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Nives Škunca
Researcher at Swiss Institute of Bioinformatics
Publications - 30
Citations - 8236
Nives Škunca is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: Ontology (information science) & Protein function prediction. The author has an hindex of 22, co-authored 30 publications receiving 6730 citations. Previous affiliations of Nives Škunca include University College London & Baylor College of Medicine.
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Journal ArticleDOI
REVIGO Summarizes and Visualizes Long Lists of Gene Ontology Terms
TL;DR: REVIGO is a Web server that summarizes long, unintelligible lists of GO terms by finding a representative subset of the terms using a simple clustering algorithm that relies on semantic similarity measures.
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
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang,Tal Ronnen Oron,Wyatt T. Clark,Asma R. Bankapur,Daniel D'Andrea,Rosalba Lepore,Christopher S. Funk,Indika Kahanda,Karin Verspoor,Asa Ben-Hur,Da Chen Emily Koo,Duncan Penfold-Brown,Dennis Shasha,Noah Youngs,Richard Bonneau,Alexandra Lin,Sayed Mohammad Ebrahim Sahraeian,Pier Luigi Martelli,Giuseppe Profiti,Rita Casadio,Renzhi Cao,Zhaolong Zhong,Jianlin Cheng,Adrian M. Altenhoff,Adrian M. Altenhoff,Nives Škunca,Nives Škunca,Christophe Dessimoz,Christophe Dessimoz,Christophe Dessimoz,Tunca Doğan,Kai Hakala,Suwisa Kaewphan,Farrokh Mehryary,Tapio Salakoski,Filip Ginter,Hai Fang,Ben Smithers,Matt E. Oates,Julian Gough,Petri Törönen,Patrik Koskinen,Liisa Holm,Ching-Tai Chen,Wen-Lian Hsu,Kevin Bryson,Domenico Cozzetto,Federico Minneci,David T. Jones,Samuel Chapman,Dukka Bkc,Ishita K. Khan,Daisuke Kihara,Dan Ofer,Nadav Rappoport,Amos Stern,Elena Cibrian-Uhalte,Paul Denny,Rebecca E. Foulger,Reija Hieta,Duncan Legge,Ruth C. Lovering,Michele Magrane,Anna N. Melidoni,Prudence Mutowo-Meullenet,Klemens Pichler,Aleksandra Shypitsyna,Biao Li,Pooya Zakeri,Pooya Zakeri,Sarah ElShal,Sarah ElShal,Léon-Charles Tranchevent,Léon-Charles Tranchevent,Sayoni Das,Natalie L. Dawson,David A. Lee,Jonathan G. Lees,Ian Sillitoe,Prajwal Bhat,Tamás Nepusz,Alfonso E. Romero,Rajkumar Sasidharan,Haixuan Yang,Alberto Paccanaro,Jesse Gillis,Adriana E. Sedeno-Cortes,Paul Pavlidis,Shou Feng,Juan Miguel Cejuela,Tatyana Goldberg,Tobias Hamp,Lothar Richter,Asaf Salamov,Toni Gabaldón,Toni Gabaldón,Marina Marcet-Houben,Fran Supek,Fran Supek,Qingtian Gong,Wei Ning,Yuanpeng Zhou,Weidong Tian,Marco Falda,Paolo Fontana,Enrico Lavezzo,Stefano Toppo,Carlo Ferrari,Manuel Giollo,Damiano Piovesan,Silvio C. E. Tosatto,Angela del Pozo,José M. Fernández,Paolo Maietta,Alfonso Valencia,Michael L. Tress,Alfredo Benso,Stefano Di Carlo,Gianfranco Politano,Alessandro Savino,Hafeez Ur Rehman,Matteo Re,Marco Mesiti,Giorgio Valentini,Joachim W. Bargsten,Aalt D. J. van Dijk,Branislava Gemovic,Sanja Glisic,Vladmir Perovic,Veljko Veljkovic,Nevena Veljkovic,Danillo C Almeida-E-Silva,Ricardo Z. N. Vêncio,Malvika Sharan,Jörg Vogel,Lakesh Kansakar,Shanshan Zhang,Slobodan Vucetic,Zheng Wang,Michael J.E. Sternberg,Mark N. Wass,Rachael P. Huntley,Maria Jesus Martin,Claire O'Donovan,Peter N. Robinson,Yves Moreau,Anna Tramontano,Patricia C. Babbitt,Steven E. Brenner,Michal Linial,Christine A. Orengo,Burkhard Rost,Casey S. Greene,Sean D. Mooney,Iddo Friedberg,Iddo Friedberg,Predrag Radivojac +156 more
TL;DR: The second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function, was conducted by as mentioned in this paper. But the results of the CAFA2 assessment are limited.
