Hirak Sarkar

Hirak Sarkar

Ludwig Scholar at the Princeton University; Former research assistant at the Computer Science Department, University of Maryland

Posts by Category

Bioinformatics

Accurate, fast and lightweight clustering of de novo transcriptomes using fragment equivalence classes

Published in RECOMB-Seq, 2015

We present a method for clustering contigs from de novo transcriptome assemblies based upon the relationships exposed by multi-mapping sequencing fragments. Read more

Recommended citation: Accurate, fast and lightweight clustering of de novo transcriptomes using fragment equivalence classes A Srivastava*, H Sarkar*, L Malik, R Patro - arXiv preprint arXiv:1604.03250, 2016

Quark enables semi-reference-based compression of RNA-seq data

Published in Bioinformatics, 2017

We present Quark, a semi-reference-based compression tool designed for RNA-seq data. Quark makes use of a reference sequence when encoding reads, but produces a representation that can be decoded independently, without the need for a reference. Read more

Recommended citation: Hirak Sarkar, and Rob Patro. Quark enables semi-reference-based compression of RNA-seq data. Bioinformatics 33.21 (2017): 3380-3386.

Towards selective-alignment: Bridging the accuracy gap between alignment-based and alignment-free transcript quantification

Published in ACM-BCB, 2018

We introduce an algorithm for selectively aligning high-throughput sequencing reads to a transcriptome, with the goal of improving transcript-level quantification in difficult or adversarial scenarios. Read more

Recommended citation: Sarkar, Hirak*, Mohsen Zakeri*, Laraib Malik, Rob Patro Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. 2018.

ML

Social Media Attributions in the Context of Water Crisis

Published in Arxiv, 2020

In this paper, we explore how can we use social media data and an AI-driven approach to complement traditional surveys and automatically extract attribution factors. Read more

Recommended citation: R Sarkar, H Sarkar, S Mahinder, AR KhudaBukhsh - arXiv preprint arXiv:2001.01697

NLP

Social Media Attributions in the Context of Water Crisis

Published in Arxiv, 2020

In this paper, we explore how can we use social media data and an AI-driven approach to complement traditional surveys and automatically extract attribution factors. Read more

Recommended citation: R Sarkar, H Sarkar, S Mahinder, AR KhudaBukhsh - arXiv preprint arXiv:2001.01697

Other

Voronoi Game on Graphs

Published in TCS, 2015

An approximation algorithm and some related proofs for the two player game in facility location problems. Voronoi game is a geometric model of competitive facility location problem played between two players. Read more

Recommended citation: S Bandyapadhyay, A Banik, S Das, H Sarkar - Theoretical Computer Science, 2015 (authors alphabetical order)

Social Media Attributions in the Context of Water Crisis

Published in Arxiv, 2020

In this paper, we explore how can we use social media data and an AI-driven approach to complement traditional surveys and automatically extract attribution factors. Read more

Recommended citation: R Sarkar, H Sarkar, S Mahinder, AR KhudaBukhsh - arXiv preprint arXiv:2001.01697

Social Science

Social Media Attributions in the Context of Water Crisis

Published in Arxiv, 2020

In this paper, we explore how can we use social media data and an AI-driven approach to complement traditional surveys and automatically extract attribution factors. Read more

Recommended citation: R Sarkar, H Sarkar, S Mahinder, AR KhudaBukhsh - arXiv preprint arXiv:2001.01697

Theory

Voronoi Game on Graphs

Published in TCS, 2015

An approximation algorithm and some related proofs for the two player game in facility location problems. Voronoi game is a geometric model of competitive facility location problem played between two players. Read more

Recommended citation: S Bandyapadhyay, A Banik, S Das, H Sarkar - Theoretical Computer Science, 2015 (authors alphabetical order)