Sophie Schbath

2.1k citations
44 papers · 1.4k indexed · h-index 20
Topics
Genomics and Phylogenetic Studies (15 papers)RNA and protein synthesis mechanisms (15 papers)Algorithms and Data Compression (10 papers)
Journals
CellSHILAP Revista de lepidopterologíaBioinformatics
Partner nations
FranceMoroccoNiger

In The Last Decade

Sophie Schbath

42 papers receiving 1.3k citations

Peers

Sophie Schbath
Comparison fields: 5 of 96
  • Molecular Biology 1.0k
  • Genetics 413
  • Ecology 294
  • Artificial Intelligence 288
  • Plant Science 98
Replace Marie-France Sagot with:
Marie-France Sagot France
Tetsuhiro Ogawa Japan
Alain Hénaut France
Alain Schenkel Switzerland
B. Edwin Blaisdell United States
Antti Honkela Finland
Heladia Salgado Mexico
Michael Brown United States
Mei‐Hui Wang Taiwan
Alberto Policriti Italy
Sophie Schbath relative to Marie-France Sagot France Marie-France Sagot's profile →
Citations per field
00.5×1.5×2.3×
Marie-France Sagot · 1×
Citations per year

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
#WorkIndexed citations
1 5
2 0
3 6
4 1
5 1
6 9
7 2
8 8
9 53
10 1
11 10
12 44
13 19
14 24
15 13
16 24
17 1
18 61
19 6
20 75

About Sophie Schbath

Sophie Schbath is a scholar working on Molecular Biology, Artificial Intelligence and Genetics, having authored 44 papers that have together received 1.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (15 papers), RNA and protein synthesis mechanisms (15 papers) and Algorithms and Data Compression (10 papers). The work is most often cited by research in Molecular Biology (1.0k citations), Genetics (413 citations) and Endocrinology (67 citations). Sophie Schbath has collaborated with scholars based in France, Morocco and Niger. Frequent co-authors include Gesine Reinert, Meriem El Karoui, Michael S. Waterman, Marie‐Agnès Petit, Stephane S. Robin, Stéphane Robin, Frédéric Boccard, Olivier Espéli, Romain Mercier and Bernard Prum. Their work appears in journals such as Cell, SHILAP Revista de lepidopterología 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.

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