Anasuya Dighe Email & Phone Number

New Haven, Ct, Us

New Haven, Ct, Us

New Haven, Ct, Us

At Yale Center for Molecular and Cellular Oncology, my work is focused on identifying and understanding the key determinants of effective anti-tumor immunity using computational approaches.I utilize single-cell proteogenomic tools to systematically dissect tumor microenvironment and identify candidate immune cell populations and cellular states that impact response or resistance to immune checkpoint inhibitors. Further, I construct patient-derived model systems to enable a mechanistic understanding of these potential determinants of anti-tumor immunity.

New Haven, Ct, Us

I work as a Bioinformatics research scientist at Biomedical Engineering at Yale and our group uses quantitative, systems-level approaches to study intracellular and extracellular signaling networks regulating immune cell functions. We are particularly interested in how variability between single cells impacts immune responses with a focus on the regulation of macrophage activation in response to pathogenic stimulation and within tumor microenvironments.

New Haven, Ct, Us

My work involves developing Next-Gen Sequencing pipelines to understand the link between cancer malignancy and placentation. • I work as principal bioinformatician on projects in Cancer Systems Biology lab to mine large-scale transcriptomic datasets to understand evolutionary link between cancer metastasis and architecture of mammalian placenta• Designed end-to-end bioinformatics pipelines for NGS analysis workflows (including bulk RNASeq, WGS, scRNASeq, snRNASeq) using R, Seurat and scanPY • Conceptualized and formulated workflow to integrate bulk RNASeq data from 10+ mammalian species and perform quality control, alignment, differential gene expression profiles and create customized data visualizations • Programmed computational pipelines to identify novel genetic variants using variant calling methods like GATK, FreeBayes. Identified effects of variants using VEP. • Automated current in-house RNASeq and scRNASeq pipelines to reduce runtime by 50%• Collaborated with High Performance Computing (HPC) core to build computing platforms and programming environments. Standardized these platforms for problem-specific computational pipelines • Mentored two Yale graduate students to guide them with lab computational workflows• Presented research as talks and posters at Yale Cancer Systems Biology Symposium (2019-22)

Bangalore, Karnataka, In

I implemented graph theory principles and network biology to study protein-drug interactions. I investigated effects of drug binding on proteins by performing large-scale GPU-based Molecular Dynamics (MD) simulations of drug-protein complexes. I collaborated with mathematician to help formalize, implement a metric to score binding site similarity based on network architecture of binding site. I initiated and published an in-depth study of drug-binding sites in G-Protein Coupled Receptors (GPCRs) to reveal network similarities in their architecture and identify major players of signal transduction.

Bangalore, Karnataka, In

I computationally mined and curated a dataset of 65000 protein-drug interactions investigate structural similarity within drug binding sites. Used in-house distance-based algorithm to assess binding site similarity across diverse drug binding sites.

Doctor Of Philosophy - Phd, Computational Biology And Structural Bioinformatics

Master'S Degree, Bioinformatics

Bachelor Of Science - Bs, Biotechnology