Chanchal Kumar

14.2k total citations · 5 hit papers
35 papers, 10.8k citations indexed

About

Chanchal Kumar is a scholar working on Molecular Biology, Spectroscopy and Surgery. According to data from OpenAlex, Chanchal Kumar has authored 35 papers receiving a total of 10.8k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Molecular Biology, 14 papers in Spectroscopy and 5 papers in Surgery. Recurrent topics in Chanchal Kumar's work include Advanced Proteomics Techniques and Applications (14 papers), Metabolomics and Mass Spectrometry Studies (8 papers) and Mass Spectrometry Techniques and Applications (6 papers). Chanchal Kumar is often cited by papers focused on Advanced Proteomics Techniques and Applications (14 papers), Metabolomics and Mass Spectrometry Studies (8 papers) and Mass Spectrometry Techniques and Applications (6 papers). Chanchal Kumar collaborates with scholars based in Germany, Sweden and Denmark. Chanchal Kumar's co-authors include Matthias Mann, Jesper V. Olsen, Florian Gnad, Boris Maček, Chunaram Choudhary, Michael L. Nielsen, Michael Rehman, Tobias C. Walther, Blagoy Blagoev and Peter Mortensen and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Chanchal Kumar

35 papers receiving 10.6k citations

Hit Papers

Lysine Acetylation Targets Protein Complexes and Co-Regul... 2006 2026 2012 2019 2009 2006 2010 2006 2021 1000 2.0k 3.0k
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.

  1. Lysine Acetylation Targets Protein Complexes and Co-Regulates Major Cellular Functions
    2009 3.3k citations Chunaram Choudhary, Chanchal Kumar et al. Science profile →
  2. Global, In Vivo, and Site-Specific Phosphorylation Dynamics in Signaling Networks
    2006 2.8k citations Jesper V. Olsen, Florian Gnad et al. profile →
  3. Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis
    2010 1.2k citations Jesper V. Olsen, Michiel Vermeulen et al. Science Signaling profile →
  4. The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins
    2006 541 citations Jun Adachi, Chanchal Kumar et al. Genome biology profile →
  5. Artificial intelligence for proteomics and biomarker discovery
    2021 216 citations Matthias Mann, Chanchal Kumar et al. Cell Systems profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Chanchal Kumar Germany 26 8.4k 2.8k 1.4k 1.2k 758 35 10.8k
Florian Gnad Germany 37 11.3k 1.3× 3.3k 1.2× 1.9k 1.3× 1.7k 1.4× 785 1.0× 54 13.6k
W. Hayes McDonald United States 55 8.6k 1.0× 1.7k 0.6× 1.0k 0.7× 2.0k 1.7× 883 1.2× 138 11.3k
Michael L. Nielsen Denmark 55 10.8k 1.3× 3.0k 1.1× 2.8k 2.0× 1.2k 1.0× 741 1.0× 143 13.7k
Noah Dephoure United States 38 8.5k 1.0× 1.1k 0.4× 1.2k 0.8× 2.0k 1.7× 729 1.0× 60 10.7k
Sean A. Beausoleil United States 25 7.3k 0.9× 2.9k 1.0× 1.0k 0.7× 1.5k 1.2× 813 1.1× 30 9.0k
Edward L. Huttlin United States 35 7.1k 0.8× 2.4k 0.8× 946 0.7× 1.2k 1.0× 1.5k 2.0× 55 9.2k
Birgit Schilling United States 52 6.2k 0.7× 1.8k 0.6× 808 0.6× 764 0.6× 887 1.2× 179 10.0k
Shao‐En Ong United States 36 11.5k 1.4× 4.9k 1.7× 1.5k 1.1× 1.7k 1.4× 609 0.8× 81 14.3k
Carson C. Thoreen United States 25 10.3k 1.2× 1.2k 0.4× 1.0k 0.7× 1.9k 1.6× 1.8k 2.3× 36 12.7k
Dirk Wolters Germany 32 6.3k 0.7× 4.2k 1.5× 624 0.4× 734 0.6× 394 0.5× 66 9.5k

