T
Thomas Rolland
Researcher at Harvard University
Publications - 35
Citations - 4970
Thomas Rolland is an academic researcher from Harvard University. The author has contributed to research in topics: Autism & Interactome. The author has an hindex of 18, co-authored 31 publications receiving 3951 citations. Previous affiliations of Thomas Rolland include Centre national de la recherche scientifique & Pierre-and-Marie-Curie University.
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Journal ArticleDOI
A proteome-scale map of the human interactome network
Thomas Rolland,Murat Tasan,Benoit Charloteaux,Samuel J. Pevzner,Quan Zhong,Quan Zhong,Nidhi Sahni,Song Yi,Irma Lemmens,Celia Fontanillo,Roberto Mosca,Atanas Kamburov,Susan Dina Ghiassian,Susan Dina Ghiassian,Xinping Yang,Lila Ghamsari,Dawit Balcha,Bridget E. Begg,Pascal Braun,Marc Brehme,Martin P. Broly,Anne-Ruxandra Carvunis,Dan Convery-Zupan,Roser Corominas,Jasmin Coulombe-Huntington,Jasmin Coulombe-Huntington,Elizabeth Dann,Matija Dreze,Amélie Dricot,Changyu Fan,Eric A. Franzosa,Eric A. Franzosa,Fana Gebreab,Bryan J. Gutierrez,Madeleine F. Hardy,Mike Jin,Shuli Kang,Ruth Kiros,Guan Ning Lin,Katja Luck,Andrew MacWilliams,Jörg Menche,Jörg Menche,Ryan R. Murray,Alexandre Palagi,Matthew M. Poulin,Xavier Rambout,Xavier Rambout,John Rasla,Patrick Reichert,Viviana Romero,Elien Ruyssinck,Julie M. Sahalie,Annemarie Scholz,Akash A. Shah,Amitabh Sharma,Amitabh Sharma,Yun Shen,Kerstin Spirohn,Stanley Tam,Alexander O. Tejeda,Shelly A. Trigg,Jean-Claude Twizere,Jean-Claude Twizere,Kerwin Vega,Jennifer M. Walsh,Michael E. Cusick,Yu Xia,Yu Xia,Albert-László Barabási,Albert-László Barabási,Albert-László Barabási,Lilia M. Iakoucheva,Patrick Aloy,Javier De Las Rivas,Jan Tavernier,Michael A. Calderwood,David E. Hill,Tong Hao,Frederick P. Roth,Marc Vidal +80 more
TL;DR: The map uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.
Journal ArticleDOI
Evidence for Network Evolution in an Arabidopsis Interactome Map
Matija Dreze,Anne-Ruxandra Carvunis,Benoit Charloteaux,Mary Galli,Samuel J. Pevzner,Murat Tasan,Yong-Yeol Ahn,Padmavathi Balumuri,Albert-László Barabási,Vanessa Bautista,Pascal Braun,Danielle Byrdsong,Huaming Chen,Jonathan D. Chesnut,Michael E. Cusick,Jeffery L. Dangl,Chris de los Reyes,Amélie Dricot,Melissa Duarte,Joseph R. Ecker,Changyu Fan,Lantian Gai,Fana Gebreab,Gourab Ghoshal,Patrick Gilles,Bryan J. Gutierrez,Tong Hao,David E. Hill,Christopher Kim,Rosa Cheuk Kim,Claire Lurin,Andrew MacWilliams,Uday Matrubutham,Tijana Milenkovic,Jyotika Mirchandani,Dario Monachello,Jonathan D. Moore,M. Shahid Mukhtar,Eric Olivares,Suswapna Patnaik,Matthew M. Poulin,Natasa Przulj,Rosa Quan,Sabrina Rabello,Gopalakrishna Ramaswamy,Patrick Reichert,Edward A. Rietman,Thomas Rolland,Viviana Romero,Frederick P. Roth,Balaji Santhanam,Robert J. Schmitz,Paul Shinn,William Spooner,Joshua C. Stein,Geetha M. Swamilingiah,Stanley Tam,Jean Vandenhaute,Marc Vidal,Selma Waaijers,Doreen Ware,Evan M. Weiner,Stacy Wu,Junshi Yazaki +63 more
TL;DR: A proteome-wide binary protein-protein interaction map for the interactome network of the plant Arabidopsis thaliana containing about 6200 highly reliable interactions between about 2700 proteins is described.
