UniProt: a hub for protein information
By The Uniprot Consortium. 2014
4,537 citations recorded by the source corpus.
UniProt is an important collection of protein sequences and their annotations, which has doubled in size to 80 million sequences during the past year. This growth in sequences has prompted an extension of UniProt accession number space from 6 to 10 characters. An increasing fraction of new sequences are identical to a sequence that already exists in the database with the majority of sequences coming from genome sequencing projects. We have created a new proteome identifier that uniquely identifies a particular assembly of a species and strain or subspecies to help users track the provenance of sequences. We present a new website that has been designed using a user-experience design process. We have introduced an annotation score for all entries in UniProt to represent the relative amount of knowledge known about each protein. These scores will be helpful in identifying which proteins are the best characterized and most informative for comparative analysis. All UniProt data is provided freely and is available on the web at http://www.uniprot.org/.
Subfields: Molecular Biology, Computational Biology & Bioinformatics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Molecular Biology
- Peer Bork
- Paul D. Thomas
- Huaiyu Mi
- Anushya Muruganujan
- Lars Juhl Jensen
- C. von Mering
- Minoru Kanehisa
- Damian Szklarczyk
In Computational Biology & Bioinformatics
- Debora Marks
- Christopher Sander
- Bonnie Berger
- Chengxin Zhang
- Yang Zhang
- Thomas A. Hopf
- Burkhard Rost
- Adam J. Riesselman
Citations in the corpus
- AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery (2015, background): “Following Mysinger et al. [20], we first grouped target affinities by their UniProt gene name pre-fix [26] and removed targets for which there were less than 10 active ligands.”
- UniProt Tools (2016, methodology): “The UniProt Web site provides a Basic Local Alignment Search Tool (BLAST; UniProt Consortium, 2015) which finds regions of local similarity between sequences.”
- KinMap: a web-based tool for interactive navigation through human kinome data (2017, methodology): “The current parsing function recognizes names used by Manning [3], recommended by the UniProt Consortium [16], approved by the HUGO Gene Nomenclature Committee [17], as well as any of the alternative names listed in these resources.”