As a result of the significant disruption that is being caused by the COVID-19 pandemic we are very aware that many researchers will have difficulty in meeting the timelines associated with our peer review process during normal times. Please do let us know if you need additional time. Our systems will continue to remind you of the original timelines but we intend to be highly flexible at this time.
COVID-19 and impact on peer review
Articles
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Elucidating the role of the gastrointestinal microbiota in racial and ethnic health disparities
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Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data
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Knowledge-primed neural networks enable biologically interpretable deep learning on single-cell sequencing data
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Long-read-based human genomic structural variation detection with cuteSV
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The Kardashian index: a measure of discrepant social media profile for scientists
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A survey of best practices for RNA-seq data analysis
The Erratum to this article has been published in Genome Biology 2016 17:181
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
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Differential expression analysis for sequence count data
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DNA methylation age of human tissues and cell types
The Erratum to this article has been published in Genome Biology 2015 16:96
Latest articles from Genome Medicine
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Illuminating the human virome in health and disease
30 July 2020
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Focus: Approaches to Data Analysis
Read the latest papers on the approaches to data analysis across BMC flagship journals.
The challenges of colposcopy for cervical cancer screening in LMICs and solutions by artificial intelligence
Peng Xue et al.
Published in BMC Medicine 03 June 2020
ImageJ SurfCut: a user-friendly pipeline for high-throughput extraction of cell contours from 3D image stacks
Özer Erguvan et al.
Published in BMC Biology 09 May 2019
An unsupervised learning approach to identify novel signatures of health and disease from multimodal data
Ilan Shomorony et al.
Published in Genome Medicine 10 January 2020
DISC: a highly scalable and accurate inference of gene expression and structure for single-cell transcriptomes using semi-supervised deep learning
Yao He et al.
Published in Genome Biology 10 July 2020
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From the blog
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Transposon Day Quiz 2020
16 June 2020
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DNA Day quiz 2020
24 April 2020
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The fascination of plant genomes
20 May 2019
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2018 Journal Metrics
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Citation Impact
10.806 - 2-year Impact Factor
19.041 - 5-year Impact Factor
2.794 - Source Normalized Impact per Paper (SNIP)
9.479 - SCImago Journal Rank (SJR)
