Publisher: BioMed Central

Journal description

BMC Genomics publishes original research articles in all aspects of gene mapping, sequencing and analysis, functional genomics, and proteomics.

Current impact factor: 3.99

Impact Factor Rankings

2015 Impact Factor Available summer 2016
2014 Impact Factor 3.986
2013 Impact Factor 4.041
2012 Impact Factor 4.397
2011 Impact Factor 4.073
2010 Impact Factor 4.206
2009 Impact Factor 3.759
2008 Impact Factor 3.926
2007 Impact Factor 4.18
2006 Impact Factor 4.029
2005 Impact Factor 4.092
2004 Impact Factor 3.25

Impact factor over time

Impact factor

Additional details

5-year impact 4.36
Cited half-life 4.30
Immediacy index 0.51
Eigenfactor 0.09
Article influence 1.35
Website BMC Genomics website
Other titles BMC genomics, Genomics
ISSN 1471-2164
OCLC 45259143
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

BioMed Central

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
    • Author can archive a post-print version
  • Conditions
    • Publisher's version/PDF may be used
    • Eligible UK authors may deposit in OpenDepot
    • Creative Commons Attribution License
    • Copy of License must accompany any deposit.
    • All titles are open access journals
    • 'BioMed Central' is an imprint of 'Springer Verlag (Germany)'
  • Classification
    ‚Äč green

Publications in this journal

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Transcriptomics analyses of bacteria (and other organisms) provide global as well as detailed information on gene expression levels and, consequently, on other processes in the cell. RNA sequencing (RNA-seq) has over the past few years become the most accurate method for global transcriptome measurements and for the identification of novel RNAs. This development has been accompanied by advances in the bioinformatics methods, tools and software packages that deal with the analysis of the large data sets resulting from RNA-seq efforts. Based on years of experience in analyzing transcriptome data, we developed a user-friendly webserver that performs the statistical analysis on the gene expression values generated by RNA-seq. It also provides the user with a whole range of data plots. We benchmarked our RNA-seq pipeline, T-REx, using a case study of CodY mutants of Bacillus subtilis and show that it could easily and automatically reproduce the statistical analysis of the cognate publication. Furthermore, by mining the correlation matrices, k-means clusters and heatmaps generated by T-REx we observed interesting gene-behavior and identified sub-groups in the CodY regulon. T-REx is a parameter-free statistical analysis pipeline for RNA-seq gene expression data that is dedicated for use by biologists and bioinformaticians alike. The tables and figures produced by T-REx are in most cases sufficient to accurately mine the statistical results. In addition to the stand-alone version, we offer a user-friendly webserver that only needs basic input ( ).
    BMC Genomics 12/2015; 16(1):663. DOI:10.1186/s12864-015-1834-4
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Rice yield and quality are adversely affected by high temperatures, especially at night; high nighttime temperatures are more harmful to grain weight than high daytime temperatures. Unfortunately, global temperatures are consistently increasing at an alarming rate and the minimum nighttime temperature has increased three times as much as the corresponding maximum daytime temperature over the past few decades. We analyzed the transcriptome profiles for rice grain from heat-tolerant and -sensitive lines in response to high night temperatures at the early milky stage using the Illumina Sequencing method. The analysis results for the sequencing data indicated that 35 transcripts showed different expressions between heat-tolerant and -sensitive rice, and RT-qPCR analyses confirmed the expression patterns of selected transcripts. Functional analysis of the differentially expressed transcripts indicated that 21 genes have functional annotation and their functions are mainly involved in oxidation-reduction (6 genes), metabolic (7 genes), transport (4 genes), transcript regulation (2 genes), defense response (1 gene) and photosynthetic (1 gene) processes. Based on the functional annotation of the differentially expressed genes, the possible process that regulates these differentially expressed transcripts in rice grain responding to high night temperature stress at the early milky stage was further analyzed. This analysis indicated that high night temperature stress disrupts electron transport in the mitochondria, which leads to changes in the concentration of hydrogen ions in the mitochondrial and cellular matrix and influences the activity of enzymes involved in TCA and its secondary metabolism in plant cells. Using Illumina sequencing technology, the differences between the transcriptomes of heat-tolerant and -sensitive rice lines in response to high night temperature stress at the early milky stage was described here for the first time. The candidate transcripts may provide genetic resources that may be useful in the improvement of heat-tolerant characters of rice. The model proposed here is based on differences in expression and transcription between two rice lines. In addition, the model may support future studies on the molecular mechanisms underlying plant responses to high night temperatures.
    BMC Genomics 12/2015; 16(1). DOI:10.1186/s12864-015-1222-0