Christopher T. Workman

13.2k total citations · 3 hit papers
96 papers, 6.0k citations indexed

About

Christopher T. Workman is a scholar working on Molecular Biology, Genetics and Immunology. According to data from OpenAlex, Christopher T. Workman has authored 96 papers receiving a total of 6.0k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Molecular Biology, 17 papers in Genetics and 9 papers in Immunology. Recurrent topics in Christopher T. Workman's work include Fungal and yeast genetics research (15 papers), RNA and protein synthesis mechanisms (13 papers) and Microbial Metabolic Engineering and Bioproduction (13 papers). Christopher T. Workman is often cited by papers focused on Fungal and yeast genetics research (15 papers), RNA and protein synthesis mechanisms (13 papers) and Microbial Metabolic Engineering and Bioproduction (13 papers). Christopher T. Workman collaborates with scholars based in Denmark, United States and United Kingdom. Christopher T. Workman's co-authors include Gary D. Stormo, Søren Brunak, Daniel C. Weaver, Trey Ideker, Steen Knudsen, Lars Juhl Jensen, Nassim Usman, Kasper Lage, Susan Grimm and Randy M. Berka and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of the American Chemical Society.

In The Last Decade

Christopher T. Workman

95 papers receiving 5.8k citations

Hit Papers

A scored human protein–pr... 2015 2026 2018 2022 2016 2015 2019 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Christopher T. Workman 4.4k 781 614 402 376 96 6.0k
Johannes Griss 4.1k 0.9× 438 0.6× 520 0.8× 856 2.1× 412 1.1× 61 6.5k
Stephen Kwok‐Wing Tsui 4.2k 1.0× 441 0.6× 371 0.6× 766 1.9× 1.1k 3.0× 275 7.6k
Laura L. Elo 3.6k 0.8× 713 0.9× 346 0.6× 681 1.7× 766 2.0× 159 5.7k
Shuai Weng 3.7k 0.8× 1.0k 1.3× 551 0.9× 309 0.8× 395 1.1× 29 5.2k
Keiichiro Ono 4.7k 1.0× 896 1.1× 699 1.1× 400 1.0× 921 2.4× 29 6.8k
Martin Eisenacher 5.4k 1.2× 568 0.7× 398 0.6× 856 2.1× 780 2.1× 163 8.6k
Haruko Ogawa 1.6k 0.4× 426 0.5× 317 0.5× 726 1.8× 240 0.6× 236 4.4k
Alan J. Tackett 5.8k 1.3× 531 0.7× 485 0.8× 499 1.2× 535 1.4× 150 7.5k
Mickaël Guedj 2.2k 0.5× 435 0.6× 213 0.3× 420 1.0× 413 1.1× 54 4.0k
Xiangqin Cui 3.6k 0.8× 952 1.2× 813 1.3× 337 0.8× 439 1.2× 120 5.7k

Countries citing papers authored by Christopher T. Workman

Since Specialization
Citations

This map shows the geographic impact of Christopher T. Workman'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 Christopher T. Workman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher T. Workman more than expected).

Fields of papers citing papers by Christopher T. Workman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Christopher T. Workman. 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 Christopher T. Workman. The network helps show where Christopher T. Workman may publish in the future.

