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Bioinformatics Advances is a peer-reviewed journal published by Oxford University Press, covering Bioinformatics and Genomic Networks, Genomics and Phylogenetic Studies, Single-cell and spatial transcriptomics. Over its lifetime it has published 1,081 papers, which have received 7,009 citations.
| Publisher | Oxford University Press |
|---|---|
| Reference style | Author–year (OUP) Author–year — (Smith, 2023) in the text Smith, A., Jones, B. and Lee, C. (2023) 'A representative article title', Bioinformatics Advances, 12(3), pp. 45–58.
Formats any DOI in the closest standard style — Bioinformatics Advances has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Bioinformatics and Genomic Networks Genomics and Phylogenetic Studies Single-cell and spatial transcriptomics Machine Learning in Bioinformatics Cell Image Analysis Techniques |
| ISSN | 2635-0041 |
| Citation impact (2-yr) | 2.28 |
| h-index | 30 |
| i10-index | 147 |
| Article processing charge | $2,164 |
| Open access | Yes — indexed in DOAJ |
| Top institutions publishing here | Centre National de la Recherche Scientifique |
| Journal website | academic.oup.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.
Summary: Many methods allow us to extract biological activities from omics data using information from prior knowledge resources, reducing the dimensionality for increased statistical power and better interpretability. Here, we present decoupleR, a Bioconductor and Python package containing computational methods to extract these activities within a unified framework. decoupleR allows us to flexibly run any…
Motivation: Genes involved in coordinated biological pathways, including metabolism, drug resistance and virulence, are often collocalized as gene clusters. Identifying homologous gene clusters aids in the study of their function and evolution, however, existing tools are limited to searching local sequence databases. Tools for remotely searching public databases are necessary to keep pace with the…
Motivation: General protein language models have been shown to summarize the semantics of protein sequences into representations that are useful for state-of-the-art predictive methods. However, for antibody specific problems, such as restoring residues lost due to sequencing errors, a model trained solely on antibodies may be more powerful. Antibodies are one of the few protein…
Summary: The transformer-based language models, including vanilla transformer, BERT and GPT-3, have achieved revolutionary breakthroughs in the field of natural language processing (NLP). Since there are inherent similarities between various biological sequences and natural languages, the remarkable interpretability and adaptability of these models have prompted a new wave of their application in bioinformatics research. To…
Abstract Motivation Oxford Nanopore Technologies (ONT) sequencing has become very popular over the past few years and offers a cost-effective solution for many genomic and transcriptomic projects. One distinctive feature of the technology is that the protocol includes the ligation of adapters to both ends of each fragment. Those adapters should then be removed before…
