Eric Viara
Impact in
- Molecular Biology top 5%
- Genomics and Chromatin Dynamics
- Genomics and Phylogenetic Studies
- Bioinformatics and Genomic Networks
- RNA Research and Splicing
- Gene Regulatory Network Analysis
- Epigenetics and DNA Methylation
- Microbial Metabolic Engineering and Bioproduction
- Plant Science top 5%
- Chromosomal and Genetic Variations
Papers in
-
- Bioinformatics and Genomic Networks 8
- Gene Regulatory Network Analysis 6
- Gene expression and cancer classification 4
- Microbial Metabolic Engineering and Bioproduction 3
- Genomics and Phylogenetic Studies 2
- Co-authors
- Emmanuel Barillot (15 shared papers)Jean‐Philippe Vert (2 shared papers)Édith Heard (1 shared paper)Bryan R. Lajoie (1 shared paper)Job Dekker (1 shared paper)Nicolas Servant (1 shared paper)Nelle Varoquaux (1 shared paper)Laurence Calzone (8 shared papers)
In The Last Decade
Eric Viara
16 papers receiving 1.9k citations
Eric Viara's Hit Papers
Peers
Comparison fields: 5 of 108
- Molecular Biology 1.6k
- Plant Science 575
- Genetics 363
- Cancer Research 136
- Modeling and Simulation 33
Countries citing papers authored by Eric Viara
This map shows the geographic impact of Eric Viara'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 Eric Viara with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Viara more than expected).
Fields of papers citing papers by Eric Viara
This network shows the impact of papers produced by Eric Viara. 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 Eric Viara. The network helps show where Eric Viara may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric Viara, 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 | HiC-Pro: an optimized and flexible pipeline for Hi-C data processing Hit paper breakdown → | 2015 | 1422 |
| 2 | 2012 | 88 | |
| 3 | 2015 | 86 | |
| 4 | 2017 | 74 | |
| 5 | 2007 | 71 | |
| 6 | 2006 | 66 | |
| 7 | 2013 | 36 | |
| 8 | 2006 | 28 | |
| 9 | 2015 | 25 | |
| 10 | 2017 | 8 | |
| 11 | 2022 | 6 | |
| 12 | 1999 | 5 | |
| 13 | 2015 | 5 | |
| 14 | 1998 | 5 | |
| 15 | 2021 | 3 | |
| 16 | 2003 | 3 |
About Eric Viara
Eric Viara is a scholar working on Molecular Biology, Artificial Intelligence, Computational Theory and Mathematics, Genetics and Plant Science, having authored 16 papers that have together received 1.9k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (8 papers), Gene Regulatory Network Analysis (6 papers), Gene expression and cancer classification (4 papers), Microbial Metabolic Engineering and Bioproduction (3 papers), Computational Drug Discovery Methods (2 papers), Genomics and Phylogenetic Studies (2 papers), Mathematical Biology Tumor Growth (2 papers) and Chromosomal and Genetic Variations (2 papers). The work is most often cited by research in Molecular Biology (1.6k citations), Plant Science (575 citations), Genetics (363 citations), Cancer Research (136 citations) and Modeling and Simulation (33 citations). Eric Viara has collaborated with scholars based in France, Sweden and China. Frequent co-authors include Emmanuel Barillot, Jean‐Philippe Vert, Édith Heard, Bryan R. Lajoie, Job Dekker, Nicolas Servant, Nelle Varoquaux, Laurence Calzone, Andreï Zinovyev and Gautier Stoll. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, Frontiers in Molecular Biosciences, BMC Systems Biology and Oncogenesis.
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.