Arnab Nayak

945 total citations
24 papers, 724 citations indexed

About

Arnab Nayak is a scholar working on Molecular Biology, Oncology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Arnab Nayak has authored 24 papers receiving a total of 724 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 5 papers in Oncology and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Arnab Nayak's work include Ubiquitin and proteasome pathways (9 papers), Muscle Physiology and Disorders (7 papers) and Peptidase Inhibition and Analysis (5 papers). Arnab Nayak is often cited by papers focused on Ubiquitin and proteasome pathways (9 papers), Muscle Physiology and Disorders (7 papers) and Peptidase Inhibition and Analysis (5 papers). Arnab Nayak collaborates with scholars based in Germany, Italy and Japan. Arnab Nayak's co-authors include Stefan Müller, Mamta Amrute‐Nayak, Christian Morsczeck, Friederike Berberich‐Siebelt, Sandra Viale-Bouroncle, Julia Schümann, Judith Glöckner-Pagel, Martin Vaeth, Mathias Buttmann and Edgar Serfling and has published in prestigious journals such as Journal of Biological Chemistry, Nano Letters and Molecular Cell.

In The Last Decade

Arnab Nayak

22 papers receiving 721 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arnab Nayak Germany 14 529 165 149 90 81 24 724
Amy Goodale United States 9 664 1.3× 80 0.5× 159 1.1× 54 0.6× 52 0.6× 16 861
Christopher S. Bland United States 5 578 1.1× 65 0.4× 105 0.7× 76 0.8× 67 0.8× 5 728
Tadashi Anan Japan 11 555 1.0× 46 0.3× 236 1.6× 126 1.4× 61 0.8× 32 744
Ion Cristian Cirstea Germany 14 484 0.9× 98 0.6× 105 0.7× 101 1.1× 35 0.4× 26 632
Erik H. Knelson United States 15 397 0.8× 183 1.1× 214 1.4× 166 1.8× 59 0.7× 22 703
Sean F. Landrette United States 12 441 0.8× 76 0.5× 108 0.7× 71 0.8× 58 0.7× 18 663
Martine St-Jean Canada 10 557 1.1× 176 1.1× 197 1.3× 49 0.5× 86 1.1× 14 785
Mary Shen United States 10 578 1.1× 187 1.1× 103 0.7× 253 2.8× 69 0.9× 12 829
Jian-Jiang Hao United States 14 364 0.7× 167 1.0× 99 0.7× 253 2.8× 29 0.4× 16 741
Gillian E. Begg United States 12 547 1.0× 103 0.6× 60 0.4× 102 1.1× 42 0.5× 16 903

Countries citing papers authored by Arnab Nayak

Since Specialization
Citations

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

Fields of papers citing papers by Arnab Nayak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arnab Nayak

