Simon Twigger

5.5k total citations
29 papers, 1.4k citations indexed

About

Simon Twigger is a scholar working on Molecular Biology, Genetics and Spectroscopy. According to data from OpenAlex, Simon Twigger has authored 29 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 7 papers in Genetics and 6 papers in Spectroscopy. Recurrent topics in Simon Twigger's work include Bioinformatics and Genomic Networks (12 papers), Biomedical Text Mining and Ontologies (8 papers) and Genetic Mapping and Diversity in Plants and Animals (7 papers). Simon Twigger is often cited by papers focused on Bioinformatics and Genomic Networks (12 papers), Biomedical Text Mining and Ontologies (8 papers) and Genetic Mapping and Diversity in Plants and Animals (7 papers). Simon Twigger collaborates with scholars based in United States, Japan and United Kingdom. Simon Twigger's co-authors include Brian Halligan, Seung Y. Rhee, Maria C. Costanzo, Owen White, David P. Hill, Douglas G. Howe, Petra Fey, Renate Kania, Mary Schaeffer and Takashi Gojobori and has published in prestigious journals such as Nature, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Simon Twigger

29 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simon Twigger United States 17 881 185 180 124 103 29 1.4k
David W. Kane United States 15 1.8k 2.0× 183 1.0× 135 0.8× 125 1.0× 315 3.1× 18 2.4k
Carl F. Schaefer United States 23 1.7k 2.0× 226 1.2× 238 1.3× 105 0.8× 295 2.9× 43 2.7k
Christian Stolte United States 16 747 0.8× 88 0.5× 73 0.4× 258 2.1× 80 0.8× 25 1.9k
Marco Masseroli Italy 23 1.0k 1.2× 125 0.7× 49 0.3× 310 2.5× 114 1.1× 135 2.0k
B. F. Francis Ouellette Canada 23 2.1k 2.3× 237 1.3× 59 0.3× 159 1.3× 160 1.6× 57 2.7k
Kei‐Hoi Cheung United States 24 1.6k 1.8× 655 3.5× 169 0.9× 344 2.8× 79 0.8× 77 2.5k
Uğis Sarkans United Kingdom 18 1.9k 2.1× 254 1.4× 69 0.4× 96 0.8× 289 2.8× 29 2.5k
Douglas G. Howe United States 16 779 0.9× 167 0.9× 23 0.1× 115 0.9× 74 0.7× 33 1.4k
Mehmet Koyutürk United States 30 1.7k 1.9× 245 1.3× 138 0.8× 307 2.5× 180 1.7× 122 2.7k
Maria C. Costanzo United States 28 2.5k 2.9× 202 1.1× 98 0.5× 113 0.9× 37 0.4× 58 3.2k

Countries citing papers authored by Simon Twigger

Since Specialization
Citations

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

Fields of papers citing papers by Simon Twigger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simon Twigger

This figure shows the co-authorship network connecting the top 25 collaborators of Simon Twigger. A scholar is included among the top collaborators of Simon Twigger 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 Simon Twigger. Simon Twigger 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.
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
2.
Twigger, Simon, et al.. (2009). Using the NCBO Web Services for Concept Recognition and Ontology Annotation of Expression Datasets.. 6 indexed citations
3.
Shimoyama, Mary, G. Thomas Hayman, Stanley J. F. Laulederkind, et al.. (2009). The Rat Genome Database Curators: Who, What, Where, Why. PLoS Computational Biology. 5(11). e1000582–e1000582. 21 indexed citations
4.
Dwinell, Melinda R., Elizabeth A. Worthey, Mary Shimoyama, et al.. (2008). The Rat Genome Database 2009: variation, ontologies and pathways. Nucleic Acids Research. 37(Database). D744–D749. 58 indexed citations
5.
Twigger, Simon, Kim D. Pruitt, Xosé M. Fernández, et al.. (2008). What everybody should know about the rat genome and its online resources. Nature Genetics. 40(5). 523–527. 34 indexed citations
6.
Sander, Tara L., Sushma Kaul, Bassam T. Wakim, et al.. (2008). Comparative proteomic analysis of PAI‐1 and TNF‐alpha‐derived endothelial microparticles. PROTEOMICS. 8(12). 2430–2446. 121 indexed citations
7.
Howe, Douglas G., Maria C. Costanzo, Petra Fey, et al.. (2008). The future of biocuration. Nature. 455(7209). 47–50. 459 indexed citations
8.
Phillips, G.N., Brian G. Fox, John L. Markley, et al.. (2007). Structures of proteins of biomedical interest from the Center for Eukaryotic Structural Genomics. Journal of Structural and Functional Genomics. 8(2-3). 73–84. 9 indexed citations
9.
Twigger, Simon, et al.. (2006). The Rat Genome Database, update 2007--Easing the path from disease to data and back again. Nucleic Acids Research. 35(Database). D658–D662. 109 indexed citations
10.
Twigger, Simon, et al.. (2006). Exploring Phenotypic Data at the Rat Genome Database. Current Protocols in Bioinformatics. 14(1). Unit 1.14–Unit 1.14. 15 indexed citations
11.
Shimoyama, Mary, Victoria Petri, Dean Pasko, et al.. (2005). Using multiple ontologies to integrate complex biological data. Comparative and Functional Genomics. 6(7-8). 373–378. 8 indexed citations
12.
Weinshenker, David, Malania M. Wilson, Katherine M. Williams, et al.. (2005). A new method for identifying informative genetic markers in selectively bred rats. Mammalian Genome. 16(10). 784–791. 2 indexed citations
13.
Halligan, Brian, et al.. (2005). ZoomQuant: An application for the quantitation of stable isotope labeled peptides. Journal of the American Society for Mass Spectrometry. 16(3). 302–306. 63 indexed citations
14.
Halligan, Brian, et al.. (2005). DeNovoID: a web-based tool for identifying peptides from sequence and mass tags deduced from de novo peptide sequencing by mass spectroscopy. Nucleic Acids Research. 33(Web Server). W376–W381. 17 indexed citations
15.
Wen, Xinyu, Hang Liu, Victor Ruotti, et al.. (2004). ChromSorter PC: A database of chromosomal regions associated with human prostate cancer. BMC Genomics. 5(1). 27–27. 2 indexed citations
16.
Twigger, Simon, Jeff Nie, Victor Ruotti, et al.. (2004). Integrative Genomics: In Silico Coupling of Rat Physiology and Complex Traits With Mouse and Human Data. Genome Research. 14(4). 651–660. 16 indexed citations
17.
Twigger, Simon. (2004). Of rats and men.. Genome Biology. 5(3). 314–314. 3 indexed citations
18.
Halligan, Brian, et al.. (2004). ProMoST (Protein Modification Screening Tool): a web-based tool for mapping protein modifications on two-dimensional gels. Nucleic Acids Research. 32(Web Server). W638–W644. 97 indexed citations
19.
Twigger, Simon. (2002). Rat Genome Database (RGD): mapping disease onto the genome. Nucleic Acids Research. 30(1). 125–128. 80 indexed citations
20.
Kwitek, Anne E., Peter J. Tonellato, Dan Chen, et al.. (2001). Automated Construction of High-Density Comparative Maps Between Rat, Human, and Mouse. Genome Research. 11(11). 1935–1943. 34 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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