J.L. Risler

1.4k total citations
25 papers, 1.2k citations indexed

About

J.L. Risler is a scholar working on Molecular Biology, Materials Chemistry and Genetics. According to data from OpenAlex, J.L. Risler has authored 25 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 8 papers in Materials Chemistry and 4 papers in Genetics. Recurrent topics in J.L. Risler's work include RNA and protein synthesis mechanisms (13 papers), Machine Learning in Bioinformatics (7 papers) and Enzyme Structure and Function (7 papers). J.L. Risler is often cited by papers focused on RNA and protein synthesis mechanisms (13 papers), Machine Learning in Bioinformatics (7 papers) and Enzyme Structure and Function (7 papers). J.L. Risler collaborates with scholars based in France, Japan and United States. J.L. Risler's co-authors include S. Brunie, C. Zelwer, Alain Hénaut, H. Delacroix, Marie-Odile Delorme, Claude Monteilhet, Jean‐Philippe Salier, Mark A. Rould, John J. Perona and Piotr P. Słonimski and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Molecular Biology.

In The Last Decade

J.L. Risler

25 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J.L. Risler France 17 1.0k 252 217 79 73 25 1.2k
Jean‐François Lefèvre France 22 1.0k 1.0× 157 0.6× 160 0.7× 79 1.0× 104 1.4× 45 1.3k
Nicholas M. Glykos Greece 18 926 0.9× 135 0.5× 300 1.4× 67 0.8× 51 0.7× 50 1.2k
C. Mark Fletcher United States 13 1.1k 1.0× 108 0.4× 115 0.5× 57 0.7× 129 1.8× 15 1.3k
Christian A.E.M. Spronk Netherlands 11 1.0k 1.0× 136 0.5× 293 1.4× 112 1.4× 69 0.9× 11 1.2k
Laurent Vuillard France 19 763 0.7× 103 0.4× 184 0.8× 92 1.2× 87 1.2× 33 1.2k
Xiubei Liao United States 21 1.1k 1.0× 183 0.7× 115 0.5× 86 1.1× 84 1.2× 32 1.3k
L. Reshetnikova Russia 14 1.8k 1.8× 424 1.7× 299 1.4× 87 1.1× 66 0.9× 31 2.0k
James G. Bann United States 20 730 0.7× 234 0.9× 117 0.5× 60 0.8× 71 1.0× 36 1.1k
Alexander I. Denesyuk Finland 22 790 0.8× 194 0.8× 222 1.0× 80 1.0× 205 2.8× 70 1.2k
A.E. Hodel United States 19 1.6k 1.5× 172 0.7× 273 1.3× 124 1.6× 88 1.2× 26 1.9k

Countries citing papers authored by J.L. Risler

Since Specialization
Citations

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

Fields of papers citing papers by J.L. Risler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.L. Risler. 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 J.L. Risler. The network helps show where J.L. Risler may publish in the future.

