G
Genki Terashi
Researcher at Purdue University
Publications - 80
Citations - 1190
Genki Terashi is an academic researcher from Purdue University. The author has contributed to research in topics: Protein structure prediction & Computer science. The author has an hindex of 14, co-authored 68 publications receiving 764 citations. Previous affiliations of Genki Terashi include Max Planck Society & Kitasato University.
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Journal ArticleDOI
Community-wide assessment of protein-interface modeling suggests improvements to design methodology
Sarel J. Fleishman,Sarel J. Fleishman,Timothy A. Whitehead,Eva-Maria Strauch,Jacob E. Corn,Jacob E. Corn,Sanbo Qin,Huan-Xiang Zhou,Julie C. Mitchell,Omar N. A. Demerdash,Mayuko Takeda-Shitaka,Genki Terashi,Iain H. Moal,Xiaofan Li,Paul A. Bates,Martin Zacharias,Hahnbeom Park,Junsu Ko,Hasup Lee,Chaok Seok,Thomas Bourquard,Julie Bernauer,Anne Poupon,Jérôme Azé,Seren Soner,Şefik Kerem Ovali,Pemra Ozbek,Nir Ben Tal,Turkan Haliloglu,Howook Hwang,Thom Vreven,Brian G. Pierce,Zhiping Weng,Laura Pérez-Cano,Carles Pons,Juan Fernández-Recio,Fan Jiang,Feng Yang,Xinqi Gong,Libin Cao,Xianjin Xu,Bin Liu,Panwen Wang,Chunhua Li,Cunxin Wang,Charles H. Robert,Mainak Guharoy,Shiyong Liu,Yangyu Huang,Lin Li,Dachuan Guo,Ying Chen,Yi Xiao,Nir London,Zohar Itzhaki,Ora Schueler-Furman,Yuval Inbar,Vladimir Potapov,Mati Cohen,Gideon Schreiber,Yuko Tsuchiya,Eiji Kanamori,Daron M. Standley,Haruki Nakamura,Kengo Kinoshita,C.M. Driggers,Robert G. Hall,Jessica L. Morgan,Victor L. Hsu,Jian Zhan,Yuedong Yang,Yaoqi Zhou,Panagiotis L. Kastritis,Alexandre M. J. J. Bonvin,Weiyi Zhang,Carlos J. Camacho,Krishna Praneeth Kilambi,Aroop Sircar,Jeffrey J. Gray,Masahito Ohue,Nobuyuki Uchikoga,Yuri Matsuzaki,Takashi Ishida,Yutaka Akiyama,Raed Khashan,Stephen Bush,Denis Fouches,Alexander Tropsha,Juan Esquivel-Rodríguez,Daisuke Kihara,P. Benjamin Stranges,Ron Jacak,Brian Kuhlman,Sheng-You Huang,Xiaoqin Zou,Shoshana J. Wodak,Joël Janin,David Baker +97 more
TL;DR: A number of designed protein-protein interfaces with very favorable computed binding energies but which do not appear to be formed in experiments are generated, suggesting that there may be important physical chemistry missing in the energy calculations.
Journal ArticleDOI
Community-wide Evaluation of Methods for Predicting the Effect of Mutations on Protein-Protein Interactions
Rocco Moretti,Sarel J. Fleishman,Rudi Agius,Mieczyslaw Torchala,Paul A. Bates,Panagiotis L. Kastritis,João P. G. L. M. Rodrigues,Mikael Trellet,Alexandre M. J. J. Bonvin,Meng Cui,Marianne Rooman,Dimitri Gillis,Yves Dehouck,Iain H. Moal,Miguel Romero-Durana,Laura Pérez-Cano,Chiara Pallara,Brian Jimenez,Juan Fernández-Recio,Samuel C. Flores,Michael S. Pacella,Krishna Praneeth Kilambi,Jeffrey J. Gray,Petr Popov,Petr Popov,Sergei Grudinin,Sergei Grudinin,Juan Esquivel-Rodríguez,Daisuke Kihara,Nan Zhao,Dmitry Korkin,Xiaolei Zhu,Omar N. A. Demerdash,Julie C. Mitchell,Eiji Kanamori,Yuko Tsuchiya,Haruki Nakamura,Hasup Lee,Hahnbeom Park,Chaok Seok,Jamica Sarmiento,Shide Liang,Shusuke Teraguchi,Daron M. Standley,Hiromitsu Shimoyama,Genki Terashi,Mayuko Takeda-Shitaka,Mitsuo Iwadate,Hideaki Umeyama,Dmitri Beglov,David R. Hall,Dima Kozakov,Sandor Vajda,Brian G. Pierce,Howook Hwang,Thom Vreven,Zhiping Weng,Yangyu Huang,Haotian Li,Xiufeng Yang,Xiaofeng Ji,Shiyong Liu,Yi Xiao,Martin Zacharias,Sanbo Qin,Huan-Xiang Zhou,Sheng-You Huang,Xiaoqin Zou,Sameer Velankar,Joël Janin,Shoshana J. Wodak,David Baker +71 more
TL;DR: A community‐wide assessment of methods to predict the effects of mutations on protein–protein interactions found that large‐scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies.
Journal ArticleDOI
De novo main-chain modeling for EM maps using MAINMAST
Genki Terashi,Daisuke Kihara +1 more
TL;DR: A fully automated de novo structure modeling method, MAINMAST, which builds three-dimensional models of a protein from a near-atomic resolution EM map and directly traces the protein’s main-chain and identifies Cα positions as tree-graph structures in the EM map.
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
Protein docking model evaluation by 3D deep convolutional neural networks.
TL;DR: A convolutional deep neural network-based approach named DOVE (DOcking decoy selection with Voxel-based deep neural nEtwork) for evaluating protein docking models and considers atomic interaction types and their energetic contributions as input features applied to the neural network.