Kevin Keegan

5.2k total citations
24 papers, 2.5k citations indexed

About

Kevin Keegan is a scholar working on Molecular Biology, Endocrine and Autonomic Systems and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kevin Keegan has authored 24 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 9 papers in Endocrine and Autonomic Systems and 8 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kevin Keegan's work include Circadian rhythm and melatonin (9 papers), Neurobiology and Insect Physiology Research (7 papers) and Genomics and Phylogenetic Studies (7 papers). Kevin Keegan is often cited by papers focused on Circadian rhythm and melatonin (9 papers), Neurobiology and Insect Physiology Research (7 papers) and Genomics and Phylogenetic Studies (7 papers). Kevin Keegan collaborates with scholars based in United States, Bulgaria and United Kingdom. Kevin Keegan's co-authors include Ravi Allada, Folker Meyer, Elizabeth M. Glass, Valerie L. Kilman, Michael Rosbash, Cory Pfeiffenberger, Bridget C. Lear, Brie Paddock, Suraj Pradhan and Andreas Wilke and has published in prestigious journals such as Nature, Cell and Nucleic Acids Research.

In The Last Decade

Kevin Keegan

24 papers receiving 2.5k citations

Peers

Kevin Keegan

CMN

EAS

ECOLO

KyeongJin Kang South Korea

Atsuhiko Hattori Japan

Dan Zhou United States

Sachiye Inouye Japan

Teiichi Tanimura Japan

William W. Ja United States

Gerben van Ooijen United Kingdom

Min Pan United States

Mingyao Yang China

KyeongJin Kang South Korea

Kevin Keegan

508 ×0.6

1.6k ×2.2

CMN

364 ×0.5

EAS

307 ×0.6

266 ×0.6

ECOLO

Citations per year, relative to Kevin Keegan Kevin Keegan (= 1×) peers KyeongJin Kang

Countries citing papers authored by Kevin Keegan

Since Specialization

Citations

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

Fields of papers citing papers by Kevin Keegan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin Keegan

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

All Works

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20 of 20 papers shown

Keegan, Kevin, Elizabeth M. Glass, & Folker Meyer. (2016). MG-RAST, a Metagenomics Service for Analysis of Microbial Community Structure and Function. Methods in molecular biology. 1399. 207–233. 324 indexed citations

Kortman, Guus A. M., Bas E. Dutilh, Annet Maathuis, et al.. (2016). Microbial Metabolism Shifts Towards an Adverse Profile with Supplementary Iron in the TIM-2 In vitro Model of the Human Colon. Frontiers in Microbiology. 6. 1481–1481. 63 indexed citations

Brown, Bonnie L., et al.. (2015). Metagenomic analysis of planktonic microbial consortia from a non-tidal urban-impacted segment of James River. Standards in Genomic Sciences. 10(1). 65–65. 23 indexed citations

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

Gerlach, Wolfgang, Wei Tang, Kevin Keegan, et al.. (2014). Skyport - Container-Based Execution Environment Management for Multi-cloud Scientific Workflows. 25–32. 68 indexed citations

Smith, Daniel P., John C. Alverdy, Gary An, et al.. (2013). The Hospital Microbiome Project: Meeting Report for the 1st Hospital Microbiome Project Workshop on sampling design and building science measurements, Chicago, USA, June 7th-8th 2012. Standards in Genomic Sciences. 8(1). 112–117. 13 indexed citations

Serova, Lidia, Andrej Tillinger, Lishay G. Alaluf, et al.. (2013). Single intranasal neuropeptide Y infusion attenuates development of PTSD-like symptoms to traumatic stress in rats. Neuroscience. 236. 298–312. 163 indexed citations

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

Claud, Erika C., Kevin Keegan, Jennifer M. Brulc, et al.. (2013). Bacterial community structure and functional contributions to emergence of health or necrotizing enterocolitis in preterm infants. Microbiome. 1(1). 20–20. 136 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.

Delmont, Tom O., Emmanuel Prestat, Kevin Keegan, et al.. (2012). Structure, fluctuation and magnitude of a natural grassland soil metagenome. The ISME Journal. 6(9). 1677–1687. 156 indexed citations

13.

Larsen, Peter E., F. Collart, Dawn Field, et al.. (2011). Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset. PubMed. 1(1). 4–4. 71 indexed citations

14.

Keegan, Kevin, Suraj Pradhan, Ji-Ping Wang, & Ravi Allada. (2007). Meta-Analysis of Drosophila Circadian Microarray Studies Identifies a Novel Set of Rhythmically Expressed Genes. PLoS Computational Biology. 3(11). e208–e208. 87 indexed citations

15.

Lim, Chunghun, Brian Y. Chung, Suraj Pradhan, et al.. (2007). clockwork orange Encodes a Transcriptional Repressor Important for Circadian-Clock Amplitude in Drosophila. Current Biology. 17(12). 1082–1089. 120 indexed citations

16.

Keegan, Kevin, et al.. (2006). A dynamic role for the mushroom bodies in promoting sleep in Drosophila. Nature. 441(7094). 753–756. 255 indexed citations

17.

Keegan, Kevin, Suraj Pradhan, Jiping Wang, & Ravi Allada. (2005). Meta-analysis of Drosophila Circadian Microarray Studies Identifies a Novel Set of Rhythmically Expressed Genes. PLoS Computational Biology. preprint(2007). e208–e208. 1 indexed citations

18.

Atwell, S., J.M. Adams, John Badger, et al.. (2004). A Novel Mode of Gleevec Binding Is Revealed by the Structure of Spleen Tyrosine Kinase. Journal of Biological Chemistry. 279(53). 55827–55832. 161 indexed citations

19.

Zhao, Jie, Valerie L. Kilman, Kevin Keegan, et al.. (2003). Drosophila Clock Can Generate Ectopic Circadian Clocks. Cell. 113(6). 755–766. 104 indexed citations

20.

Kilman, Valerie L., et al.. (2002). A role for casein kinase 2α in the Drosophila circadian clock. Nature. 420(6917). 816–820. 284 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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