Countries citing papers authored by Chanchal Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Chanchal Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chanchal Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Chanchal Kumar. A scholar is included among the top collaborators of Chanchal Kumar 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 Chanchal Kumar. Chanchal Kumar 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
1.
Buvall, Lisa, Robert Menzies, Julie Williams, et al.. (2022). Selecting the right therapeutic target for kidney disease. Frontiers in Pharmacology. 13. 971065–971065. 8 indexed citations
2.
Mann, Matthias, Chanchal Kumar, Wenfeng Zeng, & Maximilian T. Strauss. (2021). Artificial intelligence for proteomics and biomarker discovery. Cell Systems. 12(8). 759–770. 216 indexed citations breakdown →
3.
Voronova, Veronika, Victor Sokolov, Sara Straniero, et al.. (2020). A Physiology-Based Model of Bile Acid Distribution and Metabolism Under Healthy and Pathologic Conditions in Human Beings. Cellular and Molecular Gastroenterology and Hepatology. 10(1). 149–170. 33 indexed citations
4.
Cavalli, Marco, Klev Diamanti, Gang Pan, et al.. (2020). A Multi-Omics Approach to Liver Diseases: Integration of Single Nuclei Transcriptomics with Proteomics and HiCap Bulk Data in Human Liver. OMICS A Journal of Integrative Biology. 24(4). 180–194. 26 indexed citations
5.
Hage, Camilla, Lars Löfgren, Filippos Michopoulos, et al.. (2020). Metabolomic Profile in HFpEF vs HFrEF Patients. Journal of Cardiac Failure. 26(12). 1050–1059. 60 indexed citations
6.
Eriksson, Maria J., Anna Walentinsson, Matthias Corbascio, et al.. (2019). Transcriptomics of cardiac biopsies reveals differences in patients with or without diagnostic parameters for heart failure with preserved ejection fraction. Scientific Reports. 9(1). 3179–3179. 39 indexed citations
7.
Diamanti, Klev, Marco Cavalli, Gang Pan, et al.. (2019). Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes. Scientific Reports. 9(1). 9653–9653. 32 indexed citations
8.
Kumar, Chanchal, et al.. (2016). A Review on Management of Blood Glucose in Type 2 Diabetes Mellitus. International Journal of Plant Animal and Environmental Sciences. 2016(1). 1 indexed citations
9.
Oppermann, Felix, et al.. (2011). Combination of Chemical Genetics and Phosphoproteomics for Kinase Signaling Analysis Enables Confident Identification of Cellular Downstream Targets. Molecular & Cellular Proteomics. 11(4). O111.012351–O111.012351. 52 indexed citations
10.
Sharma, Kirti, Chanchal Kumar, Gÿorgý Kéri, et al.. (2010). Quantitative Analysis of Kinase-Proximal Signaling in Lipopolysaccharide-Induced Innate Immune Response. Journal of Proteome Research. 9(5). 2539–2549. 28 indexed citations
11.
Olsen, Jesper V., Michiel Vermeulen, Anna Santamaría, et al.. (2010). Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis. Science Signaling. 3(104). ra3–ra3. 1221 indexed citations breakdown →
12.
Choudhary, Chunaram, Chanchal Kumar, Florian Gnad, et al.. (2009). Lysine Acetylation Targets Protein Complexes and Co-Regulates Major Cellular Functions. Science. 325(5942). 834–840. 3252 indexed citations breakdown →
13.
Forner, Francesca, Chanchal Kumar, Christian A. Luber, et al.. (2009). Proteome Differences between Brown and White Fat Mitochondria Reveal Specialized Metabolic Functions. Cell Metabolism. 10(4). 324–335. 180 indexed citations
14.
Kumar, Chanchal & Matthias Mann. (2009). Bioinformatics analysis of mass spectrometry‐based proteomics data sets. FEBS Letters. 583(11). 1703–1712. 120 indexed citations
15.
Waanders, Leonie F., Karolina Chwalek, Mara Monetti, et al.. (2009). Quantitative proteomic analysis of single pancreatic islets. Proceedings of the National Academy of Sciences. 106(45). 18902–18907. 177 indexed citations
16.
Bonaldi, Tiziana, Tobias Straub, Jürgen Cox, et al.. (2008). Combined Use of RNAi and Quantitative Proteomics to Study Gene Function in Drosophila. Molecular Cell. 31(5). 762–772. 83 indexed citations
17.
Maček, Boris, Florian Gnad, Boumediene Soufi, et al.. (2007). Phosphoproteome Analysis of E. coli Reveals Evolutionary Conservation of Bacterial Ser/Thr/Tyr Phosphorylation. Molecular & Cellular Proteomics. 7(2). 299–307. 354 indexed citations
18.
Adachi, Jun, Chanchal Kumar, Yanling Zhang, & Matthias Mann. (2007). In-depth Analysis of the Adipocyte Proteome by Mass Spectrometry and Bioinformatics. Molecular & Cellular Proteomics. 6(7). 1257–1273. 95 indexed citations
19.
Adachi, Jun, Chanchal Kumar, Yanling Zhang, Jesper V. Olsen, & Matthias Mann. (2006). The human urinary proteome contains more than 1500 proteins, including a large proportion of membrane proteins. Genome biology. 7(9). R80–R80. 541 indexed citations breakdown →
20.
Zhang, Yanling, Jun Adachi, Jesper V. Olsen, et al.. (2006). MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes. Nucleic Acids Research. 35(Database). D771–D779. 52 indexed citations

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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