Timothy Galitski

5.2k total citations · 2 hit papers
33 papers, 3.9k citations indexed

About

Timothy Galitski is a scholar working on Molecular Biology, Genetics and Cell Biology. According to data from OpenAlex, Timothy Galitski has authored 33 papers receiving a total of 3.9k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 7 papers in Genetics and 2 papers in Cell Biology. Recurrent topics in Timothy Galitski's work include Bioinformatics and Genomic Networks (16 papers), Gene Regulatory Network Analysis (11 papers) and Fungal and yeast genetics research (9 papers). Timothy Galitski is often cited by papers focused on Bioinformatics and Genomic Networks (16 papers), Gene Regulatory Network Analysis (11 papers) and Fungal and yeast genetics research (9 papers). Timothy Galitski collaborates with scholars based in United States, Canada and Switzerland. Timothy Galitski's co-authors include Trey Ideker, Leroy Hood, Alexander Rives, Gerald R. Fink, Eric S. Lander, Cora A. Styles, John R. Roth, Alok J. Saldanha, Cintia F. Hongay and Paula Grisafi and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Timothy Galitski

33 papers receiving 3.8k citations

Hit Papers

A NEWAPPROACH TODECODINGLIFE: Systems Biology 1999 2026 2008 2017 2001 1999 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Timothy Galitski United States 21 3.2k 603 487 257 244 33 3.9k
Vera van Noort Belgium 36 3.3k 1.0× 480 0.8× 468 1.0× 151 0.6× 493 2.0× 78 4.5k
Jan Ihmels Israel 13 3.6k 1.1× 591 1.0× 240 0.5× 176 0.7× 136 0.6× 13 4.0k
Edda Klipp Germany 39 4.4k 1.4× 358 0.6× 362 0.7× 495 1.9× 264 1.1× 161 5.4k
Frank J. Bruggeman Netherlands 38 4.0k 1.3× 712 1.2× 196 0.4× 538 2.1× 246 1.0× 124 4.9k
Pier Luigi Martelli Italy 35 3.8k 1.2× 1.1k 1.8× 725 1.5× 140 0.5× 232 1.0× 160 5.3k
Iddo Friedberg United States 25 5.7k 1.8× 749 1.2× 576 1.2× 126 0.5× 349 1.4× 59 7.2k
Julien Gagneur Germany 37 5.0k 1.6× 824 1.4× 455 0.9× 213 0.8× 128 0.5× 92 6.0k
Michael Costanzo Canada 40 4.5k 1.4× 626 1.0× 497 1.0× 176 0.7× 223 0.9× 84 5.2k
Alan Bridge Switzerland 23 3.1k 1.0× 458 0.8× 400 0.8× 189 0.7× 232 1.0× 44 4.1k
Dmitrij Frishman Germany 36 6.0k 1.9× 884 1.5× 501 1.0× 198 0.8× 459 1.9× 160 7.5k

Countries citing papers authored by Timothy Galitski

Since Specialization
Citations

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

Fields of papers citing papers by Timothy Galitski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timothy Galitski

This figure shows the co-authorship network connecting the top 25 collaborators of Timothy Galitski. A scholar is included among the top collaborators of Timothy Galitski 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 Timothy Galitski. Timothy Galitski 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.
Galitski, Timothy. (2012). Reductionism Gives Way to Systems Biology. Genetic Engineering & Biotechnology News. 32(6). 52–53. 1 indexed citations
2.
Thompson, Ethan & Timothy Galitski. (2012). Quantifying and Analyzing the Network Basis of Genetic Complexity. PLoS Computational Biology. 8(7). e1002583–e1002583. 5 indexed citations
3.
Carter, Gregory W., et al.. (2012). Use of Pleiotropy to Model Genetic Interactions in a Population. PLoS Genetics. 8(10). e1003010–e1003010. 20 indexed citations
4.
Falconnet, Didier, et al.. (2010). High-throughput tracking of single yeast cells in a microfluidic imaging matrix. Lab on a Chip. 11(3). 466–473. 53 indexed citations
5.
Carter, Gregory W., David J. Galas, & Timothy Galitski. (2009). Maximal Extraction of Biological Information from Genetic Interaction Data. PLoS Computational Biology. 5(4). e1000347–e1000347. 30 indexed citations
6.
Siegel, Andrew F., et al.. (2007). Network motif analysis of a multi-mode genetic-interaction network. Genome Biology. 8(8). R160–R160. 9 indexed citations
7.
Prinz, Susanne, et al.. (2007). Control of Signaling in a MAP-kinase Pathway by an RNA-Binding Protein. PLoS ONE. 2(2). e249–e249. 19 indexed citations
8.
Carter, Gregory W., Steffen Rupp, Gerald R. Fink, & Timothy Galitski. (2006). Disentangling information flow in the Ras-cAMP signaling network. Genome Research. 16(4). 520–526. 14 indexed citations
9.
Hongay, Cintia F., Paula Grisafi, Timothy Galitski, & Gerald R. Fink. (2006). Antisense Transcription Controls Cell Fate in Saccharomyces cerevisiae. Cell. 127(4). 735–745. 291 indexed citations
10.
Marzolf, Bruz, Eric W. Deutsch, Patrick Moss, et al.. (2006). SBEAMS-Microarray: database software supporting genomic expression analyses for systems biology. BMC Bioinformatics. 7(1). 286–286. 44 indexed citations
11.
Reiss, David J., et al.. (2005). Tools enabling the elucidation of molecular pathways active in human disease: Application to Hepatitis C virus infection. BMC Bioinformatics. 6(1). 154–154. 15 indexed citations
12.
Drees, Becky, Vésteinn Thórsson, Gregory W. Carter, et al.. (2005). Derivation of genetic interaction networks from quantitative phenotype data. Genome biology. 6(4). R38–R38. 92 indexed citations
13.
Štorchová, Zuzana, et al.. (2004). Defects Arising From Whole-Genome Duplications in Saccharomyces cerevisiae. Genetics. 167(3). 1109–1121. 66 indexed citations
14.
Prinz, Susanne, et al.. (2004). Control of Yeast Filamentous-Form Growth by Modules in an Integrated Molecular Network. Genome Research. 14(3). 380–390. 73 indexed citations
15.
Yan, Wei, Hookeun Lee, Eugene C. Yi, et al.. (2004). System-based proteomic analysis of the interferon response in human liver cells. Genome biology. 5(8). R54–R54. 61 indexed citations
16.
Galitski, Timothy. (2004). MOLECULAR NETWORKS IN MODEL SYSTEMS. Annual Review of Genomics and Human Genetics. 5(1). 177–187. 15 indexed citations
17.
Wright, Michael E., Jimmy K. Eng, James H. Sherman, et al.. (2003). Identification of androgen-coregulated protein networks from the microsomes of human prostate cancer cells. Genome biology. 5(1). R4–R4. 56 indexed citations
18.
Smith, Jennifer J., Marcello Marelli, Franco J. Vizeacoumar, et al.. (2002). Transcriptome profiling to identify genes involved in peroxisome assembly and function. The Journal of Cell Biology. 158(2). 259–271. 154 indexed citations
19.
Galitski, Timothy & John R. Roth. (1997). Pathways for Homologous Recombination Between Chromosomal Direct Repeats in Salmonella typhimurium. Genetics. 146(3). 751–767. 57 indexed citations
20.
Galitski, Timothy & John R. Roth. (1996). A Search for a General Phenomenon of Adaptive Mutability. Genetics. 143(2). 645–659. 42 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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