W. Trimble

1.4k total citations
34 papers, 901 citations indexed

About

W. Trimble is a scholar working on Molecular Biology, Ecology and Nuclear and High Energy Physics. According to data from OpenAlex, W. Trimble has authored 34 papers receiving a total of 901 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 10 papers in Ecology and 8 papers in Nuclear and High Energy Physics. Recurrent topics in W. Trimble's work include Genomics and Phylogenetic Studies (10 papers), Microbial Community Ecology and Physiology (9 papers) and Nuclear physics research studies (8 papers). W. Trimble is often cited by papers focused on Genomics and Phylogenetic Studies (10 papers), Microbial Community Ecology and Physiology (9 papers) and Nuclear physics research studies (8 papers). W. Trimble collaborates with scholars based in United States, Canada and Russia. W. Trimble's co-authors include Folker Meyer, Andreas Wilke, Jack A. Gilbert, Travis Harrison, Tobias Paczian, Kevin Keegan, Wolfgang Gerlach, Ananth Grama, Somali Chaterji and Saurabh Bagchi and has published in prestigious journals such as Physical Review Letters, Nucleic Acids Research and Applied Physics Letters.

In The Last Decade

W. Trimble

33 papers receiving 886 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
W. Trimble United States 17 387 242 178 122 97 34 901
M. Nicolaï Italy 19 469 1.2× 34 0.1× 365 2.1× 183 1.5× 88 0.9× 72 1.5k
K. Baba Japan 24 571 1.5× 36 0.1× 135 0.8× 37 0.3× 86 0.9× 116 1.8k
Xing Zhang China 17 349 0.9× 28 0.1× 62 0.3× 32 0.3× 55 0.6× 109 1.1k
Indu Khatri India 17 377 1.0× 90 0.4× 23 0.1× 130 1.1× 10 0.1× 66 850
M. Rost Czechia 23 70 0.2× 46 0.2× 111 0.6× 74 0.6× 57 0.6× 81 1.3k
David A. Foley United States 19 247 0.6× 145 0.6× 110 0.6× 19 0.2× 48 0.5× 38 1.2k
James H. Hunter United States 18 284 0.7× 31 0.1× 26 0.1× 42 0.3× 41 0.4× 90 1.2k
Don S. Daly United States 14 556 1.4× 106 0.4× 9 0.1× 18 0.1× 25 0.3× 39 975
Huw Morgan United Kingdom 28 1.4k 3.7× 408 1.7× 10 0.1× 17 0.1× 23 0.2× 136 3.0k
Yongan Liu China 16 106 0.3× 31 0.1× 27 0.2× 13 0.1× 20 0.2× 63 830