This figure shows the co-authorship network connecting the top 25 collaborators of Arnab Nayak. A scholar is included among the top collaborators of Arnab Nayak 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 Arnab Nayak. Arnab Nayak 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.
Lanzuolo, Chiara, Natalie Weber, Dongchao Lu, et al.. (2025). Calcium Handling Machinery and Sarcomere Assembly are Impaired Through Multipronged Mechanisms in Cancer Cytokine‐Induced Cachexia. Journal of Cachexia Sarcopenia and Muscle. 16(2). e13776–e13776.
2.
3.
Weber, Natalie, Arnab Nayak, Ε. L. Wehry, et al.. (2023). Skeletal muscle fiber hypercontraction induced by Bothrops asper myotoxic phospholipases A2 ex vivo does not involve a direct action on the contractile apparatus. Pflügers Archiv - European Journal of Physiology. 475(10). 1193–1202. 2 indexed citations
4.
Amrute‐Nayak, Mamta, et al.. (2023). Emerging Mechanisms of Skeletal Muscle Homeostasis and Cachexia: The SUMO Perspective. Cells. 12(4). 644–644. 9 indexed citations
5.
Perrelli, Andrea, Kiran Kumar Bali, Raffaella Mastrocola, et al.. (2023). Identification of galectin-3 as a novel potential prognostic/predictive biomarker and therapeutic target for cerebral cavernous malformation disease. Genes & Diseases. 11(1). 67–71. 2 indexed citations
6.
Scholz, Tim, et al.. (2022). Cardiac ventricular myosin and slow skeletal myosin exhibit dissimilar chemomechanical properties despite bearing the same myosin heavy chain isoform. Journal of Biological Chemistry. 298(7). 102070–102070. 10 indexed citations
7.
Amrute‐Nayak, Mamta, et al.. (2022). SENP7 deSUMOylase-governed transcriptional program coordinates sarcomere assembly and is targeted in muscle atrophy. Cell Reports. 41(8). 111702–111702. 9 indexed citations
8.
Nayak, Arnab, Peter Franz, Steffen Walter, et al.. (2020). Single-molecule analysis reveals that regulatory light chains fine-tune skeletal myosin II function. Journal of Biological Chemistry. 295(20). 7046–7059. 15 indexed citations
9.
Amrute‐Nayak, Mamta, et al.. (2020). Chemotherapy triggers cachexia by deregulating synergetic function of histone‐modifying enzymes. Journal of Cachexia Sarcopenia and Muscle. 12(1). 159–176. 17 indexed citations
10.
Nayak, Arnab & Mamta Amrute‐Nayak. (2020). SUMO system – a key regulator in sarcomere organization. FEBS Journal. 287(11). 2176–2190. 8 indexed citations
11.
Nayak, Arnab, et al.. (2019). Regulation of SETD7 Methyltransferase by SENP3 Is Crucial for Sarcomere Organization and Cachexia. Cell Reports. 27(9). 2725–2736.e4. 21 indexed citations
12.
Nayak, Arnab, et al.. (2017). Flightless-I governs cell fate by recruiting the SUMO isopeptidase SENP3 to distinct HOX genes. Epigenetics & Chromatin. 10(1). 15–15. 13 indexed citations
13.
Brandes, Ralf P., Christoph Schürmann, Ivana Josipovic, et al.. (2016). The Cytosolic NADPH Oxidase Subunit NoxO1 Promotes an Endothelial Stalk Cell Phenotype. Arteriosclerosis Thrombosis and Vascular Biology. 36(8). 1558–1565. 21 indexed citations
14.
15.
Nayak, Arnab, Sandra Viale-Bouroncle, Christian Morsczeck, & Stefan Müller. (2014). The SUMO-Specific Isopeptidase SENP3 Regulates MLL1/MLL2 Methyltransferase Complexes and Controls Osteogenic Differentiation. Molecular Cell. 55(1). 47–58. 58 indexed citations
16.
Nayak, Arnab, et al.. (2014). mTOR Signaling Regulates Nucleolar Targeting of the SUMO-Specific Isopeptidase SENP3. Molecular and Cellular Biology. 34(24). 4474–4484. 27 indexed citations
17.
Nayak, Arnab, et al.. (2013). The SUMO system: a master organizer of nuclear protein assemblies. Chromosoma. 122(6). 475–485. 61 indexed citations
18.
Azukizawa, Hiroaki, Nobuo Kanazawa, Arnab Nayak, et al.. (2011). Steady state migratory RelB+ langerin+ dermal dendritic cells mediate peripheral induction of antigen‐specific CD4+CD25+Foxp3+ regulatory T cells. European Journal of Immunology. 41(5). 1420–1434. 69 indexed citations
19.
Nayak, Arnab, Judith Glöckner-Pagel, Martin Vaeth, et al.. (2009). Sumoylation of the Transcription Factor NFATc1 Leads to Its Subnuclear Relocalization and Interleukin-2 Repression by Histone Deacetylase. Journal of Biological Chemistry. 284(16). 10935–10946. 83 indexed citations
20.
Nayak, Arnab, et al.. (2008). Blimp-1Δexon7: A naturally occurring Blimp-1 deletion mutant with auto-regulatory potential. Experimental Cell Research. 314(20). 3614–3627. 15 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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