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Journal Photo for NAR Genomics and Bioinformatics
Peer reviewed only Open Access

NAR Genomics and Bioinformatics (NAR GB)

Publisher : Oxford University Press
Biology Genomics Hi-C
e-ISSN 2631-9268
Issue Frequency Monthly
Impact Factor 4.0
Est. Year 2019
Mobile 441865556767
Country United Kingdom
Language English
APC YES
Impact Factor Assignee Google Scholar
Email cedric.notredame@crg.eu

Journal Descriptions

NAR Genomics and Bioinformatics is an interdisciplinary journal focused on genomics and bioinformatics large-scale data analysis. It aims at providing the community with high quality results, analysis and methods in all aspects of genomics and bioinformatics. Reproducibility is a strong focus of the journal, and all entries will have to comply with strict guidelines ensuring the perfect reproducibility of both experimental and bioinformatics analysis. Standard papers are expected to be compliant with NAR main guidelines and entries must fulfill the condition of scientific quality, novelty, timeliness, usefulness and usability, as established through an extensive peer-reviewing process. In the case of bioinformatics methods and analysis, usability implies a suitable implementation of the FAIR principle that requires data and software to be Findable, Accessible, Interoperable and Re-usable. NAR Genomics and Bioinformatics has a strict open-source policy and will only consider for publication contributions whose novel bioinformatics components are open source.

NAR Genomics and Bioinformatics (NAR GB) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Biology, Genomics, Hi-C, Metabolomics, Structural Biology, Omics Analysis, Functional genomics, Single Cell Analysis, Gene Regulation, Sequence Analysis, Human Health, Plant Biology, Microbiology, Statistical Learning, Mathematics , Online , Monthly Journal

  • UGC Approved, ISSN Approved: P-ISSN E-ISSN: 2631-9268, Established: 2019, Impact Factor: 4.0
  • Does Not Provide Crossref DOI
  • Indexed in: Scopus, WoS, DOAJ, PubMed

  • Not indexed in UGC CARE

Indexing

Publications of NAR GB

Pietro Liò December, 2024
The identification of cell types in single-cell RNA sequencing (scRNA-seq) data is a critical task in understanding complex biological systems. Traditional supervised machine learning method...