Ashir Borah

About

I am a Graduate Researcher in Biological and Medical Informatics at the University of California San Francisco/Arc Institute, working in the Luke Gilbert and Brian Hie labs. My work integrates computational analysis of genome-scale CRISPR data with experimental biology to identify novel therapeutic targets in cancer. Previously, I served as a Computational Associate at the Broad Institute of MIT and Harvard, contributing to cancer data science and the Dependency Map Project.

I earned my B.S. in Mathematics and Computer Science from Dickinson College, graduating Magna Cum Laude and Phi Beta Kappa. My interdisciplinary expertise spans computational biology, machine learning, and functional genomics.

Research Focus

CRISPR Data Analysis & Computational Genomics

Conducting large-scale computational analysis on CRISPR screens to uncover novel cancer vulnerabilities and therapeutic targets.

Cancer Data Science

Integrating machine learning with genomic data to model genetic dependencies and biomarkers in cancer.

Experimental & Computational Integration

Merging computational predictions with laboratory validation, including cell culture and molecular cloning experiments.

Selected Publications

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

S. Raghavan, P.S. Winter, A.W. Navia, H.L. Williams, A. DenAdel, R.L. Kalekar, …, A.A. Borah, et al.

Cell · 2021 · Accepted

Repeat expansions confer WRN dependence in microsatellite-unstable cancers

N. van Wietmarschen, S. Sridharan, W.J. Nathan, A. Tubbs, E.M. Chan, …, A.A. Borah, et al.

Nature · 2020

Sparse dictionary learning recovers pleiotropy from human cell fitness screens

J. Pan, J.J. Kwon, J.A. Talamas, A.A. Borah, F. Vazquez, J.S. Boehm, et al.

Cell Systems · Under Revision

A ubiquitination cascade regulates the integrated stress response and epithelial cancer survival

L.D. Cervia, T. Shibue, B. Gaeta, A.A. Borah, L. Leung, N. Li, et al.

Cancer Discovery · Under Revision

Partial gene suppression improves identification of cancer vulnerabilities when CRISPR-Cas9 knockout is pan-lethal

J.M. Krill-Burger, J.M. Dempster, A.A. Borah, et al.

Under Preparation

Education & Experience

University of California San Francisco / Arc Institute

2022 - Present

Graduate Researcher, Biological and Medical Informatics

Conduct computational analysis on genome-scale CRISPR data to identify novel therapeutic targets
Integrate experimental validation through cell culture and molecular cloning
Collaborate in multidisciplinary research with Luke Gilbert and Brian Hie labs

Broad Institute of MIT and Harvard

2019 - 2022

Computational Associate I & II, Cancer Data Science

Led computational efforts to validate therapeutic genetic targets and identify biomarkers
Developed strategies for discovering targets from genome-scale screens
Contributed to an open-source machine learning platform modeling genetic knockout dependency profiles
Modeled latent variables from CRISPR-Cas9 screens, resulting in key publications

Dickinson College

Graduated 2019

B.S. Mathematics and Computer Science, Magna Cum Laude, Phi Beta Kappa

Conducted computational research on leukemia cell lines
Earned several academic honors and participated in multiple research projects