Jeff De Pons

953 total citations
19 papers, 520 citations indexed

About

Jeff De Pons is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Jeff De Pons has authored 19 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 6 papers in Genetics and 2 papers in Cancer Research. Recurrent topics in Jeff De Pons's work include Bioinformatics and Genomic Networks (13 papers), Biomedical Text Mining and Ontologies (9 papers) and Gene expression and cancer classification (7 papers). Jeff De Pons is often cited by papers focused on Bioinformatics and Genomic Networks (13 papers), Biomedical Text Mining and Ontologies (9 papers) and Gene expression and cancer classification (7 papers). Jeff De Pons collaborates with scholars based in United States. Jeff De Pons's co-authors include G. Thomas Hayman, Melinda R. Dwinell, Jennifer R. Smith, Mary Shimoyama, Stanley J. F. Laulederkind, Marek Tutaj, Shur‐Jen Wang, Rajni Nigam, Victoria Petri and Elizabeth A. Worthey and has published in prestigious journals such as Nucleic Acids Research, Briefings in Bioinformatics and Physiological Genomics.

In The Last Decade

Jeff De Pons

19 papers receiving 513 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeff De Pons United States 13 398 121 38 36 29 19 520
Rajni Nigam United States 13 421 1.1× 123 1.0× 35 0.9× 32 0.9× 46 1.6× 22 542
Marek Tutaj United States 13 416 1.0× 148 1.2× 55 1.4× 33 0.9× 25 0.9× 26 584
Victoria Petri United States 15 543 1.4× 156 1.3× 52 1.4× 32 0.9× 27 0.9× 26 689
David A. Drubin United States 12 805 2.0× 150 1.2× 53 1.4× 66 1.8× 17 0.6× 18 969
Andrew Tikhonov United Kingdom 4 519 1.3× 62 0.5× 94 2.5× 41 1.1× 22 0.8× 5 686
Gabriel Musso United States 15 502 1.3× 140 1.2× 57 1.5× 14 0.4× 13 0.4× 28 660
Matteo Bersanelli Italy 8 337 0.8× 64 0.5× 42 1.1× 25 0.7× 21 0.7× 11 445
Denise Slenter Netherlands 5 369 0.9× 56 0.5× 93 2.4× 48 1.3× 12 0.4× 8 605
Kahn Rhrissorrakrai United States 11 226 0.6× 66 0.5× 49 1.3× 59 1.6× 17 0.6× 28 428
Phillip Le United States 8 223 0.6× 99 0.8× 29 0.8× 9 0.3× 31 1.1× 11 453

Countries citing papers authored by Jeff De Pons

Since Specialization
Citations

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

Fields of papers citing papers by Jeff De Pons

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeff De Pons. 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 Jeff De Pons. The network helps show where Jeff De Pons may publish in the future.