Additional file 1 of An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Yuxiang Jiang,Tal Ronnen Oron,Wyatt T. Clark,Asma R. Bankapur,Daniel D'Andrea,Rosalba Lepore,Christopher S. Funk,Indika Kahanda,Karin Verspoor,Asa Ben-Hur,Da Chen Emily Koo,Duncan Penfold-Brown,Dennis Shasha,Noah Youngs,Richard Bonneau,Alexandra Lin,Sayed M. E. Sahraeian,Pier Luigi Martelli,Giuseppe Profiti,Rita Casadio,Renzhi Cao,Zhaolong Zhong,Jianlin Cheng,Adrian M. Altenhoff,Nives Škunca,Christophe Dessimoz,Tunca Doğan,Kai Hakala,Suwisa Kaewphan,Farrokh Mehryary,Tapio Salakoski,Filip Ginter,Hai Fang,Ben Smithers,Matt E. Oates,Julian Gough,Petri Törönen,Patrik Koskinen,Liisa Holm,Ching-Tai Chen,Wen-Lian Hsu,Kevin Bryson,Domenico Cozzetto,Federico Minneci,David T. Jones,Samuel Chapman,Dukka Bkc,Ishita K. Khan,Daisuke Kihara,Dan Ofer,Nadav Rappoport,Amos Stern,Elena Cibrian-Uhalte,Paul Denny,Rebecca E. Foulger,Reija Hieta,Duncan Legge,Ruth C. Lovering,Michele Magrane,Anna N. Melidoni,Prudence Mutowo-Meullenet,Klemens Pichler,Aleksandra Shypitsyna,Biao Li,Pooya Zakeri,Sarah ElShal,Léon-Charles Tranchevent,Sayoni Das,Natalie L. Dawson,David A. Lee,Jonathan G. Lees,Ian Sillitoe,Prajwal Bhat,Tamás Nepusz,Alfonso E. Romero,Rajkumar Sasidharan,Haixuan Yang,Alberto Paccanaro,Jesse Gillis,Adriana E. Sedeño Cortés,Paul Pavlidis,Shou Feng,Juan Miguel Cejuela,Tatyana Goldberg,Tobias Hamp,Lothar Richter,Asaf Salamov,Toni Gabaldón,Marina Marcet-Houben,Fran Supek,Qingtian Gong,Wei Ning,Yuanpeng Zhou,Weidong Tian,Marco Falda,Paolo Fontana,Enrico Lavezzo,Stefano Toppo,Carlo Ferrari,Manuel Giollo,Damiano Piovesan,Silvio C. E. Tosatto,Angela del Pozo,José M. Fernández,Paolo Maietta,Alfonso Valencia,Michael L. Tress,Alfredo Benso,Stefano Di Carlo,Gianfranco Politano,Alessandro Savino,Hafeez Ur Rehman,Matteo Re,Marco Mesiti,Giorgio Valentini,Joachim W. Bargsten,Aalt D. J. van Dijk,Branislava Gemovic,Sanja Glisic,Vladmir Perovic,Veljko Veljkovic,Nevena Veljkovic,Danillo C. Almeida e. Silva,Ricardo Z. N. Vêncio,Malvika Sharan,Jörg Vogel,Lakesh Kansakar,Shanshan Zhang,Slobodan Vucetic,Zheng Wang,Michael J.E. Sternberg,Mark N. Wass,Rachael P. Huntley,Maria Jesus Martin,Claire O'Donovan,Peter N. Robinson,Yves Moreau,Anna Tramontano,Patricia C. Babbitt,Steven E. Brenner,Michal Linial,Christine A. Orengo,Burkhard Rost,Casey S. Greene,Sean D. Mooney,Iddo Friedberg,Predrag Radivojac +146 more
TL;DR: The second critical assessment of functional annotation (CAFA) conducted, a timed challenge to assess computational methods that automatically assign protein function, revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies.
Journal ArticleDOI
The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements
Adrian M. Altenhoff,Nives Škunca,Nives Škunca,Nives Škunca,Natasha Glover,Clément-Marie Train,Anna Sueki,Ivana Piližota,Kevin Gori,Bartlomiej Tomiczek,Steven Müller,Henning Redestig,Gaston H. Gonnet,Christophe Dessimoz +13 more
TL;DR: Six major new developments in OMA are presented: a new web interface; Gene Ontology function predictions as part of the OMA pipeline; better support for plant genomes and in particular homeologs in the wheat genome; a new synteny viewer providing the genomic context of orthologs; statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format.