Sophie Schbath

2.1k total citations
44 papers, 1.4k citations indexed

About

Sophie Schbath is a scholar working on Molecular Biology, Artificial Intelligence and Genetics. According to data from OpenAlex, Sophie Schbath has authored 44 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 13 papers in Artificial Intelligence and 10 papers in Genetics. Recurrent topics in Sophie Schbath's work include Genomics and Phylogenetic Studies (15 papers), RNA and protein synthesis mechanisms (15 papers) and Algorithms and Data Compression (10 papers). Sophie Schbath is often cited by papers focused on Genomics and Phylogenetic Studies (15 papers), RNA and protein synthesis mechanisms (15 papers) and Algorithms and Data Compression (10 papers). Sophie Schbath collaborates with scholars based in France, Morocco and Niger. Sophie Schbath's co-authors include Gesine Reinert, Meriem El Karoui, Michael S. Waterman, Marie‐Agnès Petit, Stéphane Robin, Stephane S. Robin, Romain Mercier, Frédéric Boccard, Olivier Espéli and Élisabeth de Turckheim and has published in prestigious journals such as Cell, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Sophie Schbath

42 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sophie Schbath France 20 1.0k 413 294 288 98 44 1.4k
Marie-France Sagot France 18 1.0k 1.0× 176 0.4× 147 0.5× 206 0.7× 209 2.1× 57 1.4k
Tetsuhiro Ogawa Japan 18 675 0.6× 222 0.5× 149 0.5× 209 0.7× 72 0.7× 46 1.1k
Alain Hénaut France 20 1.4k 1.4× 517 1.3× 240 0.8× 83 0.3× 172 1.8× 67 1.9k
Alain Schenkel Switzerland 6 778 0.7× 157 0.4× 90 0.3× 33 0.1× 49 0.5× 7 1.2k
B. Edwin Blaisdell United States 22 1.2k 1.2× 215 0.5× 155 0.5× 123 0.4× 152 1.6× 37 1.7k
Kevin Chen United States 10 455 0.4× 126 0.3× 131 0.4× 505 1.8× 191 1.9× 13 1.7k
Nic M. Vega United States 11 1.5k 1.4× 420 1.0× 203 0.7× 84 0.3× 112 1.1× 27 2.0k
Heladia Salgado Mexico 21 2.2k 2.1× 1.1k 2.6× 332 1.1× 64 0.2× 176 1.8× 39 2.6k
Antti Honkela Finland 19 521 0.5× 135 0.3× 45 0.2× 263 0.9× 43 0.4× 61 1.0k
Michael Brown United States 9 1.4k 1.4× 177 0.4× 79 0.3× 413 1.4× 195 2.0× 10 2.0k

Countries citing papers authored by Sophie Schbath

Since Specialization
Citations

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

Fields of papers citing papers by Sophie Schbath

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sophie Schbath

This figure shows the co-authorship network connecting the top 25 collaborators of Sophie Schbath. A scholar is included among the top collaborators of Sophie Schbath 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 Sophie Schbath. Sophie Schbath 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.
Mariadassou, Mahendra, Laurent‐Xavier Nouvel, Fabienne Constant, et al.. (2023). Microbiota members from body sites of dairy cows are largely shared within individual hosts throughout lactation but sharing is limited in the herd. SHILAP Revista de lepidopterología. 5(1). 32–32. 5 indexed citations
2.
Aubert, Julie, Sophie Schbath, & Stéphane Robin. (2021). Model‐based biclustering for overdispersed count data with application in microbial ecology. Methods in Ecology and Evolution. 12(6). 1050–1061.
3.
Bize, Ariane, Cédric Midoux, Mahendra Mariadassou, et al.. (2021). Exploring short k-mer profiles in cells and mobile elements from Archaea highlights the major influence of both the ecological niche and evolutionary history. BMC Genomics. 22(1). 186–186. 6 indexed citations
4.
5.
Fromion, Vincent, et al.. (2020). Statistical modelling of bacterial promoter sequences for regulatory motif discovery with the help of transcriptome data: application to Listeria monocytogenes. Journal of The Royal Society Interface. 17(171). 20200600–20200600. 1 indexed citations
6.
Benoit, Gaëtan, Mahendra Mariadassou, Stéphane Robin, et al.. (2019). SimkaMin: fast and resource frugal de novo comparative metagenomics. Bioinformatics. 36(4). 1275–1276. 9 indexed citations
7.
Sheinman, Michael, et al.. (2016). Comparing the Statistical Fate of Paralogous and Orthologous Sequences. Genetics. 204(2). 475–482. 2 indexed citations
8.
Benoit, Gaëtan, Pierre Peterlongo, Mahendra Mariadassou, et al.. (2016). Multiple comparative metagenomics using multiset k -mer counting. PeerJ Computer Science. 2. e94–e94. 63 indexed citations
9.
Schbath, Sophie, et al.. (2012). Mapping Reads on a Genomic Sequence: An Algorithmic Overview and a Practical Comparative Analysis. Journal of Computational Biology. 19(6). 796–813. 53 indexed citations
10.
Devillers, Hugo & Sophie Schbath. (2011). Separating Significant Matches from Spurious Matches in DNA Sequences. Journal of Computational Biology. 19(1). 1–12. 10 indexed citations
11.
Launay, Guillaume, et al.. (2011). Statistical Significance of Threading Scores. Journal of Computational Biology. 19(1). 13–29. 1 indexed citations
12.
Touzain, Fabrice, Marie‐Agnès Petit, Sophie Schbath, & Meriem El Karoui. (2010). DNA motifs that sculpt the bacterial chromosome. Nature Reviews Microbiology. 9(1). 15–26. 44 indexed citations
13.
Schbath, Sophie, Vincent Lacroix, & Marie-France Sagot. (2009). Assessing the Exceptionality of Coloured Motifs in Networks. 2009(1). 616234–616234. 16 indexed citations
14.
Robin, Stéphane, et al.. (2007). Statistical tests to compare motif count exceptionalities. BMC Bioinformatics. 8(1). 84–84. 24 indexed citations
15.
Roquain, Étienne & Sophie Schbath. (2007). Improved compound Poisson approximation for the number of occurrences of any rare word family in a stationary markov chain. Advances in Applied Probability. 39(1). 128–140. 19 indexed citations
16.
Stefanov, Valeri T., Stephane S. Robin, & Sophie Schbath. (2006). Waiting times for clumps of patterns and for structured motifs in random sequences. Discrete Applied Mathematics. 155(6-7). 868–880. 13 indexed citations
17.
Gusto, Gaëlle & Sophie Schbath. (2005). FADO: A Statistical Method to Detect Favored or Avoided Distances between Occurrences of Motifs using the Hawkes' Model. Statistical Applications in Genetics and Molecular Biology. 4(1). Article24–Article24. 24 indexed citations
18.
Schbath, Sophie. (2002). Compound Poisson approximation of word counts in DNA sequences. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
19.
Karoui, Meriem El, et al.. (1999). Characteristics of Chi distribution on different bacterial genomes. Research in Microbiology. 150(9-10). 579–587. 65 indexed citations
20.
Schbath, Sophie. (1997). Coverage Processes in Physical Mapping by Anchoring Random Clones. Journal of Computational Biology. 4(1). 61–82. 6 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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