Database The Journal of Biological Databases and Curation

Publisher: Oxford Journals (Firm), Oxford University Press (OUP)

Journal description

Current impact factor: 4.46

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 4.457
2012 Impact Factor 4.2
2011 Impact Factor 2.071

Impact factor over time

Impact factor
Year

Additional details

5-year impact 4.19
Cited half-life 2.20
Immediacy index 0.73
Eigenfactor 0.00
Article influence 1.80
Other titles Journal of biological databases and curation
ISSN 1758-0463
OCLC 319891682
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Oxford University Press (OUP)

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author cannot archive a post-print version
  • Conditions
    • Creative Commons Attribution License
    • Pre-print on author's personal website, employers website or subject repository
    • Pre-print can only be posted prior to acceptance
    • Pre-print must be accompanied by set statement (see link)
    • Pre-print must not be replaced with post-print, instead a link to published version with amended set statement should be made
    • Post-print in Institutional repositories or Central repositories
    • Publisher's version/PDF must be used
    • Publisher's version/PDF on institutional repository or centrally organised repositories
    • Published source must be acknowledged
    • Must link to publisher version
    • Set phrase to accompany archived copy (see policy)
    • Eligible authors may deposit in OpenDepot
    • Publisher will deposit on behalf of NIH, HHMI, UK MRC, Telethon and Wellcome Trust funded authors to PubMed Central and Europe PMC
    • All titles are open access journals
    • Progress of Theoretical and Experimental Physics is a participant in SCOAP3
    • This policy is an exception to the default policies of 'Oxford University Press (OUP)'
  • Classification
    ​ green

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Gram-negative pathogenic bacteria inject type III secreted effectors (T3SEs) into host cells to sabotage their immune signaling networks. Because T3SEs constitute a meeting-point of pathogen virulence and host defense, they are of keen interest to host-pathogen interaction research community. To accelerate the identification and functional understanding of T3SEs, we present BEAN 2.0 as an integrated web resource to predict, analyse and store T3SEs. BEAN 2.0 includes three major components. First, it provides an accurate T3SE predictor based on a hybrid approach. Using independent testing data, we show that BEAN 2.0 achieves a sensitivity of 86.05% and a specificity of 100%. Second, it integrates a set of online sequence analysis tools. Users can further perform functional analysis of putative T3SEs in a seamless way, such as subcellular location prediction, functional domain scan and disorder region annotation. Third, it compiles a database covering 1215 experimentally verified T3SEs and constructs two T3SE-related networks that can be used to explore the relationships among T3SEs. Taken together, by presenting a one-stop T3SE bioinformatics resource, we hope BEAN 2.0 can promote comprehensive understanding of the function and evolution of T3SEs.Database URL: http://systbio.cau.edu.cn/bean/. © The Author(s) 2015. Published by Oxford University Press.
    Database The Journal of Biological Databases and Curation 01/2015; 2015. DOI:10.1093/database/bav064
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Based on recent results, the determination of the easily accessible red blood cell (RBC) membrane proteins may provide new diagnostic possibilities for assessing mutations, polymorphisms or regulatory alterations in diseases. However, the analysis of the current mass spectrometry-based proteomics datasets and other major databases indicates inconsistencies-the results show large scattering and only a limited overlap for the identified RBC membrane proteins. Here, we applied membrane-specific proteomics studies in human RBC, compared these results with the data in the literature, and generated a comprehensive and expandable database using all available data sources. The integrated web database now refers to proteomic, genetic and medical databases as well, and contains an unexpected large number of validated membrane proteins previously thought to be specific for other tissues and/or related to major human diseases. Since the determination of protein expression in RBC provides a method to indicate pathological alterations, our database should facilitate the development of RBC membrane biomarker platforms and provide a unique resource to aid related further research and diagnostics.Database URL: http://rbcc.hegelab.org. © The Author(s) 2015. Published by Oxford University Press.
    Database The Journal of Biological Databases and Curation 01/2015; 2015. DOI:10.1093/database/bav056