Stephen Larson

1.5k total citations
32 papers, 841 citations indexed

About

Stephen Larson is a scholar working on Molecular Biology, Artificial Intelligence and Aging. According to data from OpenAlex, Stephen Larson has authored 32 papers receiving a total of 841 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Artificial Intelligence and 7 papers in Aging. Recurrent topics in Stephen Larson's work include Biomedical Text Mining and Ontologies (12 papers), Genetics, Aging, and Longevity in Model Organisms (7 papers) and Semantic Web and Ontologies (7 papers). Stephen Larson is often cited by papers focused on Biomedical Text Mining and Ontologies (12 papers), Genetics, Aging, and Longevity in Model Organisms (7 papers) and Semantic Web and Ontologies (7 papers). Stephen Larson collaborates with scholars based in United States, United Kingdom and Russia. Stephen Larson's co-authors include Maryann E. Martone, Andrey Palyanov, Hooman Hefzi, Sulagna Ghosh, Kristin K. Baldwin, Tyler Cutforth, Amarnath Gupta, Padraig Gleeson, Jeffrey S. Grethe and Michael Currie and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Philosophical Transactions of the Royal Society B Biological Sciences.

In The Last Decade

Stephen Larson

31 papers receiving 811 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephen Larson United States 15 317 189 159 158 149 32 841
Thomas M. Morse United States 14 472 1.5× 693 3.7× 119 0.7× 629 4.0× 59 0.4× 27 1.7k
Andrew P. Davison France 18 227 0.7× 481 2.5× 217 1.4× 831 5.3× 98 0.7× 47 1.5k
Youngser Park United States 13 156 0.5× 382 2.0× 274 1.7× 210 1.3× 32 0.2× 36 1.2k
Nathan W. Gouwens United States 11 275 0.9× 724 3.8× 58 0.4× 483 3.1× 160 1.1× 15 1.1k
Inbal Ayzenshtat United States 14 710 2.2× 664 3.5× 117 0.7× 780 4.9× 55 0.4× 15 1.9k
Robert A. A. Campbell United States 19 188 0.6× 407 2.2× 18 0.1× 316 2.0× 108 0.7× 36 1.1k
Manuel Berning Germany 9 107 0.3× 247 1.3× 18 0.1× 161 1.0× 161 1.1× 9 648
Louis K. Scheffer United States 15 129 0.4× 331 1.8× 26 0.2× 150 0.9× 10 0.1× 36 1.0k
Ingrid Andrade United States 6 102 0.3× 417 2.2× 30 0.2× 130 0.8× 33 0.2× 7 594
Bruce Graham United Kingdom 23 407 1.3× 922 4.9× 189 1.2× 758 4.8× 134 0.9× 67 1.7k

Countries citing papers authored by Stephen Larson

Since Specialization
Citations

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

Fields of papers citing papers by Stephen Larson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephen Larson

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Larson. A scholar is included among the top collaborators of Stephen Larson 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 Stephen Larson. Stephen Larson 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.
Larson, Stephen, et al.. (2021). Effects of trypanocidal drugs on DNA synthesis: new insights into melarsoprol growth inhibition. Parasitology. 148(10). 1143–1150. 3 indexed citations
2.
Gomez, Stephanie, Stephen Larson, Eugenia Silva‐Herzog, et al.. (2020). A Trypanosoma brucei ORFeome-Based Gain-of-Function Library Identifies Genes That Promote Survival during Melarsoprol Treatment. mSphere. 5(5). 14 indexed citations
3.
Sarma, Gopal, Bradly Alicea, Matteo Cantarelli, et al.. (2018). OpenWorm: overview and recent advances in integrative biological simulation of Caenorhabditis elegans. Philosophical Transactions of the Royal Society B Biological Sciences. 373(1758). 20170382–20170382. 46 indexed citations
4.
Szigeti, Balázs, Padraig Gleeson, M.C. Vella, et al.. (2014). OpenWorm: an open-science approach to modeling Caenorhabditis elegans. Frontiers in Computational Neuroscience. 8. 137–137. 78 indexed citations
5.
Larson, Stephen. (2014). The Basics of Digital Forensics: The Primer for Getting Started in Digital Forensics. ˜The œjournal of digital forensics, security and law. 11 indexed citations
6.
Larson, Stephen & Maryann E. Martone. (2013). NeuroLex.org: an online framework for neuroscience knowledge. Frontiers in Neuroinformatics. 7. 18–18. 47 indexed citations
7.
Larson, Stephen & Junko Yamamoto. (2013). Flipping the College Spreadsheet Skills Classroom: Initial Empirical Results. 18 indexed citations
8.
Larson, Stephen, et al.. (2012). Development and use of Ontologies Inside the Neuroscience Information Framework: A Practical Approach. Frontiers in Genetics. 3. 111–111. 37 indexed citations
9.
Palyanov, Andrey, et al.. (2012). Towards a virtual C. elegans: A framework for simulation and visualization of the neuromuscular system in a 3D physical environment. In Silico Biology. 11(3,4). 137–147. 23 indexed citations
10.
Cachat, Jonathan, Anita Bandrowski, Jeffrey S. Grethe, et al.. (2012). A Survey of the Neuroscience Resource Landscape. International review of neurobiology. 103. 39–68. 17 indexed citations
11.
Larson, Stephen, et al.. (2011). NIFSTD and NeuroLex: Comprehensive Neuroscience Ontology Development Based on Multiple Biomedical Ontologies and Community Involvement.. 5 indexed citations
12.
Ghosh, Sulagna, et al.. (2011). Sensory maps in the olfactory cortex defined by long-range viral tracing of single neurons. Nature. 472(7342). 217–220. 198 indexed citations
13.
Larson, Stephen. (2009). Ontologies for neuroscience: What are they and what are they good for?. Frontiers in Neuroscience. 3(1). 60–7. 39 indexed citations
14.
Larson, Stephen. (2009). Information Systems and strategic decisions: A literature Review. Journal of the Association for Information Systems. 3 indexed citations
15.
Bug, William, Giorgio A. Ascoli, Jeffrey S. Grethe, et al.. (2008). The NIFSTD and BIRNLex Vocabularies: Building Comprehensive Ontologies for Neuroscience. Neuroinformatics. 6(3). 175–194. 107 indexed citations
16.
Larson, Stephen & Maryann E. Martone. (2007). Rule-Based Reasoning With A Multi-Scale Neuroanatomical Ontology.. 5 indexed citations
17.
Larson, Stephen, Amarnath Gupta, William Bug, et al.. (2007). An Ontology-Driven Knowledge Environment For Subcellular Neuroanatomy.. 6 indexed citations
18.
Larson, Stephen. (2007). A formal ontology of subcellular neuroanatomy. Frontiers in Neuroinformatics. 1. 3–3. 16 indexed citations
19.
Martone, Maryann E., et al.. (2007). The Cell Centered Database project: An update on building community resources for managing and sharing 3D imaging data. Journal of Structural Biology. 161(3). 220–231. 61 indexed citations
20.
Larson, Stephen, et al.. (1999). The Minnesota SOST and Sexual Reoffending in North Dakota: A Retrospective Study. International Journal of Offender Therapy and Comparative Criminology. 43(1). 71–77. 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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