using subtractive proteomics and immunoinformatics, identifying CsgA as a conserved vaccine candidate with strong immunogenic properties.