Idioma:

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

Zhou, Naihui ; Jiang, Yuxiang ; Lee, Alexandra J ; Kacsoh, Balint Z ; Crocker, Alex W ; Georghiou, George ; Nguyen, Huy N ; Hamid, Md Nafiz ; Davis, Larry ; Atalay, Volkan ; Rifaioglu, Ahmet S ; Dalkıran, Alperen ; Cetin Atalay, Rengul ; Zhang, Chengxin ; Hurto, Rebecca L ; Freddolino, Peter L ; Supek, Fran ; Fernández, José M ; Gemovic, Branislava ; Sumonja, Neven ; Veljkovic, Nevena ; Asgari, Ehsaneddin ; Mofrad, Mohammad R K ; Savojardo, Castrense ; Martelli, Pier Luigi ; Casadio, Rita ; Boecker, Florian ; Schoof, Heiko ; Thurlby, Natalie ; McHardy, Alice C ; Renaux, Alexandre ; Saidi, Rabie ; Gough, Julian ; Freitas, Alex A ; Antczak, Magdalena ; Fabris, Fabio ; Wass, Mark N ; Hou, Jie ; Wang, Zheng ; Romero, Alfonso E ; Paccanaro, Alberto ; Yang, Haixuan ; Goldberg, Tatyana ; Zhao, Chenguang ; Holm, Liisa ; Tseng, Wei-Cheng ; Linial, Michal ; Rose, Peter W ; Dessimoz, Christophe ; Dzeroski, Saso ; Sillitoe, Ian ; Das, Sayoni ; Wan, Cen ; Fa, Rui ; Notaro, Marco ; Grossi, Giuliano ; Valentini, Giorgio ; Mesiti, Marco ; Ritchie, David W ; Aridhi, Sabeur ; Bonneau, Richard ; Gligorijević, Vladimir ; Fang, Hai ; Toppo, Stefano ; Falda, Marco ; Berselli, Michele ; Mao, Qizhong ; Black, Gage S ; Suh, Erica ; Dayton, Jonathan B ; Larsen, Dallas J ; Omdahl, Ashton R ; McGuffin, Liam J ; Brackenridge, Danielle A ; Babbitt, Patricia C ; Yunes, Jeffrey M ; Fontana, Paolo ; Zhang, Feng ; Zhu, Shanfeng ; Dai, Suyang ; Yao, Shuwei ; Cao, Renzhi ; Amezola, Miguel ; Johnson, Devon ; Liu, Yi-Wei ; Frank, Yotam ; Hoehndorf, Robert ; Kulmanov, Maxat ; Björne, Jari ; Tolvanen, Martti E E ; Salakoski, Tapio ; Altenhoff, Adrian ; Ben-Hur, Asa ; Rost, Burkhard ; Orengo, Christine A ; Bosco, Giovanni ; Martin, Maria J ; Mooney, Sean D ; Greene, Casey S ; Radivojac, Predrag

Genome Biology, 2019-11, Vol.20 (1), p.244-244, Article 244 [Periódico revisado por pares]

