Sumit Mukherjee

2.7k citations
22 papers · 1.1k indexed · 1 hit paper · h-index 9
Topics
Building Energy and Comfort Optimization (3 papers)Single-cell and spatial transcriptomics (3 papers)Bioinformatics and Genomic Networks (3 papers)
Journals
ScienceNature CommunicationsSHILAP Revista de lepidopterología

In The Last Decade

Sumit Mukherjee

21 papers receiving 1.0k citations

Hit Papers

Single-cell profiling of the developing mouse brain and s...20182026202020232018250500750

Peers

Sumit Mukherjee
Comparison fields: 5 of 109
  • Molecular Biology 817
  • Cancer Research 170
  • Immunology 151
  • Biophysics 103
  • Neurology 102
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Dingding Han China
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Sumit Mukherjee relative to Samantha J. Riesenfeld United States Samantha J. Riesenfeld's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sumit Mukherjee

Since Specialization
Citations

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

Fields of papers citing papers by Sumit Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sumit Mukherjee

This figure shows the co-authorship network connecting the top 25 collaborators of Sumit Mukherjee. A scholar is included among the top collaborators of Sumit 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 Sumit Mukherjee. Sumit Mukherjee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 8
4 2
5 6
6 3
7 4
8 26
9 1
10 3
11 31
12 2
13 13
14
Protecting GANs against privacy attacks by preventing overfitting.
2
15 6
16 17
17 8
18
Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcodingbreakdown →
877
19 16
20 36

About Sumit Mukherjee

Sumit Mukherjee is a scholar working on Toxicology, Neurology and Health, having authored 22 papers that have together received 1.1k indexed citations. Recurring topics across this work include Building Energy and Comfort Optimization (3 papers), Single-cell and spatial transcriptomics (3 papers) and Bioinformatics and Genomic Networks (3 papers). The work is most often cited by research in Biophysics (103 citations), Developmental Neuroscience (53 citations) and Neurology (102 citations). Sumit Mukherjee has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Georg Seelig, Suzie H. Pun, Drew L. Sellers, Anna Kuchina, Bosiljka Tasic, David J. Peeler, Zizhen Yao, Charles M. Roco, Alexander Rosenberg and Paul Sample. Their work appears in journals such as Science, Nature Communications and SHILAP Revista de lepidopterología.

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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