Éric Rivals

4.4k total citations · 1 hit paper
78 papers, 2.3k citations indexed

About

Éric Rivals is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Éric Rivals has authored 78 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Molecular Biology, 30 papers in Artificial Intelligence and 18 papers in Genetics. Recurrent topics in Éric Rivals's work include Genomics and Phylogenetic Studies (33 papers), Algorithms and Data Compression (30 papers) and RNA and protein synthesis mechanisms (19 papers). Éric Rivals is often cited by papers focused on Genomics and Phylogenetic Studies (33 papers), Algorithms and Data Compression (30 papers) and RNA and protein synthesis mechanisms (19 papers). Éric Rivals collaborates with scholars based in France, Germany and United States. Éric Rivals's co-authors include Leena Salmela, Philippe Jarne, S. Leclercq, Max Dauchet, Jean‐Paul Delahaye, François Nicolas, Thérèse Commes, Sabine Laurent‐Chabalier, Olivier Ganier and Philippe Coulombe and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Bioinformatics.

In The Last Decade

Éric Rivals

78 papers receiving 2.3k citations

Hit Papers

LoRDEC: accurate and efficient long read error correction 2014 2026 2018 2022 2014 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. LoRDEC: accurate and efficient long read error correction
    2014 520 citations Leena Salmela, Éric Rivals Bioinformatics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Éric Rivals France 23 1.8k 531 394 362 232 78 2.3k
Rayan Chikhi France 26 1.8k 1.0× 661 1.2× 364 0.9× 414 1.1× 471 2.0× 63 2.5k
Paul Medvedev United States 22 1.6k 0.9× 574 1.1× 311 0.8× 787 2.2× 249 1.1× 75 2.3k
Rasko Leinonen United Kingdom 9 2.4k 1.3× 475 0.9× 227 0.6× 501 1.4× 325 1.4× 11 3.3k
Petri Törönen Finland 19 1.5k 0.8× 543 1.0× 153 0.4× 189 0.5× 207 0.9× 40 2.3k
Kengo Sato Japan 22 2.2k 1.2× 346 0.7× 131 0.3× 303 0.8× 303 1.3× 64 2.7k
Patrik D’haeseleer United States 30 2.4k 1.4× 230 0.4× 424 1.1× 222 0.6× 333 1.4× 43 3.5k
Hideo Matsuda Japan 22 1.6k 0.9× 258 0.5× 150 0.4× 483 1.3× 550 2.4× 139 2.8k
Nomi L. Harris United States 18 1.7k 0.9× 304 0.6× 171 0.4× 494 1.4× 102 0.4× 44 2.4k
Knut Reinert Germany 37 3.9k 2.2× 844 1.6× 504 1.3× 1.0k 2.8× 291 1.3× 124 5.0k
Erik Garrison United States 21 1.5k 0.8× 773 1.5× 169 0.4× 865 2.4× 129 0.6× 39 2.2k

Countries citing papers authored by Éric Rivals

Since Specialization
Citations

This map shows the geographic impact of Éric Rivals'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 Éric Rivals with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Éric Rivals more than expected).

Fields of papers citing papers by Éric Rivals

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Éric Rivals. 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 Éric Rivals. The network helps show where Éric Rivals may publish in the future.

Co-authorship network of co-authors of Éric Rivals

This figure shows the co-authorship network connecting the top 25 collaborators of Éric Rivals. A scholar is included among the top collaborators of Éric Rivals based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Éric Rivals. Éric Rivals is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Linard, Benjamin, et al.. (2023). Computing Phylo-k-Mers. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 20(5). 2889–2897. 1 indexed citations
2.
Linard, Benjamin, et al.. (2023). EPIK: precise and scalable evolutionary placement with informativek-mers. Bioinformatics. 39(12). 3 indexed citations
3.
Ripoll, Julie, et al.. (2023). dipwmsearch: a Python package for searching di-PWM motifs. Bioinformatics. 39(4). 1 indexed citations
4.
Linard, Benjamin, et al.. (2020). Rapid screening and detection of inter-type viral recombinants using phylo- k -mers. Bioinformatics. 36(22-23). 5351–5360. 3 indexed citations
5.
Rivals, Éric, et al.. (2018). Practical lower and upper bounds for the Shortest Linear Superstring. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics). 1 indexed citations
6.
Baaijens, Jasmijn A., Amal Zine El Aabidine, Éric Rivals, & Alexander Schönhuth. (2017). De novo assembly of viral quasispecies using overlap graphs. Genome Research. 27(5). 835–848. 58 indexed citations
7.
Bras, Yvan Le, Olivier Collin, Vincent Lacroix, et al.. (2016). Colib'read on galaxy: a tools suite dedicated to biological information extraction from raw NGS reads. GigaScience. 5(1). 9–9. 3 indexed citations
8.
Limasset, Antoine, et al.. (2016). Read mapping on de Bruijn graphs. BMC Bioinformatics. 17(1). 237–237. 41 indexed citations
9.
Rivals, Éric, et al.. (2015). The power of greedy algorithms for approximating Max-ATSP, Cyclic Cover, and superstrings. Discrete Applied Mathematics. 212. 48–60. 4 indexed citations
10.
Rivals, Éric, et al.. (2014). Reverse engineering of compact suffix trees and links: A novel algorithm. Journal of Discrete Algorithms. 28. 9–22. 11 indexed citations
11.
Rivals, Éric, et al.. (2014). 3-Shortest Superstring is 2-approximable by a greedy algorithm. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
12.
Philippe, Nicolas, Anthony Boureux, Qiang Baï, et al.. (2013). Combining DGE and RNA-sequencing data to identify new polyA+ non-coding transcripts in the human genome. Nucleic Acids Research. 42(5). 2820–2832. 12 indexed citations
13.
Cayrou, Christelle, Philippe Coulombe, Slavica Stanojčić, et al.. (2011). Genome-scale analysis of metazoan replication origins reveals their organization in specific but flexible sites defined by conserved features. Genome Research. 21(9). 1438–1449. 258 indexed citations
14.
Uricaru, Raluca, et al.. (2011). An alternative approach to multiple genome comparison. Nucleic Acids Research. 39(15). e101–e101. 5 indexed citations
15.
Adebiyi, Ezekiel & Éric Rivals. (2007). Detection of Recombination in Variable Number Tandem Repeat Sequences. Covenant University Repository (Covenant University). 2 indexed citations
16.
Nicolas, François & Éric Rivals. (2007). Hardness of optimal spaced seed design. Journal of Computer and System Sciences. 74(5). 831–849. 14 indexed citations
17.
Rivals, Éric, Anthony Boureux, Florence Ottonès, et al.. (2007). Transcriptome annotation using tandem SAGE tags. Nucleic Acids Research. 35(17). e108–e108. 19 indexed citations
18.
Rivals, Éric, et al.. (2004). STAR: an algorithm to Search for Tandem Approximate Repeats. Bioinformatics. 20(16). 2812–2820. 72 indexed citations
19.
Varré, Jean‐Stéphane, Jean‐Paul Delahaye, & Éric Rivals. (1997). The Transformation Distance. Proceedings Genome Informatics Workshop/Genome informatics. 8. 352–353. 2 indexed citations
20.
Rivals, Éric, Jean‐Paul Delahaye, Max Dauchet, et al.. (1997). Detection of significant patterns by compression algorithms: the case of approximate tandem repeats in DNA sequences. Computer applications in the biosciences. 13(2). 131–136. 35 indexed citations

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.

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