Jay Gopalakrishnan
Impact in
- Cell Biology top 2%
- Microtubule and mitosis dynamics
- Developmental Neuroscience top 10%
Papers in
-
- Epigenetics and DNA Methylation 5
- Protist diversity and phylogeny 5
- Renal and related cancers 4
- Pluripotent Stem Cells Research 4
- Hedgehog Signaling Pathway Studies 3
- Cell Biology 15
- Microtubule and mitosis dynamics 14
- Co-authors
- Tomer Avidor‐Reiss (8 shared papers)Elke Gabriel (8 shared papers)Anand Ramani (7 shared papers)Aruljothi Mariappan (9 shared papers)Stéphanie Blachon (2 shared papers)Daniela Nicastro (2 shared papers)Roberto Pallini (6 shared papers)Lucia Ricci‐Vitiani (6 shared papers)
- Journals
- Cell Reports (3 papers)Nature Communications (2 papers)Human Molecular Genetics (2 papers)SLAS DISCOVERY (2 papers)Journal of Visualized Experiments (2 papers)
- Partner nations
- GermanyUnited StatesItaly
In The Last Decade
Jay Gopalakrishnan
36 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 89
- Cell Biology 537
- Developmental Neuroscience 72
- Molecular Biology 859
- Genetics 343
- Genetics 82
Countries citing papers authored by Jay Gopalakrishnan
This map shows the geographic impact of Jay Gopalakrishnan'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 Jay Gopalakrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Gopalakrishnan more than expected).
Fields of papers citing papers by Jay Gopalakrishnan
This network shows the impact of papers produced by Jay Gopalakrishnan. 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 Jay Gopalakrishnan. The network helps show where Jay Gopalakrishnan may publish in the future.
Co-authors
The 25 scholars most cited alongside Jay Gopalakrishnan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 172 | |
| 2 | 2008 | 126 | |
| 3 | 2011 | 107 | |
| 4 | 2020 | 71 | |
| 5 | 2013 | 66 | |
| 6 | 2012 | 62 | |
| 7 | 2014 | 52 | |
| 8 | 2014 | 46 | |
| 9 | 2015 | 40 | |
| 10 | 2020 | 39 | |
| 11 | 2010 | 39 | |
| 12 | 2021 | 35 | |
| 13 | 2012 | 35 | |
| 14 | 2020 | 32 | |
| 15 | 2021 | 31 | |
| 16 | 2017 | 30 | |
| 17 | 2019 | 27 | |
| 18 | 2020 | 24 | |
| 19 | 2022 | 22 | |
| 20 | 2018 | 19 |
About Jay Gopalakrishnan
Jay Gopalakrishnan is a scholar working on Molecular Biology, Cell Biology, Genetics, Genetics and Organic Chemistry, having authored 36 papers that have together received 1.2k indexed citations. Recurring topics across this work include Genetic and Kidney Cyst Diseases (14 papers), Microtubule and mitosis dynamics (14 papers), Epigenetics and DNA Methylation (5 papers), Protist diversity and phylogeny (5 papers), Renal and related cancers (4 papers), Pluripotent Stem Cells Research (4 papers), Hedgehog Signaling Pathway Studies (3 papers) and Neuroscience and Neural Engineering (2 papers). The work is most often cited by research in Cell Biology (537 citations), Developmental Neuroscience (72 citations), Molecular Biology (859 citations), Genetics (343 citations) and Genetics (82 citations). Jay Gopalakrishnan has collaborated with scholars based in Germany, United States and Italy. Frequent co-authors include Tomer Avidor‐Reiss, Elke Gabriel, Anand Ramani, Aruljothi Mariappan, Stéphanie Blachon, Daniela Nicastro, Roberto Pallini, Lucia Ricci‐Vitiani, Gladiola Goranci-Buzhala and Andrey Polyanovsky. Their work appears in journals such as Cell Reports, Nature Communications, Human Molecular Genetics, SLAS DISCOVERY and Journal of Visualized Experiments.
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.