Hirak Sarkar

2.5k total citations · 1 hit paper
21 papers, 513 citations indexed

About

Hirak Sarkar is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Hirak Sarkar has authored 21 papers receiving a total of 513 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 8 papers in Cancer Research and 3 papers in Genetics. Recurrent topics in Hirak Sarkar's work include Single-cell and spatial transcriptomics (10 papers), Genomics and Phylogenetic Studies (6 papers) and Gene expression and cancer classification (5 papers). Hirak Sarkar is often cited by papers focused on Single-cell and spatial transcriptomics (10 papers), Genomics and Phylogenetic Studies (6 papers) and Gene expression and cancer classification (5 papers). Hirak Sarkar collaborates with scholars based in United States, Switzerland and Sweden. Hirak Sarkar's co-authors include Rob Patro, Avi Srivastava, Fatemeh Almodaresi, Nitish Gupta, Mohsen Zakeri, Peter V. Kharchenko, Charlotte Soneson, Michael I. Love, Laraib Malik and Carl Kingsford and has published in prestigious journals such as Cell, Nature Communications and Genes & Development.

In The Last Decade

Hirak Sarkar

19 papers receiving 510 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses

2023 126 citations Taghreed Hirz, Shenglin Mei et al. Nature Communications profile →

Peers

Countries citing papers authored by Hirak Sarkar

Since Specialization

Citations

This map shows the geographic impact of Hirak Sarkar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hirak Sarkar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hirak Sarkar more than expected).

Fields of papers citing papers by Hirak Sarkar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hirak Sarkar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hirak Sarkar. The network helps show where Hirak Sarkar may publish in the future.

Co-authorship network of co-authors of Hirak Sarkar

This figure shows the co-authorship network connecting the top 25 collaborators of Hirak Sarkar. A scholar is included among the top collaborators of Hirak Sarkar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hirak Sarkar. Hirak Sarkar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Comparative Single-Cell Transcriptomics of Human Neuroblastoma and Preclinical Models Reveals Conservation of an Adrenergic Cell State 2025 ·Cancer Research ·(unknown), Hirak Sarkar, (unknown), Jörg Otte, Thale Kristin Olsen, (unknown), Polina Kameneva, Artem V. Artemov, Natalia Akkuratova, Igor Adameyko, Jan‐Bernd Stukenborg, Malin Wickström, Per Kogner, John Inge Johnsen, Shenglin Mei, Peter V. Kharchenko, Ninib Baryawno	2
2	Mapping the topography of spatial gene expression with interpretable deep learning 2025 ·Nature Methods ·(unknown), Brian J. Arnold, Hirak Sarkar, (unknown), Cong Ma, (unknown), Benjamin J. Raphael	12
3	Tumors hijack macrophages for iron supply to promote bone metastasis and anemia 2025 ·Cell ·Yu Han, Hirak Sarkar, Zhan Xu, (unknown), Yongyue Wei, Xiang Hang, Fengshuo Liu, (unknown), Wei Wang, Jennifer Miller, Christina J. DeCoste, (unknown), Robert L. Satcher, Xiang H.-F. Zhang, Yibin Kang	0
4	DifferentialRegulation : a Bayesian hierarchical approach to identify differentially regulated genes 2024 ·Biostatistics ·Simone Tiberi, (unknown), (unknown), Charlotte Soneson, Dongze He, Hirak Sarkar, (unknown), Rob Patro, Mark D. Robinson	0
5	Deciphering normal and cancer stem cell niches by spatial transcriptomics: opportunities and challenges 2024 ·Genes & Development ·Hirak Sarkar, Eun-Mi Lee, (unknown), Yibin Kang	6
6	Single-cell analyses of metastatic bone marrow in human neuroblastoma reveals microenvironmental remodeling and metastatic signature 2024 ·JCI Insight ·Shenglin Mei, (unknown), (unknown), (unknown), Bronte Manouk Verhoeven, Ting Zhao, Xiangyun Li, (unknown), (unknown), Hirak Sarkar, Thale Kristin Olsen, Malin Wickström, Jakob Stenman, (unknown), Peter V. Kharchenko, Philip J. Saylor, John Inge Johnsen, David B. Sykes, Per Kogner, Ninib Baryawno	8
7	Dissecting the immune suppressive human prostate tumor microenvironment via integrated single-cell and spatial transcriptomic analyses breakdown → 2023 ·Nature Communications ·Taghreed Hirz, Shenglin Mei, Hirak Sarkar, Youmna Kfoury, Shulin Wu, Bronte Manouk Verhoeven, Alexander O. Subtelny, Dimitar V. Zlatev, (unknown), Keyan Salari, Evan Murray, Fei Chen, Evan Z. Macosko, Chin‐Lee Wu, David T. Scadden, Douglas M. Dahl, Ninib Baryawno, Philip J. Saylor, Peter V. Kharchenko, David B. Sykes	126
8	Airpart: interpretable statistical models for analyzing allelic imbalance in single-cell datasets 2022 ·Bioinformatics ·(unknown), Hirak Sarkar, Avi Srivastava, Kwangbom Choi, Rob Patro, Michael I. Love	7
9	Haplotype-aware analysis of somatic copy number variations from single-cell transcriptomes 2022 ·Nature Biotechnology ·Teng Gao, Ruslan Soldatov, Hirak Sarkar, (unknown), Evan Biederstedt, Po‐Ru Loh, Peter V. Kharchenko	62
10	Alevin-fry unlocks rapid, accurate and memory-frugal quantification of single-cell RNA-seq data 2022 ·Nature Methods ·Dongze He, Mohsen Zakeri, Hirak Sarkar, Charlotte Soneson, Avi Srivastava, Rob Patro	43
11	Compression of quantification uncertainty for scRNA-seq counts 2021 ·Bioinformatics ·(unknown), Hirak Sarkar, Avi Srivastava, Naim U. Rashid, Rob Patro, Michael I. Love	1
12	A Bayesian framework for inter-cellular information sharing improves dscRNA-seq quantification 2020 ·Bioinformatics ·Avi Srivastava, Laraib Malik, Hirak Sarkar, Rob Patro	8
13	Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data 2020 ·Bioinformatics ·Hirak Sarkar, Avi Srivastava, Héctor Corrada Bravo, Michael I. Love, Rob Patro	7
14	Alignment and mapping methodology influence transcript abundance estimation 2020 ·Genome biology ·Avi Srivastava, Laraib Malik, Hirak Sarkar, Mohsen Zakeri, Fatemeh Almodaresi, Charlotte Soneson, Michael I. Love, Carl Kingsford, Rob Patro	80
15	Minnow: a principled framework for rapid simulation of dscRNA-seq data at the read level 2019 ·Bioinformatics ·Hirak Sarkar, Avi Srivastava, Rob Patro	13
16	A space and time-efficient index for the compacted colored de Bruijn graph 2018 ·Bioinformatics ·Fatemeh Almodaresi, Hirak Sarkar, Avi Srivastava, Rob Patro	38
17	Quark enables semi-reference-based compression of RNA-seq data 2017 ·Bioinformatics ·Hirak Sarkar, Rob Patro	4
18	RapMap: a rapid, sensitive and accurate tool for mapping RNA-seq reads to transcriptomes 2016 ·Bioinformatics ·Avi Srivastava, Hirak Sarkar, Nitish Gupta, Rob Patro	70
19	A New Method for the Estimation of Cellulose 2015 ·SHILAP Revista de lepidopterología ·Hirak Sarkar	10
20	Voronoi game on graphs 2014 ·Theoretical Computer Science ·(unknown), (unknown), (unknown), Hirak Sarkar	13

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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