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Bioinformatics is a peer-reviewed journal published by Oxford University Press, covering Bioinformatics and Genomic Networks, Genomics and Phylogenetic Studies, Gene expression and cancer classification. Over its lifetime it has published 19,586 papers, which have received 2,823,015 citations.
| Publisher | Oxford University Press |
|---|---|
| Reference style | Numbered (OUP) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, A representative article title, Bioinformatics 12 (2023) 45–58.
Formats any DOI in the closest standard style — Bioinformatics has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Bioinformatics and Genomic Networks Genomics and Phylogenetic Studies Gene expression and cancer classification Machine Learning in Bioinformatics Protein Structure and Dynamics |
| ISSN | 1367-4803 |
| Citation impact (2-yr) | 5.89 |
| h-index | 572 |
| i10-index | 13,926 |
| Article processing charge | $3,618 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | bioinformatics.oxfordjournals.org |
| 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.
MOTIVATION: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data.…
SUMMARY: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes…
MOTIVATION: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ…
MOTIVATION: Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases. RESULTS: To align our…
SUMMARY: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions.…
