Colm J. Ryan

2.4k total citations
45 papers, 1.0k citations indexed

About

Colm J. Ryan is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Colm J. Ryan has authored 45 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Molecular Biology, 7 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Colm J. Ryan's work include Bioinformatics and Genomic Networks (15 papers), CRISPR and Genetic Engineering (12 papers) and RNA and protein synthesis mechanisms (8 papers). Colm J. Ryan is often cited by papers focused on Bioinformatics and Genomic Networks (15 papers), CRISPR and Genetic Engineering (12 papers) and RNA and protein synthesis mechanisms (8 papers). Colm J. Ryan collaborates with scholars based in Ireland, United States and United Kingdom. Colm J. Ryan's co-authors include Christopher J. Lord, Nevan J. Krogan, Barbara De Kegel, Ilirjana Bajrami, James Campbell, Rachel Brough, Niall Quinn, Aditi Gulati, David J. Adams and Rowan Miller and has published in prestigious journals such as Nature Communications, Nature Genetics and Journal of Clinical Oncology.

In The Last Decade

Colm J. Ryan

39 papers receiving 999 citations

Peers

Colm J. Ryan

ONCOL

PFM

GENET

Feng Xing China

Nanni Huser United States

Jagruti Patel United States

Swee Seong Wong United States

Damian Fermin United States

Jaine K. Blayney United Kingdom

Joachim Bischof Germany

Ricarda Herr Germany

J. Hsu United States

Frederick S. Vizeacoumar Canada

Feng Xing China

Colm J. Ryan

492 ×0.6

199 ×0.9

ONCOL

124 ×1.0

83 ×0.7

PFM

62 ×0.7

GENET

Citations per year, relative to Colm J. Ryan Colm J. Ryan (= 1×) peers Feng Xing

Countries citing papers authored by Colm J. Ryan

Since Specialization

Citations

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

Fields of papers citing papers by Colm J. Ryan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Colm J. Ryan. 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 Colm J. Ryan. The network helps show where Colm J. Ryan may publish in the future.

Co-authorship network of co-authors of Colm J. Ryan

This figure shows the co-authorship network connecting the top 25 collaborators of Colm J. Ryan. A scholar is included among the top collaborators of Colm J. Ryan 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 Colm J. Ryan. Colm J. Ryan 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

Ryan, Colm J., et al.. (2025). Evaluating sequence and structural similarity metrics for predicting shared paralog functions. NAR Genomics and Bioinformatics. 7(2). lqaf051–lqaf051. 1 indexed citations

Gonçalves, Emanuel, Colm J. Ryan, & David J. Adams. (2025). Synthetic lethality in cancer drug discovery: challenges and opportunities. Nature Reviews Drug Discovery. 25(1). 22–38. 1 indexed citations

Bond, Jonathan, et al.. (2023). Gene essentiality in cancer is better predicted by mRNA abundance than by gene regulatory network-inferred activity. NAR Cancer. 5(4). zcad056–zcad056. 2 indexed citations

Kegel, Barbara De & Colm J. Ryan. (2023). Paralog dispensability shapes homozygous deletion patterns in tumor genomes. Molecular Systems Biology. 19(12). e11987–e11987. 9 indexed citations

Chan, Pui Ying, Victoria Harle, Victoria Offord, et al.. (2023). Genome-wide CRISPR-Cas9 screening to identify CDS2 as an essential gene in uveal melanoma.. Journal of Clinical Oncology. 41(16_suppl). e21585–e21585. 1 indexed citations

Ryan, Colm J., et al.. (2023). Antibody reliability influences observed mRNA–protein correlations in tumour samples. Life Science Alliance. 6(8). e202201885–e202201885.

Pettitt, Stephen J., Colm J. Ryan, & Christopher J. Lord. (2023). Exploiting Cancer Synthetic Lethality in Cancer—Lessons Learnt from PARP Inhibitors. Cancer treatment and research. 186. 13–23. 1 indexed citations

Ryan, Colm J., et al.. (2023). Targeting synthetic lethal paralogs in cancer. Trends in cancer. 9(5). 397–409. 29 indexed citations

Ryan, Colm J., et al.. (2023). Complex synthetic lethality in cancer. Nature Genetics. 55(12). 2039–2048. 31 indexed citations

10.

Ryan, Colm J., et al.. (2022). Experimental reproducibility limits the correlation between mRNA and protein abundances in tumor proteomic profiles. Cell Reports Methods. 2(9). 100288–100288. 30 indexed citations

11.

Parkhitko, Andrey A., Yanhui Hu, Richard Binari, et al.. (2021). Cross-species identification of PIP5K1-, splicing- and ubiquitin-related pathways as potential targets for RB1-deficient cells. PLoS Genetics. 17(2). e1009354–e1009354. 7 indexed citations

12.

Marcone, Simone, Amy Buckley, Colm J. Ryan, et al.. (2021). Proteomic signatures of radioresistance: Alteration of inflammation, angiogenesis and metabolism-related factors in radioresistant oesophageal adenocarcinoma. Cancer Treatment and Research Communications. 27. 100376–100376. 7 indexed citations

13.

Kegel, Barbara De, Niall Quinn, Nicola Thompson, David J. Adams, & Colm J. Ryan. (2021). Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines. Cell Systems. 12(12). 1144–1159.e6. 44 indexed citations

14.

Nováček, Vít, David Matallanas, Alfonso Blanco, et al.. (2020). Accurate prediction of kinase-substrate networks using knowledge graphs. PLoS Computational Biology. 16(12). e1007578–e1007578. 17 indexed citations

15.

Kegel, Barbara De & Colm J. Ryan. (2019). Paralog buffering contributes to the variable essentiality of genes in cancer cell lines. PLoS Genetics. 15(10). e1008466–e1008466. 54 indexed citations

16.

Campbell, James, Colm J. Ryan, & Christopher J. Lord. (2018). Identifying Genetic Dependencies in Cancer by Analyzing siRNA Screens in Tumor Cell Line Panels. Methods in molecular biology. 1711. 83–99. 2 indexed citations

17.

Hashimoto, Satoru, Melanie May, Alexey Epanchintsev, et al.. (2017). MED12-related XLID disorders are dose-dependent of immediate early genes (IEGs) expression. Human Molecular Genetics. 26(11). 2062–2075. 17 indexed citations

18.

Ryan, Colm J., Susan Kennedy, Ilirjana Bajrami, David Matallanas, & Christopher J. Lord. (2017). A Compendium of Co-regulated Protein Complexes in Breast Cancer Reveals Collateral Loss Events. Cell Systems. 5(4). 399–409.e5. 28 indexed citations

19.

Williamson, Chris T., Rowan Miller, Helen N. Pemberton, et al.. (2016). ATR inhibitors as a synthetic lethal therapy for tumours deficient in ARID1A. Nature Communications. 7(1). 13837–13837. 270 indexed citations

20.

Ryan, Colm J., Peter Cimermančič, Zachary A. Szpiech, et al.. (2013). High-resolution network biology: connecting sequence with function. Nature Reviews Genetics. 14(12). 865–879. 63 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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