Igor A. Gak
Impact in
- Cell Biology top 5%
- Microtubule and mitosis dynamics
- Molecular Biology top 10%
- RNA Research and Splicing
- Bioinformatics and Genomic Networks
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- Ubiquitin and proteasome pathways
- Genomics and Chromatin Dynamics
Papers in
-
- Bioinformatics and Genomic Networks 1
- Protein Degradation and Inhibitors 1
- Microbial Metabolic Engineering and Bioproduction 1
- Protein Structure and Dynamics 1
- Oncology 2
- Cancer-related Molecular Pathways 2
- Co-authors
- Jörg Mansfeld (3 shared papers)Yusuke Toyoda (1 shared paper)Ina Poser (1 shared paper)Matthias Mann (1 shared paper)Nina C. Hubner (1 shared paper)Nagarjuna Nagaraj (1 shared paper)Jürgen Cox (1 shared paper)Frank Buchholz (1 shared paper)
- Journals
- Cell (1 paper)Biochimica et Biophysica Acta (BBA) - Molecular Cell Research (1 paper)Nature Communications (1 paper)Cell Reports (1 paper)
- Partner nations
- GermanySerbiaUnited Kingdom
In The Last Decade
Igor A. Gak
4 papers receiving 1.1k citations
Igor A. Gak's Hit Papers
Peers
Comparison fields: 5 of 92
- Cell Biology 275
- Molecular Biology 892
- Aging 16
- Biophysics 43
- Spectroscopy 123
Countries citing papers authored by Igor A. Gak
This map shows the geographic impact of Igor A. Gak'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 Igor A. Gak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor A. Gak more than expected).
Fields of papers citing papers by Igor A. Gak
This network shows the impact of papers produced by Igor A. Gak. 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 Igor A. Gak. The network helps show where Igor A. Gak may publish in the future.
Co-authors
The 23 scholars most cited alongside Igor A. Gak, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances Hit paper breakdown → | 2015 | 905 |
| 2 | 2017 | 96 | |
| 3 | 2015 | 32 | |
| 4 | 2018 | 27 |
About Igor A. Gak
Igor A. Gak is a scholar working on Molecular Biology, Oncology, Behavioral Neuroscience, Endocrinology, Diabetes and Metabolism and Physiology, having authored 4 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cancer-related Molecular Pathways (2 papers), Bioinformatics and Genomic Networks (1 paper), Protein Degradation and Inhibitors (1 paper), Cell Image Analysis Techniques (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper), Protein Structure and Dynamics (1 paper), Hormonal Regulation and Hypertension (1 paper) and Stress Responses and Cortisol (1 paper). The work is most often cited by research in Cell Biology (275 citations), Molecular Biology (892 citations), Aging (16 citations), Biophysics (43 citations) and Spectroscopy (123 citations). Igor A. Gak has collaborated with scholars based in Germany, Serbia and United Kingdom. Frequent co-authors include Jörg Mansfeld, Yusuke Toyoda, Ina Poser, Matthias Mann, Nina C. Hubner, Nagarjuna Nagaraj, Jürgen Cox, Frank Buchholz, Anthony A. Hyman and Marco Y. Hein. Their work appears in journals such as Cell, Biochimica et Biophysica Acta (BBA) - Molecular Cell Research, Nature Communications and Cell Reports.
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.