An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Autor: Jiang, Yuxiang, Oron, Tal Ronnen, Clark, Wyatt T, Bankapur, Asma R, D'Andrea, Daniel, Lepore, Rosalba, Funk, Christopher S, Kahanda, Indika, Verspoor, Karin M, Ben-Hur, Asa, Koo, Emily, Penfold-Brown, Duncan, Shasha, Dennis, Youngs, Noah, Bonneau, Richard, Lin, Alexandra, Sahraeian, Sayed ME, Martelli, Pier Luigi, Profiti, Giuseppe, Casadio, Rita, Cao, Renzhi, Zhong, Zhaolong, Cheng, Jianlin, Altenhoff, Adrian, Skunca, Nives, Dessimoz, Christophe, Dogan, Tunca, Hakala, Kai, Kaewphan, Suwisa, Mehryary, Farrokh, Salakoski, Tapio, Ginter, Filip, Fang, Hai, Smithers, Ben, Oates, Matt, Gough, Julian, Törönen, Petri, Koskinen, Patrik, Holm, Liisa, Chen, Ching-Tai, Hsu, Wen-Lian, Bryson, Kevin, Cozzetto, Domenico, Minneci, Federico, Jones, David T, Chapman, Samuel, C., Dukka B K., Khan, Ishita K, Kihara, Daisuke, Ofer, Dan, Rappoport, Nadav, Stern, Amos, Cibrian-Uhalte, Elena, Denny, Paul, Foulger, Rebecca E, Hieta, Reija, Legge, Duncan, Lovering, Ruth C, Magrane, Michele, Melidoni, Anna N, Mutowo-Meullenet, Prudence, Pichler, Klemens, Shypitsyna, Aleksandra, Li, Biao, Zakeri, Pooya, ElShal, Sarah, Tranchevent, Léon-Charles, Das, Sayoni, Dawson, Natalie L, Lee, David, Lees, Jonathan G, Sillitoe, Ian, Bhat, Prajwal, Nepusz, Tamás, Romero, Alfonso E, Sasidharan, Rajkumar, Yang, Haixuan, Paccanaro, Alberto, Gillis, Jesse, Sedeño-Cortés, Adriana E, Pavlidis, Paul, Feng, Shou, Cejuela, Juan M, Goldberg, Tatyana, Hamp, Tobias, Richter, Lothar, Salamov, Asaf, Gabaldon, Toni, Marcet-Houben, Marina, Supek, Fran, Gong, Qingtian, Ning, Wei, Zhou, Yuanpeng, Tian, Weidong, Falda, Marco, Fontana, Paolo, Lavezzo, Enrico, Toppo, Stefano, Ferrari, Carlo, Giollo, Manuel, Piovesan, Damiano, Tosatto, Silvio, del Pozo, Angela, Fernández, José M, Maietta, Paolo, Valencia, Alfonso, Tress, Michael L, Benso, Alfredo, Di Carlo, Stefano, Politano, Gianfranco, Savino, Alessandro, Rehman, Hafeez Ur, Re, Matteo, Mesiti, Marco, Valentini, Giorgio, Bargsten, Joachim W, van Dijk, Aalt DJ, Gemovic, Branislava, Glisic, Sanja, Perovic, Vladmir, Veljkovic, Veljko, Veljkovic, Nevena, Almeida-e-Silva, Danillo C, Vencio, Ricardo ZN, Sharan, Malvika, Vogel, Jörg, Kansakar, Lakesh, Zhang, Shanshan, Vucetic, Slobodan, Wang, Zheng, Sternberg, Michael JE, Wass, Mark N, Huntley, Rachael P, Martin, Maria J, O'Donovan, Claire, Robinson, Peter N, Moreau, Yves, Tramontano, Anna, Babbitt, Patricia C, Brenner, Steven E, Linial, Michal, Orengo, Christine A, Rost, Burkhard, Greene, Casey S, Mooney, Sean D, Friedberg, Iddo, Radivojac, Predrag

Background: The increasing volume and variety of genotypic and phenotypic data is a major defining characteristic of modern biomedical sciences. At the same time, the limitations in technology for generating data and the inherently stochastic nature

Externí odkaz: http://arxiv.org/abs/1601.00891

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ProfPPIdb: Pairs of physical protein-protein interactions predicted for entire proteomes.

Autor: Tran, Linh^1,2 linh.tran@imperial.ac.uk, Hamp, Tobias², Rost, Burkhard^2,3

Publikováno v: PLoS ONE. 7/18/2018, Vol. 13 Issue 7, p1-13. 13p.

ProfPPIdb: Pairs of physical protein-protein interactions predicted for entire proteomes

Autor: Tran, Linh, Hamp, Tobias, Rost, Burkhard

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______518::4ece70e69ef768e973878fe824eaf8cd
https://mediatum.ub.tum.de/1485231

Homology-based inference sets the bar high for protein function prediction.

Autor: Hamp, Tobias¹, Kassner, Rebecca¹, Seemayer, Stefan¹, Vicedo, Esmeralda¹, Schaefer, Christian¹, Achten, Dominik¹, Auer, Florian¹, Boehm, Ariane¹, Braun, Tatjana¹, Hecht, Maximilian¹, Heron, Mark¹, Hönigschmid, Peter¹, Hopf, Thomas A.¹, Kaufmann, Stefanie¹, Kiening, Michael¹, Krompass, Denis¹, Landerer, Cedric¹, Mahlich, Yannick¹, Roos, Manfred¹, Rost, Burkhard^1,2,3 rost@in.tum.de

Publikováno v: BMC Bioinformatics. 2013, Vol. 14 Issue S3, p1-10. 10p. 4 Diagrams, 3 Charts, 1 Graph.