Charles E. Chapple

8.1k citations
11 papers · 1.6k indexed · 1 hit paper · h-index 10
Topics
Bioinformatics and Genomic Networks (5 papers)Selenium in Biological Systems (2 papers)Machine Learning in Bioinformatics (2 papers)
Partner nations
FranceSpainSwitzerland

In The Last Decade

Charles E. Chapple

11 papers receiving 1.6k citations

Hit Papers

VarSome: the human genomic variant search engine201820262020202320182505007501000

Peers

Charles E. Chapple
Comparison fields: 5 of 114
  • Molecular Biology 859
  • Genetics 494
  • Nutrition and Dietetics 176
  • Cancer Research 140
  • Oncology 117
Replace Claudia Gonzaga‐Jauregui with:
Claudia Gonzaga‐Jauregui United States
Rolf Jaggi Switzerland
Anatole Ghazalpour United States
Pekka Katajisto Finland
Junko Sasaki Japan
Remo Calabrese Italy
Jen-Yue Tsai United States
Rodolfo Iuliano Italy
David Valle‐García United States
Georges Siegenthaler Switzerland
Charles E. Chapple relative to Claudia Gonzaga‐Jauregui United States Claudia Gonzaga‐Jauregui's profile →
Citations per field
00.5×3.7×
Claudia Gonzaga‐Jauregui · 1×
Citations per year

Countries citing papers authored by Charles E. Chapple

Since Specialization
Citations

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

Fields of papers citing papers by Charles E. Chapple

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Charles E. Chapple. 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 Charles E. Chapple. The network helps show where Charles E. Chapple may publish in the future.

Co-authorship network of co-authors of Charles E. Chapple

This figure shows the co-authorship network connecting the top 25 collaborators of Charles E. Chapple. A scholar is included among the top collaborators of Charles E. Chapple 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 Charles E. Chapple. Charles E. Chapple is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

11 of 11 papers shown
#WorkIndexed citations
1
VarSome: the human genomic variant search enginebreakdown →
1140
2 10
3 6
4 74
5 35
6 99
7 32
8 30
9 53
10 53
11 81

About Charles E. Chapple

Charles E. Chapple is a scholar working on Molecular Biology, Nutrition and Dietetics and Computational Theory and Mathematics, having authored 11 papers that have together received 1.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (5 papers), Selenium in Biological Systems (2 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Genetics (494 citations), Molecular Biology (859 citations) and Nutrition and Dietetics (176 citations). Charles E. Chapple has collaborated with scholars based in France, Spain and Switzerland. Frequent co-authors include Richard J. Meyer, Andreas Massouras, Roderic Guigó, Christine Brun, E. Becker, Alain Guénoche, Alain Krol, Lionel Spinelli, Karine Gloux and Chaysavanh Manichanh. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

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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