Jonathan L. Lustgarten

555 total citations
12 papers, 414 citations indexed

About

Jonathan L. Lustgarten is a scholar working on Molecular Biology, Artificial Intelligence and Information Systems. According to data from OpenAlex, Jonathan L. Lustgarten has authored 12 papers receiving a total of 414 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Artificial Intelligence and 2 papers in Information Systems. Recurrent topics in Jonathan L. Lustgarten's work include Bioinformatics and Genomic Networks (7 papers), Gene expression and cancer classification (5 papers) and Machine Learning in Bioinformatics (3 papers). Jonathan L. Lustgarten is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Gene expression and cancer classification (5 papers) and Machine Learning in Bioinformatics (3 papers). Jonathan L. Lustgarten collaborates with scholars based in United States and Canada. Jonathan L. Lustgarten's co-authors include Vanathi Gopalakrishnan, Shyam Visweswaran, Gregory F. Cooper, Himanshu Grover, Henrik Ryberg, Robert Bowser, Jiyan An, Merit Cudkowicz, David Lacomis and Samuel Darko and has published in prestigious journals such as Bioinformatics, PLoS ONE and BMC Bioinformatics.

In The Last Decade

Jonathan L. Lustgarten

12 papers receiving 403 citations

Peers

Jonathan L. Lustgarten

MB

AI

NEURO

PHYSI

IS

Haining Li China

Isabel Rojas Germany

Adam P. Levine United Kingdom

Jingming Liu China

J.M. García-Campos Spain

M.C.K. Yang United States

Jianhai Zhang China

Yuhui Zhang China

Yue Fan China

Denise Slenter Netherlands

Haining Li China

Jonathan L. Lustgarten

299 ×1.5

MB

44 ×0.5

AI

35 ×0.5

NEURO

66 ×1.5

PHYSI

17 ×0.4

IS

Citations per year, relative to Jonathan L. Lustgarten Jonathan L. Lustgarten (= 1×) peers Haining Li

Countries citing papers authored by Jonathan L. Lustgarten

Since Specialization

Citations

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

Fields of papers citing papers by Jonathan L. Lustgarten

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan L. Lustgarten

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

All Works

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12 of 12 papers shown

1.

Lustgarten, Jonathan L., Shyam Visweswaran, Vanathi Gopalakrishnan, & Gregory F. Cooper. (2011). Application of an efficient Bayesian discretization method to biomedical data. BMC Bioinformatics. 12(1). 309–309. 42 indexed citations

2.

Li, Xiaoxiao, James F. LeBlanc, Allison Truong, et al.. (2011). A Metaproteomic Approach to Study Human-Microbial Ecosystems at the Mucosal Luminal Interface. PLoS ONE. 6(11). e26542–e26542. 65 indexed citations

3.

Ryberg, Henrik, Jiyan An, Samuel Darko, et al.. (2010). Discovery and verification of amyotrophic lateral sclerosis biomarkers by proteomics. Muscle & Nerve. 42(1). 104–111. 90 indexed citations

4.

Gopalakrishnan, Vanathi, Jonathan L. Lustgarten, Shyam Visweswaran, & Gregory F. Cooper. (2010). Bayesian rule learning for biomedical data mining. Bioinformatics. 26(5). 668–675. 29 indexed citations

5.

Lustgarten, Jonathan L., Shyam Visweswaran, Robert Bowser, William R. Hogan, & Vanathi Gopalakrishnan. (2009). Knowledge-based variable selection for learning rules from proteomic data. BMC Bioinformatics. 10(S9). S16–S16. 6 indexed citations

6.

Strober, Bruce, Amy McMichael, Maria Hordinsky, et al.. (2009). Alefacept for Severe Alopecia Areata. Archives of Dermatology. 145(11). 1262–6. 32 indexed citations

7.

Mowery, Danielle L., Henk Harkema, John Dowling, Jonathan L. Lustgarten, & Wendy W. Chapman. (2009). Distinguishing historical from current problems in clinical reports. 10–10. 7 indexed citations

8.

Gopalakrishnan, Vanathi & Jonathan L. Lustgarten. (2009). A bayesian rule generation framework for 'omic' biomedical data analysis. 5 indexed citations

9.

Lustgarten, Jonathan L., Vanathi Gopalakrishnan, & Shyam Visweswaran. (2009). Measuring stability of feature selection in biomedical datasets.. PubMed. 2009. 406–10. 50 indexed citations

10.

Lustgarten, Jonathan L., Shyam Visweswaran, Himanshu Grover, & Vanathi Gopalakrishnan. (2008). An Evaluation of Discretization Methods for Learning Rules from Biomedical Datasets.. 527–532. 5 indexed citations

11.

Lustgarten, Jonathan L., Vanathi Gopalakrishnan, Himanshu Grover, & Shyam Visweswaran. (2008). Improving classification performance with discretization on biomedical datasets.. PubMed. 445–9. 68 indexed citations

12.

Lustgarten, Jonathan L., et al.. (2008). EPO-KB: a searchable knowledge base of biomarker to protein links. Bioinformatics. 24(11). 1418–1419. 15 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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