3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      PASS2 version 6: a database of structure-based sequence alignments of protein domain superfamilies in accordance with SCOPe

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          The number of protein structures is increasing due to the individual initiatives and rapid development of structure determination techniques. Structure-based sequence alignments of distantly related proteins enable the investigation of structural, evolutionary and functional relationships between proteins and their domains leading to their common evolutionary origin. Protein Alignments organized as Structural Superfamilies (PASS2) is a database that provides such alignments of members of protein domain superfamilies of known structure and with less than 40% sequence identity. PASS2 has been continuously updated in accordance to Structural Classification of Proteins (SCOP), and now Structural Classification of Proteins - extended (SCOPe). The current update directly corresponds to SCOPe 2.06, dealing with 2006 domain superfamilies of known structure and about 14 000 domains. Alignments have been augmented by features such as hidden Markov models, highly conserved residues, structural motifs and gene ontology terms, which are available for download. In this update, we introduce the concepts of ‘extreme structural outliers’ and ‘split superfamilies’ as well.

          Related collections

          Most cited references23

          • Record: found
          • Abstract: found
          • Article: not found

          Profile hidden Markov models.

          S. Eddy (1998)
          The recent literature on profile hidden Markov model (profile HMM) methods and software is reviewed. Profile HMMs turn a multiple sequence alignment into a position-specific scoring system suitable for searching databases for remotely homologous sequences. Profile HMM analyses complement standard pairwise comparison methods for large-scale sequence analysis. Several software implementations and two large libraries of profile HMMs of common protein domains are available. HMM methods performed comparably to threading methods in the CASP2 structure prediction exercise.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Gene Ontology Annotations and Resources

            The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new ‘phylogenetic annotation’ process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Neutrophil-activating peptide-1/interleukin 8, a novel cytokine that activates neutrophils.

                Bookmark

                Author and article information

                Journal
                Database (Oxford)
                Database (Oxford)
                databa
                Database: The Journal of Biological Databases and Curation
                Oxford University Press
                1758-0463
                2019
                01 March 2019
                01 March 2019
                : 2019
                : baz028
                Affiliations
                [1]National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road, Bangalore, Karnataka, India
                Author notes
                Corresponding author: Tel: (+91) 80 2366 6250; Fax: (+91) 80 2363 6462; Email: mini@ 123456ncbs.res.in

                Present address: International Institute of Molecular and Cell Biology, Księcia Trojdena 4, 02-109 Warsaw, Poland

                Joint first authors

                Author information
                http://orcid.org/0000-0003-3641-6393
                http://orcid.org/0000-0001-9336-2796
                http://orcid.org/0000-0002-6312-3118
                http://orcid.org/0000-0002-6642-2367
                Article
                baz028
                10.1093/database/baz028
                6395796
                30820573
                0b6d375f-58eb-42e0-8f8c-c96d1a04ed1b
                © The Author(s) 2019. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 August 2018
                : 3 February 2019
                : 6 February 2019
                Page count
                Pages: 08
                Funding
                Funded by: Department of Biotechnology, Ministry of Science and Technology 10.13039/501100001407
                Award ID: BT/01/COE/09/01
                Funded by: Science and Engineering Research Board 10.13039/501100001843
                Award ID: SB/S2/JCB-071/2015
                Categories
                Database Update

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

                Comments

                Comment on this article