UniProt: a hub for protein information. 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/.

References in zbMATH (referenced in 136 articles , 1 standard article )

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  1. Dhole, Kaustubh; Singh, Gurdeep; Pai, Priyadarshini P.; Mondal, Sukanta: Sequence-based prediction of protein-protein interaction sites with L1-logreg classifier (2014)
  2. Kasabov, Nikola (ed.): Springer handbook of bio-/neuro-informatics (2014)
  3. Malaguti, Giulia; Singh, Param Priya; Isambert, Hervé: On the retention of gene duplicates prone to dominant deleterious mutations (2014)
  4. Wu, Zheyang; Sun, Yiming; He, Shiquan; Cho, Judy; Zhao, Hongyu; Jin, Jiashun: Detection boundary and higher criticism approach for rare and weak genetic effects (2014)
  5. Feng, Peng-Mian; Ding, Hui; Chen, Wei; Lin, Hao: Naïve Bayes classifier with feature selection to identify phage virion proteins (2013)
  6. Eusse, Juan Fernando; Moreano, Nahri; De Melo, Alba Cristina Magalhaes Alves; Jacobi, Ricardo Pezzuol: A protein sequence analysis hardware accelerator based on divergences (2012) ioport
  7. Fan, Guo-Liang; Li, Qian-Zhong: Predicting mycobacterial proteins subcellular locations by incorporating pseudo-average chemical shift into the general form of Chou’s pseudo amino acid composition (2012)
  8. Qin, Wenli; Li, Yizhou; Li, Juan; Yu, Lezheng; Wu, Di; Jing, Runyu; Pu, Xuemei; Guo, Yanzhi; Li, Menglong: Predicting deleterious non-synonymous single nucleotide polymorphisms in signal peptides based on hybrid sequence attributes (2012)
  9. Zamora-Chimal, Criseida; Santillán, Moisés; Rodríguez-González, Jesús: Influence of the feedback loops in the \textittrpoperon of \textitB. subtilis on the system dynamic response and noise amplitude (2012)
  10. Consortium, The Uniprot: Ongoing and future developments at the universal protein resource (2011) ioport
  11. Desai, Dhwani K.; Nandi, Soumyadeep; Srivastava, Prashant K.; Lynn, Andrew M.: ModEnzA: accurate identification of metabolic enzymes using function specific profile HMMs with optimised discrimination threshold and modified emission probabilities (2011)
  12. Faure, Andre J.; Seoighe, Cathal; Mulder, Nicola J.: Investigating the effect of paralogs on microarray gene-set analysis (2011) ioport
  13. Groppe, Sven: Data Management and query processing in semantic web databases. (2011)
  14. Lin, Hao; Ding, Hui: Predicting ion channels and their types by the dipeptide mode of pseudo amino acid composition (2011)
  15. Mazandu, Gaston K.; Mulder, Nicola J.: Generation and analysis of large-scale data-driven mycobacterium tuberculosis functional networks for drug target identification (2011) ioport
  16. Roterman, I.; Konieczny, L.; Jurkowski, W.; Prymula, K.; Banach, M.: Two-intermediate model to characterize the structure of fast-folding proteins (2011)
  17. Winkler, Jonas; Armano, Giuliano; Dybowski, J. Nikolaj; Kuhn, Oliver; Ledda, Filippo; Heider, Dominik: Computational design of a DNA- and Fc-binding fusion protein (2011) ioport
  18. Wolfsheimer, Stefan; Herms, Inke; Rahmann, Sven; Hartmann, Alexander K.: Accurate statistics for local sequence alignment with position-dependent scoring by rare-event sampling (2011) ioport
  19. -: The universal protein resource (UniProt) in 2010 (2010) ioport
  20. Brown, Daniel G.; Golod, Daniil: Decoding hmms using the (k)best paths: algorithms and applications (2010) ioport