Journal ArticleDOI
A reference map of the human binary protein interactome
Katja Luck,Dae-Kyum Kim,Luke Lambourne,Kerstin Spirohn,Bridget E. Begg,Wenting Bian,Ruth Brignall,Tiziana M. Cafarelli,Francisco J. Campos-Laborie,Benoit Charloteaux,Dong-Sic Choi,Atina G. Cote,Meaghan Daley,Steven Deimling,Alice Desbuleux,Amélie Dricot,Marinella Gebbia,Madeleine F. Hardy,Nishka Kishore,Jennifer J. Knapp,István Kovács,István Kovács,Irma Lemmens,Irma Lemmens,Miles W. Mee,Joseph C. Mellor,Carl Pollis,Carles Pons,Aaron Richardson,Sadie Schlabach,Bridget Teeking,Anupama Yadav,Mariana Babor,Dawit Balcha,Omer Basha,Christian Bowman-Colin,Suet-Feung Chin,Soon Gang Choi,Claudia Colabella,Georges Coppin,Cassandra D’Amata,David De Ridder,Steffi De Rouck,Steffi De Rouck,Miquel Duran-Frigola,Hanane Ennajdaoui,Florian Goebels,Liana Goehring,Anjali Gopal,Ghazal Haddad,Elodie Hatchi,Mohamed Helmy,Yves Jacob,Yves Jacob,Yoseph Kassa,Serena Landini,Roujia Li,Natascha van Lieshout,Andrew MacWilliams,Dylan Markey,Joseph N. Paulson,Joseph N. Paulson,Sudharshan Rangarajan,John Rasla,Ashyad Rayhan,Thomas Rolland,Adriana San-Miguel,Yun Shen,Dayag Sheykhkarimli,Gloria M. Sheynkman,Eyal Simonovsky,Murat Tasan,Alexander O. Tejeda,Vincent Tropepe,Jean-Claude Twizere,Yang Wang,Robert J. Weatheritt,Jochen Weile,Yu Xia,Yu Xia,Xinping Yang,Esti Yeger-Lotem,Quan Zhong,Patrick Aloy,Gary D. Bader,Javier De Las Rivas,Suzanne Gaudet,Tong Hao,Janusz Rak,Jan Tavernier,Jan Tavernier,David E. Hill,Marc Vidal,Frederick P. Roth,Michael A. Calderwood +94 more
TL;DR: The utility of HuRI is demonstrated in identifying the specific subcellular roles of protein–protein interactions and in identifying potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases.
Journal ArticleDOI
Proto-genes and de novo gene birth
Anne-Ruxandra Carvunis,Thomas Rolland,Ilan Wapinski,Michael A. Calderwood,Muhammed A. Yildirim,Nicolas Simonis,Nicolas Simonis,Benoit Charloteaux,Benoit Charloteaux,César A. Hidalgo,Justin Barbette,Balaji Santhanam,Gloria A. Brar,Jonathan S. Weissman,Aviv Regev,Aviv Regev,Nicolas Thierry-Mieg,Michael E. Cusick,Marc Vidal +18 more
TL;DR: In this article, the authors formalize an evolutionary model according to which functional genes evolve de novo through transitory proto-genes generated by widespread translational activity in non-genic sequences.
Journal ArticleDOI
A chaperome subnetwork safeguards proteostasis in aging and neurodegenerative disease.
Marc Brehme,Cindy Voisine,Thomas Rolland,Shinichiro Wachi,James Soper,Yitan Zhu,Kai Orton,Adriana Villella,Dan Garza,Marc Vidal,Hui Ge,Richard I. Morimoto +11 more
TL;DR: A critical chaperome subnetwork that functions in aging and disease is identified using function, localization, interactome, and expression data sets to identify repression and induction clusters in human brain aging.