Mathieu Giraud
Impact in
- Sensory Systems top 5%
- Olfactory and Sensory Function Studies
Papers in
-
- Genomics and Phylogenetic Studies 10
- RNA and protein synthesis mechanisms 8
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- Algorithms and Data Compression 15
- Co-authors
- Mikaël Salson (9 shared papers)Maud Rimbault (1 shared paper)Patricia Lavigne (1 shared paper)Emmanuelle Morin (1 shared paper)Kerstin Lindblad‐Toh (1 shared paper)Pascale Quignon (1 shared paper)Sandrine Tacher (1 shared paper)Francis Galibert (1 shared paper)
- Journals
- Information and Computation (2 papers)Journal of Computational Biology (2 papers)Parallel Computing (2 papers)Lecture notes in computer science (10 papers)Bioinformatics (1 paper)
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
Mathieu Giraud
46 papers receiving 562 citations
Peers
Comparison fields: 5 of 104
- Sensory Systems 86
- Genetics 46
- Signal Processing 51
- Hepatology 30
- Nutrition and Dietetics 59
Countries citing papers authored by Mathieu Giraud
This map shows the geographic impact of Mathieu Giraud'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 Mathieu Giraud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mathieu Giraud more than expected).
Fields of papers citing papers by Mathieu Giraud
This network shows the impact of papers produced by Mathieu Giraud. 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 Mathieu Giraud. The network helps show where Mathieu Giraud may publish in the future.
Co-authors
The 25 scholars most cited alongside Mathieu Giraud, 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 51 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2005 | 130 | |
| 2 | 2016 | 55 | |
| 3 | 2017 | 48 | |
| 4 | 2014 | 48 | |
| 5 | 2008 | 31 | |
| 6 | 2008 | 27 | |
| 7 | 2010 | 25 | |
| 8 | 2016 | 18 | |
| 9 | 2016 | 15 | |
| 10 | 2021 | 15 | |
| 11 | 2020 | 15 | |
| 12 | 1981 | 11 | |
| 13 | 2005 | 11 | |
| 14 | 2006 | 9 | |
| 15 | 2008 | 9 | |
| 16 | 2015 | 8 | |
| 17 | 2012 | 8 | |
| 18 | 2019 | 7 | |
| 19 | 2010 | 7 | |
| 20 | 2018 | 6 |
About Mathieu Giraud
Mathieu Giraud is a scholar working on Molecular Biology, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing and Cognitive Neuroscience, having authored 51 papers that have together received 583 indexed citations. Recurring topics across this work include Algorithms and Data Compression (15 papers), Music and Audio Processing (10 papers), Genomics and Phylogenetic Studies (10 papers), Music Technology and Sound Studies (9 papers), RNA and protein synthesis mechanisms (8 papers), Neuroscience and Music Perception (6 papers), Lymphoma Diagnosis and Treatment (5 papers) and Acute Lymphoblastic Leukemia research (4 papers). The work is most often cited by research in Sensory Systems (86 citations), Genetics (46 citations), Signal Processing (51 citations), Hepatology (30 citations) and Nutrition and Dietetics (59 citations). Mathieu Giraud has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Mikaël Salson, Maud Rimbault, Patricia Lavigne, Emmanuelle Morin, Kerstin Lindblad‐Toh, Pascale Quignon, Sandrine Tacher, Francis Galibert, Jacques Nicolas and Robert Giegerich. Their work appears in journals such as Information and Computation, Journal of Computational Biology, Parallel Computing, Lecture notes in computer science and Bioinformatics.
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.