England: BioMed Central

Texto completo disponível

Citações Citado por

Enviar para

Título:
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
Autor: Zhou, Naihui ; Jiang, Yuxiang ; Lee, Alexandra J ; Kacsoh, Balint Z ; Crocker, Alex W ; Georghiou, George ; Nguyen, Huy N ; Hamid, Md Nafiz ; Davis, Larry ; Atalay, Volkan ; Rifaioglu, Ahmet S ; Dalkıran, Alperen ; Cetin Atalay, Rengul ; Zhang, Chengxin ; Hurto, Rebecca L ; Freddolino, Peter L ; Supek, Fran ; Fernández, José M ; Gemovic, Branislava ; Sumonja, Neven ; Veljkovic, Nevena ; Asgari, Ehsaneddin ; Mofrad, Mohammad R K ; Savojardo, Castrense ; Martelli, Pier Luigi ; Casadio, Rita ; Boecker, Florian ; Schoof, Heiko ; Thurlby, Natalie ; McHardy, Alice C ; Renaux, Alexandre ; Saidi, Rabie ; Gough, Julian ; Freitas, Alex A ; Antczak, Magdalena ; Fabris, Fabio ; Wass, Mark N ; Hou, Jie ; Wang, Zheng ; Romero, Alfonso E ; Paccanaro, Alberto ; Yang, Haixuan ; Goldberg, Tatyana ; Zhao, Chenguang ; Holm, Liisa ; Tseng, Wei-Cheng ; Linial, Michal ; Rose, Peter W ; Dessimoz, Christophe ; Dzeroski, Saso ; Sillitoe, Ian ; Das, Sayoni ; Wan, Cen ; Fa, Rui ; Notaro, Marco ; Grossi, Giuliano ; Valentini, Giorgio ; Mesiti, Marco ; Ritchie, David W ; Aridhi, Sabeur ; Bonneau, Richard ; Gligorijević, Vladimir ; Fang, Hai ; Toppo, Stefano ; Falda, Marco ; Berselli, Michele ; Mao, Qizhong ; Black, Gage S ; Suh, Erica ; Dayton, Jonathan B ; Larsen, Dallas J ; Omdahl, Ashton R ; McGuffin, Liam J ; Brackenridge, Danielle A ; Babbitt, Patricia C ; Yunes, Jeffrey M ; Fontana, Paolo ; Zhang, Feng ; Zhu, Shanfeng ; Dai, Suyang ; Yao, Shuwei ; Cao, Renzhi ; Amezola, Miguel ; Johnson, Devon ; Liu, Yi-Wei ; Frank, Yotam ; Hoehndorf, Robert ; Kulmanov, Maxat ; Björne, Jari ; Tolvanen, Martti E E ; Salakoski, Tapio ; Altenhoff, Adrian ; Ben-Hur, Asa ; Rost, Burkhard ; Orengo, Christine A ; Bosco, Giovanni ; Martin, Maria J ; Mooney, Sean D ; Greene, Casey S ; Radivojac, Predrag
Assuntos: Animals ; Artificial Intelligence ; Biofilm ; Biofilms ; Bioinformatics ; Candida albicans - genetics ; Community challenge ; Computer Science ; Critical assessment ; Distributed, Parallel, and Cluster Computing ; Drosophila melanogaster - genetics ; Genome, Bacterial ; Genome, Fungal ; Humans ; Locomotion ; Long-term memory ; Machine Learning ; Memory, Long-Term ; Molecular Sequence Annotation - methods ; Molecular Sequence Annotation - trends ; Protein function prediction ; Pseudomonas aeruginosa - genetics
É parte de: Genome Biology, 2019-11, Vol.20 (1), p.244-244, Article 244
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
PMCID: PMC6864930
Descrição: The Critical Assessment of Functional Annotation (CAFA) is an ongoing, global, community-driven effort to evaluate and improve the computational annotation of protein function. Here, we report on the results of the third CAFA challenge, CAFA3, that featured an expanded analysis over the previous CAFA rounds, both in terms of volume of data analyzed and the types of analysis performed. In a novel and major new development, computational predictions and assessment goals drove some of the experimental assays, resulting in new functional annotations for more than 1000 genes. Specifically, we performed experimental whole-genome mutation screening in Candida albicans and Pseudomonas aureginosa genomes, which provided us with genome-wide experimental data for genes associated with biofilm formation and motility. We further performed targeted assays on selected genes in Drosophila melanogaster, which we suspected of being involved in long-term memory. We conclude that while predictions of the molecular function and biological process annotations have slightly improved over time, those of the cellular component have not. Term-centric prediction of experimental annotations remains equally challenging; although the performance of the top methods is significantly better than the expectations set by baseline methods in C. albicans and D. melanogaster, it leaves considerable room and need for improvement. Finally, we report that the CAFA community now involves a broad range of participants with expertise in bioinformatics, biological experimentation, biocuration, and bio-ontologies, working together to improve functional annotation, computational function prediction, and our ability to manage big data in the era of large experimental screens.
Editor: England: BioMed Central
Idioma: Inglês

Links

Voltar para lista de resultados

Anterior Resultado 4 Avançar Ir para próxima página

Realização: Logos de Redes Sociais:

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens

England: BioMed Central

Buscando em bases de dados remotas. Favor aguardar.