Co-authorship network of co-authors of Christopher T. Workman

This figure shows the co-authorship network connecting the top 25 collaborators of Christopher T. Workman. A scholar is included among the top collaborators of Christopher T. Workman 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 Christopher T. Workman. Christopher T. Workman 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.
Mansourvar, Marjan, et al.. (2023). PanYolo: a pangenome-based deep-learning model for variant calling. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU). 1 indexed citations
2.
Großbach, Jan, Mathieu Clément‐Ziza, Ludovic Gillet, et al.. (2023). Genetic effects on molecular network states explain complex traits. Molecular Systems Biology. 19(8). e11493–e11493. 13 indexed citations
3.
Andersen, Daniel, Janne Marie Moll, Niels Banhos Danneskiold‐Samsøe, et al.. (2023). Oral administration of helminth fluid modulates distinct tuft cell and immune‐metabolic cues linked to reduced body fat. Parasite Immunology. 45(7). e12998–e12998. 2 indexed citations
4.
Jian, Jianbo, Zhangyan Wu, Arisbe Silva-Núñez, et al.. (2023). Long-read genome sequencing provides novel insights into the harmful algal bloom species Prymnesium parvum. The Science of The Total Environment. 908. 168042–168042. 5 indexed citations
5.
Sánchez, Benjamín J., et al.. (2022). Emergence of Phenotypically Distinct Subpopulations Is a Factor in Adaptation of Recombinant Saccharomyces cerevisiae under Glucose-Limited Conditions. Applied and Environmental Microbiology. 88(7). e0230721–e0230721. 5 indexed citations
6.
Ingerslev, Lars R., Ali Altıntaş, L Lundell, et al.. (2022). Comparative Analysis of Sperm DNA Methylation Supports Evolutionary Acquired Epigenetic Plasticity for Organ Speciation. Epigenomics. 14(21). 1305–1324. 3 indexed citations
7.
Ferris, Mark, Christopher T. Workman, David Enoch, et al.. (2021). Efficacy of FFP3 respirators for prevention of SARS-CoV-2 infection in healthcare workers. eLife. 10. 17 indexed citations
8.
Williams, Kristine, Lars R. Ingerslev, Jette Bork‐Jensen, et al.. (2020). Skeletal muscle enhancer interactions identify genes controlling whole-body metabolism. Nature Communications. 11(1). 2695–2695. 27 indexed citations
9.
Moll, Janne Marie, Daniel Andersen, Christopher T. Workman, et al.. (2019). Body fluid from the parasitic worm Ascaris suum inhibits broad‐acting pro‐inflammatory programs in dendritic cells. Immunology. 159(3). 322–334. 15 indexed citations
10.
Neergaard, Jesper Skov, Claus Christiansen, Henning B. Nielsen, et al.. (2017). Modifiable risk factors promoting neurodegeneration is associated with two novel brain degradation markers measured in serum. Neurochemistry International. 108. 303–308. 2 indexed citations
11.
Lino, Felipe Senne De Oliveira, et al.. (2017). Industrial antifoam agents impair ethanol fermentation and induce stress responses in yeast cells. Applied Microbiology and Biotechnology. 101(22). 8237–8248. 15 indexed citations
12.
Seemann, Stefan E., Aashiq H. Mirza, Claus Hansen, et al.. (2017). The identification and functional annotation of RNA structures conserved in vertebrates. Genome Research. 27(8). 1371–1383. 62 indexed citations
13.
Junge, Alexander, Jan C. Refsgaard, Christian Garde, et al.. (2016). RAIN: RNA–protein Association and Interaction Networks. Database. 2017. baw167–baw167. 100 indexed citations
14.
Ewald, David, Dana Malajian, James G. Krueger, et al.. (2015). Meta-analysis derived atopic dermatitis (MADAD) transcriptome defines a robust AD signature highlighting the involvement of atherosclerosis and lipid metabolism pathways. BMC Medical Genomics. 8(1). 132 indexed citations
15.
Workman, Christopher T., et al.. (2014). Oxidative stress response pathways: Fission yeast as archetype. Critical Reviews in Microbiology. 41(4). 520–535. 28 indexed citations
16.
Yang, Lei, Lars Jelsbak, Rasmus L. Marvig, et al.. (2011). Evolutionary dynamics of bacteria in a human host environment. Proceedings of the National Academy of Sciences. 108(18). 7481–7486. 267 indexed citations
17.
Berchtold, Lukas Adrian, Claus M. Larsen, Allan Vaag, et al.. (2009). IL-1 receptor antagonism and muscle gene expression in patients with type 2 diabetes. European Cytokine Network. 20(2). 81–87. 10 indexed citations
18.
Ferreira, Gabriela B., Lut Overbergh, Evelyne van Etten, et al.. (2008). Protein‐induced changes during the maturation process of human dendritic cells: A 2‐D DIGE approach. PROTEOMICS - CLINICAL APPLICATIONS. 2(9). 1349–1360. 10 indexed citations
19.
Jensen, Lars Juhl, Ramneek Gupta, Nikolaj Blom, et al.. (2002). Prediction of Human Protein Function from Post-translational Modifications and Localization Features. Journal of Molecular Biology. 319(5). 1257–1265. 244 indexed citations
20.
Egli, Marcel, et al.. (1995). Crystallization and preliminary X-ray diffraction analysis of double-helical RNA octamers. Acta Crystallographica Section D Biological Crystallography. 51(6). 1065–1070. 7 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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