Sayan Mukherjee

72.9k total citations · 4 hit papers
139 papers, 43.3k citations indexed

About

Sayan Mukherjee is a scholar working on Molecular Biology, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Sayan Mukherjee has authored 139 papers receiving a total of 43.3k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Molecular Biology, 30 papers in Artificial Intelligence and 28 papers in Computational Theory and Mathematics. Recurrent topics in Sayan Mukherjee's work include Gene expression and cancer classification (26 papers), Bioinformatics and Genomic Networks (22 papers) and Topological and Geometric Data Analysis (20 papers). Sayan Mukherjee is often cited by papers focused on Gene expression and cancer classification (26 papers), Bioinformatics and Genomic Networks (22 papers) and Topological and Geometric Data Analysis (20 papers). Sayan Mukherjee collaborates with scholars based in United States, Germany and Canada. Sayan Mukherjee's co-authors include Jill P. Mesirov, Todd R. Golub, Pablo Tamayo, Eric S. Lander, Aravind Subramanian, Amanda G. Paulovich, Michael A. Gillette, Vamsi K. Mootha, Scott L. Pomeroy and Benjamin L. Ebert and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Sayan Mukherjee

134 papers receiving 42.6k 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.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

2005 34.0k citations Sayan Mukherjee, Todd R. Golub et al. profile →
Choosing Multiple Parameters for Support Vector Machines

2002 1.6k citations Sayan Mukherjee et al. profile →
Multiclass cancer diagnosis using tumor gene expression signatures

2001 1.5k citations Sayan Mukherjee, Massimo Loda et al. profile →
Feature Selection for SVMs

2000 692 citations Sayan Mukherjee et al. profile →

Peers

Countries citing papers authored by Sayan Mukherjee

Since Specialization

Citations

This map shows the geographic impact of Sayan Mukherjee'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 Sayan Mukherjee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sayan Mukherjee more than expected).

Fields of papers citing papers by Sayan Mukherjee

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sayan Mukherjee. 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 Sayan Mukherjee. The network helps show where Sayan Mukherjee may publish in the future.

Co-authorship network of co-authors of Sayan Mukherjee

This figure shows the co-authorship network connecting the top 25 collaborators of Sayan Mukherjee. A scholar is included among the top collaborators of Sayan Mukherjee 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 Sayan Mukherjee. Sayan Mukherjee 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	Social and environmental predictors of gut microbiome age in wild baboons 2025 ·eLife ·Mauna Dasari, Kimberly Roche, David Jansen, (unknown), Susan C. Alberts, Jenny Tung, Jack A. Gilbert, Ran Blekhman, Sayan Mukherjee, Elizabeth A. Archie	1
2	Universal gut microbial relationships in the gut microbiome of wild baboons 2023 ·eLife ·Kimberly Roche, Johannes R. Björk, Mauna Dasari, Laura Grieneisen, David Jansen, Trevor J. Gould, Laurence R. Gesquiere, Luis B. Barreiro, Susan C. Alberts, Ran Blekhman, Jack A. Gilbert, Jenny Tung, Sayan Mukherjee, Elizabeth A. Archie	12
3	Concerning Two Classes of Non-Diophantine Arithmetics 2022 ·SHILAP Revista de lepidopterología ·(unknown), (unknown), Sayan Mukherjee	1
4	A statistical pipeline for identifying physical features that differentiate classes of 3D shapes 2021 ·The Annals of Applied Statistics ·Bruce Wang, (unknown), (unknown), Tingran Gao, Douglas Boyer, Sayan Mukherjee, Lorin Crawford	12
5	Statistical robustness of Markov chain Monte Carlo accelerators 2021 ·(unknown), (unknown), Yicheng Wang, Sayan Mukherjee, Alvin R. Lebeck	8
6	Learning Subspaces of Different Dimensions 2021 ·Journal of Computational and Graphical Statistics ·B.S. Thomas, Kisung You, Lizhen Lin, Lek‐Heng Lim, Sayan Mukherjee	0
7	A unifying framework for interpreting and predicting mutualistic systems 2019 ·Nature Communications ·Feilun Wu, Allison J. Lopatkin, (unknown), (unknown), Sayan Mukherjee, Lingchong You	23
8	The Geometry of Synchronization Problems and Learning Group Actions 2019 ·Discrete & Computational Geometry ·Tingran Gao, Jacek Brodzki, Sayan Mukherjee	5
9	Evolution of DNA Methylation in Papio Baboons 2018 ·Molecular Biology and Evolution ·Tauras P. Vilgalys, Jeffrey Rogers, Clifford J. Jolly, (unknown), Sayan Mukherjee, Jenny Tung	9
10	HOMINID: a framework for identifying associations between host genetic variation and microbiome composition 2017 ·GigaScience ·Joshua Lynch, Karen Tang, Sambhawa Priya, (unknown), (unknown), Evan Tang, Sayan Mukherjee, Dan Knights, Ran Blekhman	18
11	Efficient Genome-Wide Sequencing and Low-Coverage Pedigree Analysis from Noninvasively Collected Samples 2016 ·Genetics ·Noah Snyder‐Mackler, William H. Majoros, Michael L. Yuan, Amanda O. Shaver, Jacob B. Gordon, Gisela H. Kopp, Stephen A. Schlebusch, Jeffrey D. Wall, Susan C. Alberts, Sayan Mukherjee, Xiang Zhou, Jenny Tung	61
12	Functional Data Analysis using a Topological Summary Statistic: the Smooth Euler Characteristic Transform 2016 ·arXiv (Cornell University) ·Lorin Crawford, (unknown), Andrew Chen, Sayan Mukherjee, Raúl Rabadán	6
13	Topological Summaries of Tumor Images Improve Prediction of Disease Free Survival in Glioblastoma Multiforme 2016 ·arXiv (Cornell University) ·Lorin Crawford, (unknown), Andrew Chen, Sayan Mukherjee, Raúl Rabadán	4
14	Probabilistic Fréchet means for time varying persistence diagrams 2015 ·Electronic Journal of Statistics ·Elizabeth Munch, Katharine Turner, Paul Bendich, Sayan Mukherjee, Jonathan C. Mattingly, John Harer	26
15	Supervised Dimension Reduction Using Bayesian Mixture Modeling 2010 ·Journal of Machine Learning Research ·(unknown), Feng Liang, Sayan Mukherjee	1
16	Genomic Features That Predict Allelic Imbalance in Humans Suggest Patterns of Constraint on Gene Expression Variation 2009 ·Molecular Biology and Evolution ·Jenny Tung, Olivier Fédrigo, Ralph Haygood, Sayan Mukherjee, Gregory A. Wray	8
17	Characterizing the Function Space for Bayesian Kernel Models 2007 ·Journal of Machine Learning Research ·Natesh S. Pillai, Qiang Wu, Feng Liang, Sayan Mukherjee, Robert L. Wolpert	28
18	Estimation of Gradients and Coordinate Covariation in Classification 2006 ·Journal of Machine Learning Research ·Sayan Mukherjee, Qiang Wu	43
19	Learning Coordinate Covariances via Gradients 2006 ·Journal of Machine Learning Research ·Sayan Mukherjee, Ding‐Xuan Zhou	55
20	Androgen-Induced Differentiation and Tumorigenicity of Human Prostate Epithelial Cells 2004 ·Cancer Research ·Raanan Berger, Phillip G. Febbo, Pradip K. Majumder, Jean J. Zhao, Sayan Mukherjee, Sabina Signoretti, Katrina Campbell, William R. Sellers, Thomas M. Roberts, Massimo Loda, Todd R. Golub, William C. Hahn	140

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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