Author

Antonio Rueda Martin

Queen Mary University of London

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1 Approach:statistical model· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Arianna TucciiD· 2 shared Augusto RendoniD· 2 shared Ellen M. McDonaghiD· 2 shared Henry HouldeniD· 2 shared Aditi Chawla· 1 shared Ana Lisa Taylor TavaresiD· 1 shared Andrew David MumfordiD· 1 shared Anette E. SchragiD· 1 shared

Activity by Year

2018-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenomics

Arianna TucciORCID

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Author profile →

2 papers

Recent·Most cited

Whole genome sequencing for diagnosis of neurological repeat expansion disorders

Kristina Ibáñez, James M. Polke, Tanner Hagelstrom, Egor Dolzhenko, Dorota Pasko, Ellen Thomas, Louise C. Daugherty, Dalia Kasperavičiūtė, Ellen M. McDonagh, Katherine R. Smith, Antonio Rueda Martin, Dimitris Polychronopoulos, Heather Angus‐Leppan, Kailash P. Bhatia, James E. Davison, , Arianna Tucci

This study demonstrates that whole genome sequencing can effectively detect repeat expansions in neurological disorders with high sensitivity and specificity, enabling diagnosis in previously undiagnosed patients.

bioRxiv · Nov 6, 2020 · PreprintGenomics

G2P: Using machine learning to understand and predict genes causing rare neurological disorders

Juan Antonio Botía, Sebastian Guelfi, David Zhang, Karishma D’Sa, Regina Hertfelder Reynolds, Daniel F. O. Onah, Ellen M. McDonagh, Antonio Rueda Martin, Arianna Tucci, Augusto Rendon, Henry Houlden, John Hardy, Mina Ryten

The paper develops a machine learning model to predict genes causing rare neurological disorders and shows it accurately identifies disease-associated genes.

bioRxiv · Mar 27, 2018 · PreprintGenetics