Stan Letovsky

3.2k citations
15 papers · 1.1k · h-index 9

Impact in

  • Software top 5%
    • Bioinformatics and Genomic Networks
    • RNA modifications and cancer
    • Genomics and Chromatin Dynamics
    • RNA Research and Splicing
    • RNA and protein synthesis mechanisms
    • Genomics and Phylogenetic Studies

Papers in

    • RNA and protein synthesis mechanisms 3
    • Gene expression and cancer classification 2
    • Bioinformatics and Genomic Networks 2
    • Molecular Biology Techniques and Applications 2

Stan Letovsky

13 papers receiving 1.1k citations

Peers

Stan Letovsky
Comparison fields: 5 of 101
  • Software 71
  • Molecular Biology 786
  • Cancer Research 121
  • Information Systems 160
  • Computer Science Applications 34
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Citations per field
00.5×3.0×
Yimeng Dou · 1×
Citations per year

Countries citing papers authored by Stan Letovsky

Since Specialization
Citations

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

Fields of papers citing papers by Stan Letovsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Stan Letovsky, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Stan Letovsky Line = papers co-authored together Stan Letovsky links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 2011409
2 2004251
3 1988160
4 2009148
5 201173
6 200928
7 201018
8
Strategies for documenting delocalized plans
198611
9 20119
10 20235
11
Studying software documentation from a cognitive perspective: A status report
19864
12 19922
13 20211
14 19971
15
Panel: scientific data management for human genome applications
19900

About Stan Letovsky

Stan Letovsky is a scholar working on Molecular Biology, Artificial Intelligence, Infectious Diseases, Plant Science and Computer Networks and Communications, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (3 papers), SARS-CoV-2 detection and testing (2 papers), Gene expression and cancer classification (2 papers), Chromosomal and Genetic Variations (2 papers), Bioinformatics and Genomic Networks (2 papers), COVID-19 Clinical Research Studies (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers) and Molecular Biology Techniques and Applications (2 papers). The work is most often cited by research in Software (71 citations), Molecular Biology (786 citations), Cancer Research (121 citations), Information Systems (160 citations) and Computer Science Applications (34 citations). Stan Letovsky has collaborated with scholars based in United States, Singapore and Israel. Frequent co-authors include Doron Lipson, Simon Kasif, T. M. Murali, Charles R. Cantor, Chunming Ding, Ulaş Karaöz, Yu Zheng, Jeannine Pinto, Elliot Soloway and David Littman. Their work appears in journals such as PLoS ONE, Nature Biotechnology, Frontiers in Public Health, Trends in Genetics and Communications of the ACM.

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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