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Silvia Crivelli
Researcher at University of California, Davis
Publications - 38
Citations - 542
Silvia Crivelli is an academic researcher from University of California, Davis. The author has contributed to research in topics: Protein structure prediction & CASP. The author has an hindex of 13, co-authored 34 publications receiving 462 citations. Previous affiliations of Silvia Crivelli include Lawrence Berkeley National Laboratory.
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Journal ArticleDOI
Blind prediction of homo- and hetero-protein complexes: The CASP13-CAPRI experiment.
Marc F. Lensink,Guillaume Brysbaert,Nurul Nadzirin,Sameer Velankar,Raphael A. G. Chaleil,Tereza Gerguri,Paul A. Bates,Elodie Laine,Alessandra Carbone,Alessandra Carbone,Sergei Grudinin,Ren Kong,Ranran Liu,Xu Ximing,Hang Shi,Shan Chang,Miriam Eisenstein,Agnieszka S. Karczyńska,Cezary Czaplewski,Emilia A. Lubecka,Agnieszka G. Lipska,Paweł Krupa,Magdalena A. Mozolewska,Łukasz Golon,Sergey A. Samsonov,Adam Liwo,Adam Liwo,Silvia Crivelli,Guillaume Pagès,Mikhail Karasikov,Maria Kadukova,Maria Kadukova,Yumeng Yan,Sheng-You Huang,Mireia Rosell,Mireia Rosell,Luis A. Rodríguez-Lumbreras,Luis A. Rodríguez-Lumbreras,Miguel Romero-Durana,Lucía Díaz-Bueno,Juan Fernández-Recio,Juan Fernández-Recio,Charles Christoffer,Genki Terashi,Woong-Hee Shin,Tunde Aderinwale,Sai Raghavendra Maddhuri Venkata Subraman,Daisuke Kihara,Dima Kozakov,Sandor Vajda,Kathyn Porter,Dzmitry Padhorny,Israel Desta,Dmitri Beglov,Mikhail Ignatov,Sergey Kotelnikov,Sergey Kotelnikov,Iain H. Moal,David W. Ritchie,Isaure Chauvot de Beauchêne,Bernard Maigret,Marie-Dominique Devignes,Maria Elisa Ruiz Echartea,Didier Barradas-Bautista,Zhen Cao,Luigi Cavallo,Romina Oliva,Yue Cao,Yang Shen,Minkyung Baek,Taeyong Park,Hyeonuk Woo,Chaok Seok,M. Braitbard,Lirane Bitton,Dina Scheidman-Duhovny,Justas Dapkūnas,Kliment Olechnovič,Česlovas Venclovas,Petras J. Kundrotas,Saveliy Belkin,Devlina Chakravarty,Varsha D. Badal,Ilya A. Vakser,Thom Vreven,Sweta Vangaveti,Tyler M. Borrman,Zhiping Weng,Johnathan D. Guest,Ragul Gowthaman,Brian G. Pierce,Xianjin Xu,Rui Duan,Liming Qiu,Jie Hou,Benjamin Ryan Merideth,Zhiwei Ma,Jianlin Cheng,Xiaoqin Zou,Panos Koukos,Jorge Roel-Touris,Francesco Ambrosetti,Cunliang Geng,Jörg Schaarschmidt,Mikael Trellet,Adrien S. J. Melquiond,Li C. Xue,Brian Jiménez-García,Charlotte W. van Noort,Rodrigo V. Honorato,Alexandre M. J. J. Bonvin,Shoshana J. Wodak +111 more
TL;DR: CAPRI Round 46 indicates that residues in binding interfaces were less well predicted in this set of targets than in previous Rounds, providing useful insights for directions of future improvements.
Journal ArticleDOI
WeFold: a coopetition for protein structure prediction.
George A. Khoury,Adam Liwo,Firas Khatib,Firas Khatib,Hongyi Zhou,Gaurav Chopra,Gaurav Chopra,Jaume Bacardit,Leandro Oliveira Bortot,Rodrigo Antonio Faccioli,Xin Deng,Yi He,Paweł Krupa,Paweł Krupa,Jilong Li,Magdalena A. Mozolewska,Magdalena A. Mozolewska,Adam K. Sieradzan,James Smadbeck,Tomasz K Wirecki,Tomasz K Wirecki,Seth Cooper,Jeff Flatten,Kefan Xu,David Baker,Jianlin Cheng,Alexandre C. B. Delbem,Christodoulos A. Floudas,Chen Keasar,Michael Levitt,Zoran Popović,Harold A. Scheraga,Jeffrey Skolnick,Silvia Crivelli,Foldit Players +34 more
TL;DR: The first attempt at “coopetition” in scientific research applied to the protein structure prediction and refinement problems is presented and both successes and areas needing improvement as identified throughout the first WeFold experiment are described.
Journal ArticleDOI
SEA domain proteolysis determines the functional composition of dystroglycan
TL;DR: A structural model for the cleavage domain is provided that is validated by experimental analysis and discussed in the context of mucin protein and SEA domain evolution, which constitutes a control point for the modulation of its ligand‐binding properties, with therapeutic implications for muscular dystrophies.
Posted ContentDOI
Structural Learning of Proteins Using Graph Convolutional Neural Networks
TL;DR: It is shown that GCNNs are able to learn effectively from simplistic graph representations of protein structures while providing the ability to interpret what the network learns during the training and how it applies it to perform its task.
Journal ArticleDOI
ProteinShop: a tool for interactive protein manipulation and steering.
TL;DR: ProteinShop is described, a new visualization tool that streamlines and simplifies the process of determining optimal protein folds and serves as a visual framework to monitor and steer a protein structure prediction process that may be running on a remote machine.