Shubhasis Haldar

This study investigates how IgM antibodies affect the mechanical stability of protein L using single-molecule techniques, revealing concentration-dependent stability increases and altered unfolding pathways.

This paper develops OncoMark, a neural multi-task learning framework to predict cancer hallmark activities from transcriptomics data, achieving high accuracy across internal and external datasets.

This study investigates p47's role in retrotranslocation by enhancing talin's mechanical stability and generating pulling forces to facilitate ER-to-cytosol protein export.

This study investigates the roles of periplasmic chaperones in Gram-negative bacteria, showing some act as foldases and others as holdases during protein translocation.

ACSCeND quantifies cancer stem cell composition from bulk RNA-seq data, showing improved accuracy over existing methods and linking CSC abundance to poorer survival outcomes.

This paper introduces OSCORP, a machine learning method that identifies cancer stem cells with 99% accuracy using bulk RNAseq data, revealing CSC states and their clinical and transcriptomic signatures across 22 cancer types.