Voronoi game on graphs. - Sayan Bandyapadhyay; Aritra Banik; Sandip Das 001; Hirak Sarkar (Theor. Comput. Sci., 2015)

RapMap: a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes. - Avi Srivastava; Hirak Sarkar; Nitish Gupta; Rob Patro (Bioinform., 2016)

Accurate, Fast and Lightweight Clustering of de novo Transcriptomes using Fragment Equivalence Classes. - Avi Srivastava; Hirak Sarkar; Laraib Malik; Rob Patro (CoRR, 2016)

Quark enables semi-reference-based compression of RNA-seq data. - Hirak Sarkar; Rob Patro (Bioinform., 2017)

Towards Selective-Alignment: Bridging the Accuracy Gap between Alignment-Based and Alignment-Free Transcript Quantification. - Hirak Sarkar; Mohsen Zakeri; Laraib Malik; Rob Patro (BCB, 2018)

A space and time-efficient index for the compacted colored de Bruijn graph. - Fatemeh Almodaresi; Hirak Sarkar; Avi Srivastava; Rob Patro (Bioinform., 2018)

Minnow: a principled framework for rapid simulation of dscRNA-seq data at the read level. - Hirak Sarkar; Avi Srivastava; Rob Patro (Bioinform., 2019)

Social Media Attributions in the Context of Water Crisis. - Rupak Sarkar; Sayantan Mahinder; Hirak Sarkar; Ashiqur R. KhudaBukhsh (EMNLP (1), 2020)

Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data. - Hirak Sarkar; Avi Srivastava; Héctor Corrada Bravo; Michael I. Love; Rob Patro (Bioinform., 2020)

A Bayesian framework for inter-cellular information sharing improves dscRNA-seq quantification. - Avi Srivastava; Laraib Malik; Hirak Sarkar; Rob Patro (Bioinform., 2020)

Computational approaches for improving the accuracy and efficiency of RNA-seq analysis. - Hirak Sarkar (2020)

Compression of quantification uncertainty for scRNA-seq counts. - Scott Van Buren; Hirak Sarkar; Avi Srivastava; Naim U. Rashid; Rob Patro; Michael I. Love (Bioinform., 2021)

Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets. - Wancen Mu; Hirak Sarkar; Avi Srivastava; Kwangbom Choi; Rob Patro; Michael I. Love (Bioinform., 2022)

Mapping the Topography of Spatial Gene Expression with Interpretable Deep Learning. - Uthsav Chitra; Brian J. Arnold; Hirak Sarkar; Cong Ma 008; Sereno Lopez-Darwin; Kohei Sanno; Benjamin J. Raphael (RECOMB, 2024)

A count-based model for delineating cell-cell interactions in spatial transcriptomics data. - Hirak Sarkar; Uthsav Chitra; Julian Gold; Benjamin J. Raphael (Bioinform., 2024)

Joint Imputation and Deconvolution of Gene Expression Across Spatial Transcriptomics Platforms. - Hongyu Zheng; Hirak Sarkar; Benjamin J. Raphael (RECOMB, 2025)