I analyze genomic and transcriptomic data to study disease mechanisms, identify clinically relevant molecular signatures, and develop reproducible bioinformatics workflows.
Cancer Genomics • WES • RNA-seq • Single-Cell Analysis • Multi-Omics • Reproducible Pipelines
WES Samples
Single Cells
Multi-Omics Datasets
Districts Modeled
I'm Abhimanyu Mandal, a Computational Biologist and Bioinformatician with research experience in cancer genomics, transcriptomics, whole-exome sequencing, single-cell RNA-seq, and multi-omics analysis.
My work focuses on using computational approaches to investigate disease mechanisms, characterize genomic alterations, and identify molecular signatures with potential clinical and therapeutic relevance. I have worked across academic research and biotech, analyzing large-scale biological datasets and building reproducible computational workflows.
My experience includes germline variant analysis of 300+ WES samples, single-cell analysis of 28,000+ cells, multi-omics quality assessment across 1,000+ datasets, and computational drug-repurposing analysis.
My technical work spans R, Python, Bash, Linux, GATK, Seurat, Nextflow DSL2, Docker, Git, and HPC/SLURM, with an emphasis on reproducibility and robust biological data analysis.
Technologies and tools I use for computational biology, data science and software development.
My journey in computational biology, genomics and healthcare analytics.
Computational Epidemiology · Bayesian Modeling · R · HPC
Cancer Single-Cell Genomics · scRNA-seq · Seurat · Drug Repurposing
Multi-Omics Data Infrastructure · R Shiny · Quality Control · Drug Visualization
Selected projects spanning cancer genomics, single-cell analysis, bioinformatics workflows, machine learning, and healthcare analytics.
Reconstructed and extended a breast cancer scRNA-seq workflow using Seurat, pseudobulk analysis, disease signatures, and LINCS connectivity.
Selected outcome Screened 6,720 compounds across 9,108 perturbational signatures, identifying 66 robust candidates and prioritizing 23 candidates with mechanistic support.
Built a modular Nextflow DSL2 implementation of the GATK Best Practices workflow for reproducible germline variant calling.
Selected outcome Developed a reproducible, resumable workflow for scalable germline variant analysis.
Analyzed 300+ WES samples from Indian OSCC-GB patients using GATK-based variant calling, annotation, and clinical interpretation to identify rare high-impact variants.
Selected outcome Identified rare pathogenic variants associated with early onset and poor prognosis; manuscript under review.
Developed a modular Nextflow workflow for automated QC of raw FASTQ sequencing data using FastQC and MultiQC.
Selected outcome Automated the FastQC → MultiQC workflow into a reproducible NGS quality-control pipeline.
Developed an ML workflow for predicting drug-induced neurotoxicity using molecular descriptors and chemical fingerprints.
Selected outcome Evaluated Logistic Regression, Random Forest, and SVM models; Random Forest achieved 84.06% accuracy and 0.91 ROC-AUC.
Analyzed 15,000+ healthcare claims to investigate settlement trends, fraud risk, provider performance, and operational efficiency.
Selected outcome Analyzed ₹2.30+ billion in claims, identified 469 potential fraudulent claims, and developed 4 interactive Tableau dashboards.
Academic background and research specialization.
Pharmaceutical Engineering & Technology
Specialization: Genomics & Computational Biology
CGPA: 8.74 / 10
Master's Thesis: Analyzed 300+ WES samples from Indian OSCC-GB patients using GATK, ClinVar, gnomAD, and ACMG/AMP classification. Identified rare high-impact pathogenic variants associated with early onset and poor prognosis; manuscript under peer review.
Peer-reviewed research and manuscripts.
Manuscript under review - Not yet published
Diseases (2022)
3 Biotech (2022)
NDMC, IIT Bombay
Nemo Lab, IIT Bombay
Western University, Canada
Elucidata Corporation
I'm currently interested in bioinformatics, computational biology, cancer genomics, NGS and multi-omics research opportunities across academia, biotech and pharmaceutical research.
Bengaluru, India