Michael Gribskov
- Molecular Biology top 0.5%
- Genomics and Phylogenetic Studies 23
- RNA and protein synthesis mechanisms 23
- Machine Learning in Bioinformatics 13
- Gene expression and cancer classification 11
- Bioinformatics and Genomic Networks 9
- Genomics and Chromatin Dynamics 8
- RNA Research and Splicing 8
- Genetics, Bioinformatics, and Biomedical Research 7
- Plant Science top 0.5%
- Aging top 2%
- Genetics top 1%
- Ecology top 2%
- Co-authors
- Trisha L. BaileyRichard R. BurgessDavid EisenbergA. McLachlanCarol A. GrossMichael A. LonettoNina L. RobinsonAlice Harmon
- Cited by
- Molecular BiologyPlant ScienceAging
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Nucleic Acids Research (5 papers)Nature Genetics (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Michael Gribskov
93 papers receiving 10.6k citations
Hit Papers
Peers
Comparison fields: 5 of 175
- Molecular Biology 7.4k
- Plant Science 3.6k
- Aging 152
- Genetics 1.5k
- Ecology 699
Countries citing papers authored by Michael Gribskov
This map shows the geographic impact of Michael Gribskov'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 Michael Gribskov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Gribskov more than expected).
Fields of papers citing papers by Michael Gribskov
This network shows the impact of papers produced by Michael Gribskov. 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 Michael Gribskov. The network helps show where Michael Gribskov may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael Gribskov, 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 | 2020 | 3 | |
| 2 | 2020 | 5 | |
| 3 | 2019 | 44 | |
| 4 | 2016 | 5 | |
| 5 | 2014 | 12 | |
| 6 | 2011 | 76 | |
| 7 | 2008 | 7 | |
| 8 | 2006 | 40 | |
| 9 | 2006 | 115 | |
| 10 | 2005 | 2 | |
| 11 | Genome Informatics 2003 | 2003 | 1 |
| 12 | 2003 | 1 | |
| 13 | 2001 | 14 | |
| 14 | 2001 | 101 | |
| 15 | 1999 | 6 | |
| 16 | Combining evidence using p-values: application to sequence homology searches.breakdown → | 1998 | 963 |
| 17 | 1997 | 48 | |
| 18 | 1996 | 67 | |
| 19 | 1996 | 380 | |
| 20 | 1988 | 47 |
About Michael Gribskov
Michael Gribskov is a scholar working on Molecular Biology, Horticulture and Information Systems and Management, having authored 94 papers that have together received 10.9k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (23 papers), RNA and protein synthesis mechanisms (23 papers), Machine Learning in Bioinformatics (13 papers), Gene expression and cancer classification (11 papers), Bioinformatics and Genomic Networks (9 papers), Genomics and Chromatin Dynamics (8 papers), RNA Research and Splicing (8 papers) and Genetics, Bioinformatics, and Biomedical Research (7 papers). The work is most often cited by research in Molecular Biology (7.4k citations), Plant Science (3.6k citations) and Aging (152 citations). Michael Gribskov has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Trisha L. Bailey, Richard R. Burgess, David Eisenberg, A. McLachlan, Carol A. Gross, Michael A. Lonetto, Nina L. Robinson, Alice Harmon, Jeffrey F. Harper and David Eisenberg. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Genetics.
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.