Write in a clean editor, then format for BMC Bioinformatics in one click — DocuGuru applies the official BMC (BioMed Central) template with numbered references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
BMC Bioinformatics is a peer-reviewed journal published by BMC (BioMed Central), covering Bioinformatics and Genomic Networks, Gene expression and cancer classification, Genomics and Phylogenetic Studies. Over its lifetime it has published 13,236 papers, which have received 863,675 citations.
| Publisher | BMC (BioMed Central) |
|---|---|
| Reference style | Numbered (Vancouver) Numbered — [1], [2] in the text 1. Smith A, Jones B, Lee C. A representative article title. BMC Bioinformatics. 2023;12(3):45–58.
Formats any DOI in BMC Bioinformatics style. No sign-up. |
| Publishes research in | Bioinformatics and Genomic Networks Gene expression and cancer classification Genomics and Phylogenetic Studies Machine Learning in Bioinformatics Biomedical Text Mining and Ontologies |
| ISSN | 1471-2105 |
| Citation impact (2-yr) | 4.57 |
| h-index | 314 |
| i10-index | 9,026 |
| Article processing charge | $2,072 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | www.biomedcentral.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
BACKGROUND: Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module…
BACKGROUND: RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine…
BACKGROUND: Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. RESULTS:…
BACKGROUND: Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible…
BACKGROUND: Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing…
