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Title: SIFTER search: a web server for accurate phylogeny-based protein function prediction

Journal Article · · Nucleic Acids Research
DOI:https://doi.org/10.1093/nar/gkv461· OSTI ID:1257375

We are awash in proteins discovered through high-throughput sequencing projects. As only a minuscule fraction of these have been experimentally characterized, computational methods are widely used for automated annotation. Here, we introduce a user-friendly web interface for accurate protein function prediction using the SIFTER algorithm. SIFTER is a state-of-the-art sequence-based gene molecular function prediction algorithm that uses a statistical model of function evolution to incorporate annotations throughout the phylogenetic tree. Due to the resources needed by the SIFTER algorithm, running SIFTER locally is not trivial for most users, especially for large-scale problems. The SIFTER web server thus provides access to precomputed predictions on 16 863 537 proteins from 232 403 species. Users can explore SIFTER predictions with queries for proteins, species, functions, and homologs of sequences not in the precomputed prediction set. Lastly, the SIFTER web server is accessible at http://sifter.berkeley.edu/ and the source code can be downloaded.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
Grant/Contract Number:
AC02-05CH11231; NIH R01 GM071749
OSTI ID:
1257375
Journal Information:
Nucleic Acids Research, Vol. 43, Issue W1; ISSN 0305-1048
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 31 works
Citation information provided by
Web of Science

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Cited By (15)

Protein Function Prediction book January 2017
A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks
  • Ba, Cheick Tidiane; Casiraghi, Elena; Frasca, Marco
  • Computational Intelligence Methods for Bioinformatics and Biostatistics: 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6–8, 2018, Revised Selected Papers, p. 88-98 https://doi.org/10.1007/978-3-030-34585-3_8
book January 2020
Protein functional annotation of simultaneously improved stability, accuracy and false discovery rate achieved by a sequence-based deep learning journal August 2019
Effusion: prediction of protein function from sequence similarity networks journal August 2018
Phylo-PFP: improved automated protein function prediction using phylogenetic distance of distantly related sequences journal August 2018
INGA 2.0: improving protein function prediction for the dark proteome journal May 2019
NetGO: improving large-scale protein function prediction with massive network information journal May 2019
UNIPred-Web: a web tool for the integration and visualization of biomolecular networks for protein function prediction journal August 2019
SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity journal August 2016
Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate journal January 2018
Functional Annotations of Paralogs: A Blessing and a Curse journal September 2016
A survey of human histone H1 subtypes interaction networks: Implications for histones H1 functioning journal February 2021
Computational and Experimental Studies of ADP-Ribosylation book January 2017
PvaxDB: a comprehensive structural repository ofPlasmodium vivaxproteome journal January 2018
Investigation of Antidepressant Properties of Yohimbine by Employing Structure-Based Computational Assessments journal October 2021

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