Co-authorship network of co-authors of J.L. Risler

This figure shows the co-authorship network connecting the top 25 collaborators of J.L. Risler. A scholar is included among the top collaborators of J.L. Risler 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 J.L. Risler. J.L. Risler 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.
Brézellec, Pierre, et al.. (2004). Cluster-C, an algorithm for the large-scale clustering of protein sequences based on the extraction of maximal cliques. Computational Biology and Chemistry. 28(3). 211–218. 31 indexed citations
2.
Devauchelle, Claudine, A. Großmann, Alain Hénaut, et al.. (2001). Rate Matrices for Analyzing Large Families of Protein Sequences. Journal of Computational Biology. 8(4). 381–399. 13 indexed citations
4.
Aude, Jean-Christophe, et al.. (1998). Evolution of Genes, Evolution of Species: The Case of Aminoacyl-tRNA Synthetases. Molecular Biology and Evolution. 15(11). 1548–1561. 40 indexed citations
5.
Olivier, Emmanuel, Maryvonne Daveau, Martine Hiron, et al.. (1998). The H4P Heavy Chain of Inter-α-inhibitor Family Largely Differs in the Structure and Synthesis of Its Prolin-Rich Region from Rat to Human. Biochemical and Biophysical Research Communications. 243(2). 522–530. 24 indexed citations
6.
Słonimski, Piotr P., Paweł Golik, Alain Hénaut, et al.. (1997). The First Laws of Genomics. Proceedings Genome Informatics Workshop/Genome informatics. 8(8). 9–10. 12 indexed citations
7.
Risler, J.L., et al.. (1996). Searching for a family of orphan sequences with SAMBA, a parallel hardware dedicated to biological applications. Biochimie. 78(5). 311–314. 2 indexed citations
8.
Perona, John J., S. Brunie, Mark A. Rould, et al.. (1995). A structure-based multiple sequence alignment of all class I aminoacyl-tRNA synthetases. Biochimie. 77(3). 194–203. 39 indexed citations
9.
Hénaut, Alain, et al.. (1995). Differential Codon Usage for Conserved Amino Acids: Evidence that the Serine Codons TCN were Primordial. Journal of Molecular Biology. 250(2). 123–127. 22 indexed citations
10.
Chan, Philippe, J.L. Risler, Gilda Raguénez, & Jean‐Philippe Salier. (1995). The three heavy-chain precursors for the inter-α-inhibitor family in mouse: new members of the multicopper oxidase protein group with differential transcription in liver and brain. Biochemical Journal. 306(2). 505–512. 48 indexed citations
11.
Goffeau, A., Piotr P. Słonimski, J.L. Risler, & Kenta Nakai. (1993). How many yeast genes code for membrane‐spanning proteins?. Yeast. 9(7). 691–702. 38 indexed citations
12.
Delacroix, H., T. Gulik‐Krzywicki, Paolo Mariani, & J.L. Risler. (1993). Freeze–fracture electron microscopy of lyotropic lipid systems Quantitative analysis of cubic phases of space group Ia3d (Q230). Liquid Crystals. 15(5). 605–625. 9 indexed citations
13.
Brouillet, Sophie, J.L. Risler, Alain Hénaut, & Piotr P. Słonimski. (1992). Evolutionary divergence plots of homologous proteins. Biochimie. 74(6). 571–580. 4 indexed citations
14.
Perona, John J., et al.. (1991). Structural similarities in glutaminyl- and methionyl-tRNA synthetases suggest a common overall orientation of tRNA binding.. Proceedings of the National Academy of Sciences. 88(7). 2903–2907. 61 indexed citations
15.
Brunie, S., C. Zelwer, & J.L. Risler. (1990). Crystallographic study at 2·5 Å resolution of the interaction of methionyl-tRNA synthetase from Escherichia coli with ATP. Journal of Molecular Biology. 216(2). 411–424. 200 indexed citations
16.
Risler, J.L., Marie-Odile Delorme, H. Delacroix, & Alain Hénaut. (1988). Amino acid substitutions in structurally related proteins a pattern recognition approach. Journal of Molecular Biology. 204(4). 1019–1029. 267 indexed citations
17.
Brouillet, Sophie, et al.. (1988). A comprehensive compilation of 400 nucleotide sequences coding for proteins from the yeast Saccharomyces cerevisiae = LISTA1. Current Genetics. 14(6). 529–535. 10 indexed citations
18.
Blow, D. M., Talapady N. Bhat, Alison Metcalfe, et al.. (1983). Structural homology in the amino-terminal domains of two aminoacyl-tRNA synthetases. Journal of Molecular Biology. 171(4). 571–576. 62 indexed citations
19.
Zelwer, C., J.L. Risler, & S. Brunie. (1982). Crystal structure of Escherichia coli methionyl-tRNA synthetase at 2.5 Å resolution. Journal of Molecular Biology. 155(1). 63–81. 126 indexed citations
20.
Risler, J.L., C. Zelwer, & S. Brunie. (1981). Methionyl-tRNA synthetase shows the nucleotide binding fold observed in dehydrogenases. Nature. 292(5821). 384–386. 62 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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