Sherry Bhalla

This study evaluates existing TNBC prognostic signatures and develops a robust 13-gene model with cross-cohort validation and therapeutic prioritization.

This study presents whole-genome and transcriptome analyses of breast tumors from India, identifying novel mutations, copy number alterations, and subtypes with clinical implications.

The paper identifies tumor-specific and subtype-specific alternative promoters in TNBC and develops a prognostic model based on these promoters, showing improved risk prediction.

This paper shows sertraline enhances macrophage bactericidal activity against Mtb by rewiring cholesterol metabolism and activating inflammasome pathways.

The paper identifies a three-gene expression signature that predicts response to selinexor in multiple myeloma and glioblastoma.

This study identifies key transcripts and machine learning models to classify early and late stage Papillary Thyroid Carcinoma samples using TCGA data, achieving up to 75.43% accuracy.

The paper develops prediction models using HLA-alleles and clinical characteristics to predict overall survival in skin cutaneous melanoma patients and identifies favorable and unfavorable superalleles.

GPSRdocker provides a docker-based container integrating bioinformatics tools for genomics, proteomics, and systems biology, enabling local or cloud use of computational resources.

This study predicts melanoma progression using genomic features from TCGA SKCM data, identifying key genes and miRNAs that distinguish primary from metastatic tumors.

The paper develops models to classify early and late stage Liver Hepatocellular Carcinoma using genomic and epigenomic data, achieving high accuracy and AUROC scores.

The paper develops proteomics-based prediction models to distinguish urinary tract oncological samples from healthy controls using urine data and creates a web tool for data mining.