Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Ian, Sillitoe"'
Autor:
Vaishali P. Waman, Paul Ashford, Su Datt Lam, Neeladri Sen, Mahnaz Abbasian, Laurel Woodridge, Yonathan Goldtzvik, Nicola Bordin, Jiaxin Wu, Ian Sillitoe, Christine A. Orengo
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing
Externí odkaz:
https://doaj.org/article/605cb58ddbd04446aebe2817798cb034
Autor:
Nicola Bordin, Ian Sillitoe, Vamsi Nallapareddy, Clemens Rauer, Su Datt Lam, Vaishali P. Waman, Neeladri Sen, Michael Heinzinger, Maria Littmann, Stephanie Kim, Sameer Velankar, Martin Steinegger, Burkhard Rost, Christine Orengo
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-12 (2023)
A new protein domain classification protocol incorporating deep learning strategies for detecting sequence and structure similarities between domain is used to systematically study and analyse the predicted AlphaFold2 structural models for proteins o
Externí odkaz:
https://doaj.org/article/c077b0db693c4a798c9578aeecb33276
Autor:
Elena Rojano, Fernando M. Jabato, James R. Perkins, José Córdoba-Caballero, Federico García-Criado, Ian Sillitoe, Christine Orengo, Juan A. G. Ranea, Pedro Seoane-Zonjic
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-19 (2022)
Abstract Background Protein function prediction remains a key challenge. Domain composition affects protein function. Here we present DomFun, a Ruby gem that uses associations between protein domains and functions, calculated using multiple indices b
Externí odkaz:
https://doaj.org/article/04cbfecf2a7e4f32bcde7c8858ce38c0
Publikováno v:
PLoS Computational Biology, Vol 18, Iss 12, p e1010346 (2022)
Peripheral membrane proteins (PMPs) include a wide variety of proteins that have in common to bind transiently to the chemically complex interfacial region of membranes through their interfacial binding site (IBS). In contrast to protein-protein or p
Externí odkaz:
https://doaj.org/article/baa78e879db243cb9148d40ca13e6c12
Autor:
Tolulope Adeyelu, Nicola Bordin, Vaishali P. Waman, Marta Sadlej, Ian Sillitoe, Aurelio A. Moya-Garcia, Christine A. Orengo
Publikováno v:
Biomolecules, Vol 13, Iss 2, p 277 (2023)
Protein kinases are important targets for treating human disorders, and they are the second most targeted families after G-protein coupled receptors. Several resources provide classification of kinases into evolutionary families (based on sequence ho
Externí odkaz:
https://doaj.org/article/61ece3c01e2b445daa1171daf779add8
Autor:
Naihui Zhou, Yuxiang Jiang, Timothy R. Bergquist, Alexandra J. Lee, Balint Z. Kacsoh, Alex W. Crocker, Kimberley A. Lewis, George Georghiou, Huy N. Nguyen, Md Nafiz Hamid, Larry Davis, Tunca Dogan, Volkan Atalay, Ahmet S. Rifaioglu, Alperen Dalkıran, Rengul Cetin Atalay, Chengxin Zhang, Rebecca L. Hurto, Peter L. Freddolino, Yang Zhang, Prajwal Bhat, Fran Supek, José M. Fernández, Branislava Gemovic, Vladimir R. Perovic, Radoslav S. Davidović, Neven Sumonja, Nevena Veljkovic, Ehsaneddin Asgari, Mohammad R.K. Mofrad, Giuseppe Profiti, Castrense Savojardo, Pier Luigi Martelli, Rita Casadio, Florian Boecker, Heiko Schoof, Indika Kahanda, Natalie Thurlby, Alice C. McHardy, Alexandre Renaux, Rabie Saidi, Julian Gough, Alex A. Freitas, Magdalena Antczak, Fabio Fabris, Mark N. Wass, Jie Hou, Jianlin Cheng, Zheng Wang, Alfonso E. Romero, Alberto Paccanaro, Haixuan Yang, Tatyana Goldberg, Chenguang Zhao, Liisa Holm, Petri Törönen, Alan J. Medlar, Elaine Zosa, Itamar Borukhov, Ilya Novikov, Angela Wilkins, Olivier Lichtarge, Po-Han Chi, Wei-Cheng Tseng, Michal Linial, Peter W. Rose, Christophe Dessimoz, Vedrana Vidulin, Saso Dzeroski, Ian Sillitoe, Sayoni Das, Jonathan Gill Lees, David T. Jones, Cen Wan, Domenico Cozzetto, Rui Fa, Mateo Torres, Alex Warwick Vesztrocy, Jose Manuel Rodriguez, Michael L. Tress, Marco Frasca, Marco Notaro, Giuliano Grossi, Alessandro Petrini, Matteo Re, Giorgio Valentini, Marco Mesiti, Daniel B. Roche, Jonas Reeb, David W. Ritchie, Sabeur Aridhi, Seyed Ziaeddin Alborzi, Marie-Dominique Devignes, Da Chen Emily