D
Denis Krompass
Researcher at Technische Universität München
Publications - 2
Citations - 928
Denis Krompass is an academic researcher from Technische Universität München. The author has contributed to research in topics: Protein function prediction & Inference. The author has an hindex of 2, co-authored 2 publications receiving 811 citations.
Papers
More filters
Journal ArticleDOI
A large-scale evaluation of computational protein function prediction
Predrag Radivojac,Wyatt T. Clark,Tal Ronnen Oron,Alexandra M. Schnoes,Tobias Wittkop,Artem Sokolov,Artem Sokolov,Kiley Graim,Christopher S. Funk,Karin Verspoor,Asa Ben-Hur,Gaurav Pandey,Gaurav Pandey,Jeffrey M. Yunes,Ameet Talwalkar,Susanna Repo,Susanna Repo,Michael L Souza,Damiano Piovesan,Rita Casadio,Zheng Wang,Jianlin Cheng,Hai Fang,Julian Gough,Patrik Koskinen,Petri Törönen,Jussi Nokso-Koivisto,Liisa Holm,Domenico Cozzetto,Daniel W. A. Buchan,Kevin Bryson,David T. Jones,Bhakti Limaye,Harshal Inamdar,Avik Datta,Sunitha K Manjari,Rajendra Joshi,Meghana Chitale,Daisuke Kihara,Andreas Martin Lisewski,Serkan Erdin,Eric Venner,Olivier Lichtarge,Robert Rentzsch,Haixuan Yang,Alfonso E. Romero,Prajwal Bhat,Alberto Paccanaro,Tobias Hamp,Rebecca Kaßner,Stefan Seemayer,Esmeralda Vicedo,Christian Schaefer,Dominik Achten,Florian Auer,Ariane Boehm,Tatjana Braun,Maximilian Hecht,Mark Heron,Peter Hönigschmid,Thomas A. Hopf,Stefanie Kaufmann,Michael Kiening,Denis Krompass,Cedric Landerer,Yannick Mahlich,Manfred Roos,Jari Björne,Tapio Salakoski,Andrew Wong,Hagit Shatkay,Hagit Shatkay,Fanny Gatzmann,Ingolf Sommer,Mark N. Wass,Michael J.E. Sternberg,Nives Škunca,Fran Supek,Matko Bošnjak,Panče Panov,Sašo Džeroski,Tomislav Šmuc,Yiannis A. I. Kourmpetis,Yiannis A. I. Kourmpetis,Aalt D. J. van Dijk,Cajo J. F. ter Braak,Yuanpeng Zhou,Qingtian Gong,Xinran Dong,Weidong Tian,Marco Falda,Paolo Fontana,Enrico Lavezzo,Barbara Di Camillo,Stefano Toppo,Liang Lan,Nemanja Djuric,Yuhong Guo,Slobodan Vucetic,Amos Marc Bairoch,Amos Marc Bairoch,Michal Linial,Patricia C. Babbitt,Steven E. Brenner,Christine A. Orengo,Burkhard Rost,Sean D. Mooney,Iddo Friedberg +107 more
TL;DR: Today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets, and there is considerable need for improvement of currently available tools.
Journal ArticleDOI
Homology-based inference sets the bar high for protein function prediction.
Tobias Hamp,Rebecca Kassner,Stefan Seemayer,Esmeralda Vicedo,Christian Schaefer,Dominik Achten,Florian Auer,Ariane Boehm,Tatjana Braun,Maximilian Hecht,Mark Heron,Peter Hönigschmid,Thomas A. Hopf,Stefanie Kaufmann,Michael Kiening,Denis Krompass,Cedric Landerer,Yannick Mahlich,Manfred Roos,Burkhard Rost +19 more
TL;DR: This work describes a few methods that predict protein function exclusively through homology and proposes a new rigorous measure to compare predicted and experimental annotations that puts more emphasis on the details of protein function than the other measures employed by CAFA and may best reflect the expectations of users.