About BioData Mining

What is BioData Mining?

BioData Mining, is an open access, peer reviewed, online journal encompassing research on all aspects of data mining applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, transcriptomic, genomic, proteomic, and metabolomic data.

Topical areas include, but are not limited to:

• Development, evaluation, and application of novel data mining and machine learning algorithms.
• Adaptation, evaluation, and application of traditional data mining and machine learning algorithms.
• Open-source software for the application of data mining and machine learning algorithms.
• Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies.
• Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.

Content overview

BioData Mining considers the following types of article:

• Research: reports of data from original research.
• Reviews: comprehensive, authoritative, descriptions of any subject within the scope of the journal. These articles are usually written by opinion leaders that have been invited by the Editorial Board.
• Methodology articles: present a new experimental method, test or procedure. The method described may either be completely new, or may offer a better version of an existing method. The article must describe a demonstrable advance on what is currently available. The method needs to have been well tested and ideally, but not necessarily, used in a way that proves its value.
• Short reports: brief reports of data from original research.
• Software articles: describe the source code for software applications, tools or algorithm implementations. Typically, an archive of the source code of the current version of the software should be included with the submitted manuscript as a supplementary file.

Peer review policies

Appropriate manuscripts submitted to BioData Mining will be peer reviewed by either two or three reviewers. Peer review for the journal is open, meaning reviewers' names are included on the peer review reports, and reports are made publicly available. Reviewers will be recognized experts in the field, and may be members of the Editorial Board or external peer reviewers. The Editors-in-Chief are responsible for the final decision on acceptance or rejection of a manuscript.

Edited by Jesus Aguilar-Ruiz PhD and Jason H Moore PhD, BioData Mining is supported by an international Editorial Board.

Publishing in BioData Mining

All articles will be listed in PubMed immediately upon acceptance (after peer review), and will be covered by PubMed Central.

Articles in BioData Mining should be cited in the same way as articles in a traditional journal. However, because articles in this journal are not printed, they do not have page numbers. Instead, they have a unique article number.

The following citation:

BioData Mining 2004, 2:1

refers to article 1 from volume 2 of the journal.

As an online journal, BioData Mining does not have issue numbers. Each volume corresponds to a calendar year.

To keep up to date with the latest articles from BioData Mining, why not register to receive alerts? Registration also enables you to customise your subject areas of interest, store your searches, and submit your manuscripts.

Submission of manuscripts

Manuscripts should be submitted electronically to BioData Mining using the online submission system. Full details of how to submit a manuscript are given in the instructions for authors.

General journal policies

BioData Mining is published by BioMed Central, an independent publisher committed to ensuring peer-reviewed biomedical research is Open Access. That means it is freely and universally accessible online, it is archived in at least one internationally recognised free access repository, and its authors retain copyright, allowing anyone to reproduce or disseminate articles, according to the BioMed Central copyright and licence agreement. BioData Mining however, has taken this further by making all its content Open Access.

BioData Mining's articles are archived in PubMed Central, the US National Library of Medicine's full-text repository of life science literature, and also in repositories at the University of Potsdam in Germany, at INIST in France and in e-Depot, the National Library of the Netherlands' digital archive of all electronic publications. The journal is also participating in the British Library's e-journals pilot project, and plans to deposit copies of all articles with the British Library.

BioMed Central is working closely with the Thomson Reuters (ISI) to ensure that citation analysis of articles published in BioData Mining will be available.

BioData Mining is able to deliver summaries of frequently updated content via Really Simple Syndication (RSS) feeds. For more information about RSS feeds see our publisher's website.

For further information about general policies please see the instructions for authors.