Koo, Richard Bonneau, Vladimir Gligorijević, Meet Barot, Hai Fang, Stefano Toppo, Enrico Lavezzo, Marco Falda, Michele Berselli, Silvio C.E. Tosatto, Marco Carraro, Damiano Piovesan, Hafeez Ur Rehman, Qizhong Mao, Shanshan Zhang, Slobodan Vucetic, Gage S. Black, Dane Jo, Erica Suh, Jonathan B. Dayton, Dallas J. Larsen, Ashton R. Omdahl, Liam J. McGuffin, Danielle A. Brackenridge, Patricia C. Babbitt, Jeffrey M. Yunes, Paolo Fontana, Feng Zhang, Shanfeng Zhu, Ronghui You, Zihan Zhang, Suyang Dai, Shuwei Yao, Weidong Tian, Renzhi Cao, Caleb Chandler, Miguel Amezola, Devon Johnson, Jia-Ming Chang, Wen-Hung Liao, Yi-Wei Liu, Stefano Pascarelli, Yotam Frank, Robert Hoehndorf, Maxat Kulmanov, Imane Boudellioua, Gianfranco Politano, Stefano Di Carlo, Alfredo Benso, Kai Hakala, Filip Ginter, Farrokh Mehryary, Suwisa Kaewphan, Jari Björne, Hans Moen, Martti E.E. Tolvanen, Tapio Salakoski, Daisuke Kihara, Aashish Jain, Tomislav Šmuc, Adrian Altenhoff, Asa Ben-Hur, Burkhard Rost, Steven E. Brenner, Christine A. Orengo, Constance J. Jeffery, Giovanni Bosco, Deborah A. Hogan, Maria J. Martin, Claire O’Donovan, Sean D. Mooney, Casey S. Greene, Predrag Radivojac, Iddo Friedberg
Publikováno v:
Genome Biology, Vol 20, Iss 1, Pp 1-23 (2019)
Abstract Background The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Results Here, we report on the results of the third C
Externí odkaz:
https://doaj.org/article/4c2b017b155b41ceab8d6d078186cafa
Publikováno v:
Frontiers in Molecular Biosciences, Vol 8 (2021)
This article is dedicated to the memory of Cyrus Chothia, who was a leading light in the world of protein structure evolution. His elegant analyses of protein families and their mechanisms of structural and functional evolution provided important evo
Externí odkaz:
https://doaj.org/article/53032adb227f4447a2f1b55fc38c011f
Autor:
Typhaine Paysan-Lafosse, Matthias Blum, Sara Chuguransky, Tiago Grego, Beatriz Lázaro Pinto, Gustavo A Salazar, Maxwell L Bileschi, Peer Bork, Alan Bridge, Lucy Colwell, Julian Gough, Daniel H Haft, Ivica Letunić, Aron Marchler-Bauer, Huaiyu Mi, Darren A Natale, Christine A Orengo, Arun P Pandurangan, Catherine Rivoire, Christian J A Sigrist, Ian Sillitoe, Narmada Thanki, Paul D Thomas, Silvio C E Tosatto, Cathy H Wu, Alex Bateman
Publikováno v:
Nucleic Acids Research. 51:D418-D427
The InterPro database (https://www.ebi.ac.uk/interpro/) provides an integrative classification of protein sequences into families, and identifies functionally important domains and conserved sites. Here, we report recent developments with InterPro (v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::153bbcbf1ab56d7f060b0d1aec9c1f19
https://doi.org/10.1093/nar/gkac993
https://doi.org/10.1093/nar/gkac993
Autor:
Brinda Vallat, Gerardo Tauriello, Stefan Bienert, Juergen Haas, Benjamin M. Webb, Augustin Žídek, Wei Zheng, Ezra Peisach, Dennis W. Piehl, Ivan Anischanka, Ian Sillitoe, James Tolchard, Mihaly Varadi, David Baker, Christine Orengo, Yang Zhang, Jeffrey C. Hoch, Genji Kurisu, Ardan Patwardhan, Sameer Velankar, Stephen K. Burley, Andrej Sali, Torsten Schwede, Helen M. Berman, John D. Westbrook
ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery ofFindable, Accessible, Interoperable, andReusable(FAIR) data to users worldwide. It is an extension of t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4c9e257587c0731991f7a08cfd0d716f
https://doi.org/10.1101/2022.12.06.518550
https://doi.org/10.1101/2022.12.06.518550
Autor:
Neeladri Sen, Ivan Anishchenko, Nicola Bordin, Ian Sillitoe, Sameer Velankar, David Baker, Christine Orengo
Publikováno v:
Briefings in Bioinformatics. 23
Mutations in human proteins lead to diseases. The structure of these proteins can help understand the mechanism of such diseases and develop therapeutics against them. With improved deep learning techniques, such as RoseTTAFold and AlphaFold, we can
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e617bc530a31acf1fd39687be4f01c3
https://doi.org/10.1093/bib/bbac187
https://doi.org/10.1093/bib/bbac187