Countries citing papers authored by W. Trimble

Since Specialization
Citations

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

Fields of papers citing papers by W. Trimble

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of W. Trimble

This figure shows the co-authorship network connecting the top 25 collaborators of W. Trimble. A scholar is included among the top collaborators of W. Trimble 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 W. Trimble. W. Trimble 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.
Trimble, W., et al.. (2021). Incremental and Semi-Supervised Learning of 16S-rRNA Genes For Taxonomic Classification. 2021 IEEE Symposium Series on Computational Intelligence (SSCI). 9. 1–7. 2 indexed citations
2.
Paczian, Tobias, W. Trimble, Wolfgang Gerlach, et al.. (2019). The MG-RAST API explorer: an on-ramp for RESTful query composition. BMC Bioinformatics. 20(1). 561–561. 8 indexed citations
3.
Wilke, Andreas, Wolfgang Gerlach, Elizabeth M. Glass, et al.. (2015). The MG-RAST metagenomics database and portal in 2015. Nucleic Acids Research. 44(D1). D590–D594. 129 indexed citations
4.
Xue, Hong, Otto X. Cordero, W. Trimble, et al.. (2015). Eco-Evolutionary Dynamics of Episomes among Ecologically Cohesive Bacterial Populations. mBio. 6(3). e00552–15. 20 indexed citations
5.
Williams, David, W. Trimble, Meghan H. Shilts, Folker Meyer, & Howard Ochman. (2013). Rapid quantification of sequence repeats to resolve the size, structure and contents of bacterial genomes. BMC Genomics. 14(1). 537–537. 24 indexed citations
6.
Wilke, Andreas, Elizabeth M. Glass, Daniela Bartels, et al.. (2013). A Metagenomics Portal for a Democratized Sequencing World. Methods in enzymology on CD-ROM/Methods in enzymology. 531. 487–523. 11 indexed citations
7.
Meyer, Folker, W. Trimble, Eugene B. Chang, & Kim M. Handley. (2012). Functional predictions from inference and observation in sequence-based inflammatory bowel disease research. Genome Biology. 13(9). 169–169. 9 indexed citations
8.
Olivas, Andrea D., Benjamin D. Shogan, Vesta Valuckaite, et al.. (2012). Intestinal Tissues Induce an SNP Mutation in Pseudomonas aeruginosa That Enhances Its Virulence: Possible Role in Anastomotic Leak. PLoS ONE. 7(8). e44326–e44326. 145 indexed citations
9.
Phung, Le T., W. Trimble, Folker Meyer, Jack A. Gilbert, & Simón Silver. (2012). Draft Genome Sequence of Alcaligenes faecalis subsp.faecalisNCIB 8687 (CCUG 2071). Journal of Bacteriology. 194(18). 5153–5153. 17 indexed citations
10.
Keegan, Kevin, W. Trimble, Jared Wilkening, et al.. (2012). A Platform-Independent Method for Detecting Errors in Metagenomic Sequencing Data: DRISEE. PLoS Computational Biology. 8(6). e1002541–e1002541. 63 indexed citations
11.
Trimble, W., Kevin Keegan, Mark D’Souza, et al.. (2012). Short-read reading-frame predictors are not created equal: sequence error causes loss of signal. BMC Bioinformatics. 13(1). 183–183. 27 indexed citations
12.
Amaro, Francisco, Jack A. Gilbert, Sarah M. Owens, W. Trimble, & Howard A. Shuman. (2012). Whole-Genome Sequence of the Human Pathogen Legionella pneumophila Serogroup 12 Strain 570-CO-H. Journal of Bacteriology. 194(6). 1613–1614. 20 indexed citations
13.
Phung, Le T., Simón Silver, W. Trimble, & Jack A. Gilbert. (2012). Draft Genome of Halomonas Species Strain GFAJ-1 (ATCC BAA-2256). Journal of Bacteriology. 194(7). 1835–1836. 9 indexed citations
14.
Willetts, Andrew, Ian Joint, Jack A. Gilbert, W. Trimble, & Martin Mühling. (2012). Isolation and initial characterization of a novel type of Baeyer–Villiger monooxygenase activity from a marine microorganism. Microbial Biotechnology. 5(4). 549–559. 8 indexed citations
15.
Clark, Jason A., K. S. Sharma, G. Savard, et al.. (2007). Precise measurement of theGe64mass and its effect on therpprocess. Physical Review C. 75(3). 23 indexed citations
16.
Savard, G., K. S. Sharma, H. P. Sharma, et al.. (2006). Studies of neutron-rich isotopes with the CPT mass spectrometer and the CARIBU project. International Journal of Mass Spectrometry. 251(2-3). 252–259. 38 indexed citations
17.
Savard, G., K. S. Sharma, J. A. Clark, et al.. (2004). The Canadian Penning Trap mass spectrometer. Nuclear Physics A. 746. 651–654. 12 indexed citations
18.
Clark, Jason A., Robert C. Barber, C. Boudreau, et al.. (2004). PRECISE MASS MEASUREMENTS OF NUCLIDES APPROACHING THE R-PROCESS. 11–19.
19.
Clark, J. A., G. Savard, K. S. Sharma, et al.. (2004). Precise Mass Measurement ofSe68, a Waiting-Point Nuclide along therpProcess. Physical Review Letters. 92(19). 192501–192501. 48 indexed citations
20.
Muravjov, A. V., et al.. (1999). Pulse separation control for mode-locked far-infrared p-Ge lasers. Applied Physics Letters. 74(2). 167–169. 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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