Co-authorship network of co-authors of Jeff De Pons

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

All Works

19 of 19 papers shown
1.
Laulederkind, Stanley J. F., G. Thomas Hayman, Shur‐Jen Wang, et al.. (2019). Rat Genome Databases, Repositories, and Tools. Methods in molecular biology. 2018. 71–96. 14 indexed citations
2.
Laulederkind, Stanley J. F., G. Thomas Hayman, Shur‐Jen Wang, et al.. (2018). A Primer for the Rat Genome Database (RGD). Methods in molecular biology. 1757. 163–209. 7 indexed citations
3.
Shimoyama, Mary, Jennifer R. Smith, Jeff De Pons, et al.. (2016). The Chinchilla Research Resource Database: resource for an otolaryngology disease model. Database. 2016. baw073–baw073. 18 indexed citations
4.
Hayman, G. Thomas, Stanley J. F. Laulederkind, Jennifer R. Smith, et al.. (2016). The Disease Portals, disease–gene annotation and the RGD disease ontology at the Rat Genome Database. Database. 2016. baw034–baw034. 22 indexed citations
5.
Shimoyama, Mary, Stanley J. F. Laulederkind, Jeff De Pons, et al.. (2016). Exploring human disease using the Rat Genome Database. Disease Models & Mechanisms. 9(10). 1089–1095. 23 indexed citations
6.
Petri, Victoria, G. Thomas Hayman, Marek Tutaj, et al.. (2015). Disease, Models, Variants and Altered Pathways—Journeying RGD Through the Magnifying Glass. Computational and Structural Biotechnology Journal. 14. 35–48. 3 indexed citations
7.
Liu, Weisong, Stanley J. F. Laulederkind, G. Thomas Hayman, et al.. (2015). OntoMate: a text-mining tool aiding curation at the Rat Genome Database. Database. 2015. 15 indexed citations
8.
Shimoyama, Mary, Jeff De Pons, G. Thomas Hayman, et al.. (2014). The Rat Genome Database 2015: genomic, phenotypic and environmental variations and disease. Nucleic Acids Research. 43(D1). D743–D750. 164 indexed citations
9.
Petri, Victoria, Pushkala Jayaraman, Marek Tutaj, et al.. (2014). The pathway ontology – updates and applications. Journal of Biomedical Semantics. 5(1). 7–7. 65 indexed citations
10.
Petri, Victoria, G. Thomas Hayman, Marek Tutaj, et al.. (2014). Disease pathways at the Rat Genome Database Pathway Portal: genes in context¿a network approach to understanding the molecular mechanisms of disease. Human Genomics. 8(1). 17–17. 3 indexed citations
11.
Petri, Victoria, G. Thomas Hayman, Marek Tutaj, et al.. (2014). Disease pathways at the Rat Genome Database Pathway Portal: genes in context-a network approach to understanding the molecular mechanisms of disease. Human Genomics. 8(1). 17–17. 7 indexed citations
12.
Laulederkind, Stanley J. F., G. Thomas Hayman, Shuu‐Jiun Wang, et al.. (2013). The Rat Genome Database 2013--data, tools and users. Briefings in Bioinformatics. 14(4). 520–526. 55 indexed citations
13.
Hayman, G. Thomas, Pushkala Jayaraman, Victoria Petri, et al.. (2013). The updated RGD Pathway Portal utilizes increased curation efficiency and provides expanded pathway information. Human Genomics. 7(1). 4–4. 9 indexed citations
14.
Smith, Jennifer R., Carissa A. Park, Rajni Nigam, et al.. (2013). The clinical measurement, measurement method and experimental condition ontologies: expansion, improvements and new applications. Journal of Biomedical Semantics. 4(1). 26–26. 27 indexed citations
15.
Laulederkind, Stanley J. F., Weisong Liu, Jennifer R. Smith, et al.. (2013). PhenoMiner: quantitative phenotype curation at the rat genome database. Database. 2013. bat015–bat015. 23 indexed citations
16.
Nigam, Rajni, Stanley J. F. Laulederkind, G. Thomas Hayman, et al.. (2013). Rat Genome Database: a unique resource for rat, human, and mouse quantitative trait locus data. Physiological Genomics. 45(18). 809–816. 19 indexed citations
17.
Laulederkind, Stanley J. F., Marek Tutaj, Mary Shimoyama, et al.. (2012). Ontology searching and browsing at the Rat Genome Database. Database. 2012(0). bas016–bas016. 18 indexed citations
18.
Laulederkind, Stanley J. F., Mary Shimoyama, G. Thomas Hayman, et al.. (2011). The Rat Genome Database curation tool suite: a set of optimized software tools enabling efficient acquisition, organization, and presentation of biological data. Database. 2011(0). bar002–bar002. 12 indexed citations
19.
Petri, V., G. Thomas Hayman, Jennifer R. Smith, et al.. (2011). The Rat Genome Database Pathway Portal. Database. 2011(0). bar010–bar010. 16 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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