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NAR Genomics and Bioinformatics is a peer-reviewed journal published by Oxford University Press, covering Genomics and Phylogenetic Studies, RNA and protein synthesis mechanisms, Single-cell and spatial transcriptomics. Over its lifetime it has published 964 papers, which have received 16,589 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, NAR Genomics and Bioinformatics 12 (2023) 45–58.
Formats any DOI in the closest standard style — NAR Genomics and Bioinformatics has no published style definition, so this is an approximation. No sign-up. |
| Publishes research in | Genomics and Phylogenetic Studies RNA and protein synthesis mechanisms Single-cell and spatial transcriptomics RNA modifications and cancer Bioinformatics and Genomic Networks |
| ISSN | 2631-9268 |
| Citation impact (2-yr) | 3.74 |
| h-index | 50 |
| i10-index | 312 |
| Article processing charge | $2,473 |
| 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.
The task of eukaryotic genome annotation remains challenging. Only a few genomes could serve as standards of annotation achieved through a tremendous investment of human curation efforts. Still, the correctness of all alternative isoforms, even in the best-annotated genomes, could be a good subject for further investigation. The new BRAKER2 pipeline generates and integrates external…
The benefit of integrating batches of genomic data to increase statistical power is often hindered by batch effects, or unwanted variation in data caused by differences in technical factors across batches. It is therefore critical to effectively address batch effects in genomic data to overcome these challenges. Many existing methods for batch effects adjustment assume…
Abstract We have made several steps toward creating a fast and accurate algorithm for gene prediction in eukaryotic genomes. First, we introduced an automated method for efficient ab initio gene finding, GeneMark-ES, with parameters trained in iterative unsupervised mode. Next, in GeneMark-ET we proposed a method of integration of unsupervised training with information on intron…
Sequencing technology has achieved great advances in the past decade. Studies have previously shown the quality of specific instruments in controlled conditions. Here, we developed a method able to retroactively determine the error rate of most public sequencing datasets. To do this, we utilized the overlaps between reads that are a feature of many sequencing…
Viruses are abundant, diverse and ancestral biological entities. Their diversity is high, both in terms of the number of different protein families encountered and in the sequence heterogeneity of each protein family. The recent increase in sequenced viral genomes constitutes a great opportunity to gain new insights into this diversity and consequently urges the development…
