Philippe Lamesch
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
- Plant Science top 2%
- Plant Molecular Biology Research
- Plant Stress Responses and Tolerance
Papers in
-
- Genomics and Phylogenetic Studies 6
- RNA and protein synthesis mechanisms 4
- CRISPR and Genetic Engineering 2
- Plant Gene Expression Analysis 1
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- GABA and Rice Research 2
- Plant nutrient uptake and metabolism 1
- Co-authors
- Kate Dreher (3 shared papers)Eva Huala (3 shared papers)David Swarbreck (2 shared papers)Rajkumar Sasidharan (2 shared papers)Donghui Li (2 shared papers)M. Garcia-Hernandez (2 shared papers)Tanya Berardini (2 shared papers)Christopher Wilks (1 shared paper)
- Journals
- Genome Research (3 papers)Human Molecular Genetics (2 papers)Current Protocols in Bioinformatics (1 paper)Nature Genetics (1 paper)Genomics (1 paper)
- Partner nations
- United StatesBelgiumUnited Kingdom
In The Last Decade
Philippe Lamesch
11 papers receiving 2.4k citations
Philippe Lamesch's Hit Papers
Peers
Comparison fields: 5 of 96
- Aging 212
- Plant Science 1.1k
- Molecular Biology 1.7k
- Horticulture 15
- Endocrinology 44
Countries citing papers authored by Philippe Lamesch
This map shows the geographic impact of Philippe Lamesch'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 Philippe Lamesch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Philippe Lamesch more than expected).
Fields of papers citing papers by Philippe Lamesch
This network shows the impact of papers produced by Philippe Lamesch. 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 Philippe Lamesch. The network helps show where Philippe Lamesch may publish in the future.
Co-authors
The 25 scholars most cited alongside Philippe Lamesch, 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 | The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools Hit paper breakdown → | 2011 | 1758 |
| 2 | 2007 | 210 | |
| 3 | 2004 | 143 | |
| 4 | 2001 | 138 | |
| 5 | 2004 | 91 | |
| 6 | 2005 | 38 | |
| 7 | 2010 | 28 | |
| 8 | 2006 | 24 | |
| 9 | 2013 | 7 | |
| 10 | 2006 | 2 | |
| 11 | 2002 | 1 |
About Philippe Lamesch
Philippe Lamesch is a scholar working on Molecular Biology, Plant Science, Aging, Genetics and Spectroscopy, having authored 11 papers that have together received 2.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (6 papers), RNA and protein synthesis mechanisms (4 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers), GABA and Rice Research (2 papers), CRISPR and Genetic Engineering (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Plant Gene Expression Analysis (1 paper) and Plant nutrient uptake and metabolism (1 paper). The work is most often cited by research in Aging (212 citations), Plant Science (1.1k citations), Molecular Biology (1.7k citations), Horticulture (15 citations) and Endocrinology (44 citations). Philippe Lamesch has collaborated with scholars based in United States, Belgium and United Kingdom. Frequent co-authors include Kate Dreher, Eva Huala, David Swarbreck, Rajkumar Sasidharan, Donghui Li, M. Garcia-Hernandez, Tanya Berardini, Christopher Wilks, Shanker K. Singh and Athikkattuvalasu S. Karthikeyan. Their work appears in journals such as Genome Research, Human Molecular Genetics, Current Protocols in Bioinformatics, Nature Genetics and Genomics.
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.