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期刊名称：BIODATA MINING ISSN： 1756-0381 出版频率： Continuous publication 出版社： BMC, CAMPUS, 4 CRINAN ST, LONDON, ENGLAND, N1 9XW   出版社网址： http://www.biomedcentral.com/ 期刊网址： http://www.biodatamining.org/ 影响因子： 2.522 主题范畴： Mathematical & Computational Biology 变更情况： Newly Added by 2013 期刊简介(About the journal)    投稿须知(Instructions to Authors)    编辑部信息(Editorial Board)    About the journal 1.76 Editors-in-Chief Jesus Aguilar-Ruiz, Pablo de Olavide University Jason Moore, Dartmouth College About BioData Mining Aims and scope | Open access | Article-processing charges | Indexing services | Publication and peer review process | Editorial policies | Citing articles in BioData Mining | Why publish your article in BioData Mining? This page includes information about the aims and scope of BioData Mining, editorial policies, open access and article-processing charges, the peer review process and other information. For details of how to prepare and submit a manuscript through the online submission system, please see the instructions for authors. Aims & scope 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. Open access All articles published by BioData Mining are made freely and permanently accessible online immediately upon publication, without subscription charges or registration barriers. Further information about open access can be found here. Authors of articles published in BioData Mining are the copyright holders of their articles and have granted to any third party, in advance and in perpetuity, the right to use, reproduce or disseminate the article, according to the BioMed Central copyright and license agreement. For authors who are US government employees or are prevented from being copyright holders for similar reasons, BioMed Central can accommodate non-standard copyright lines. Please contact us if further information is needed. Article-processing charges Open access publishing is not without costs. BioData Mining therefore levies an article-processing charge of £1115/$1825/€1340 for each article accepted for publication. We routinely waive charges for authors from low-income countries. Generally, if the submitting author's institution is a Member the cost of the article-processing charge is covered by the membership, and no further charge is payable. In the case of authors whose institutions are Supporter Members, however, a discounted article-processing charge is payable by the author. For further details, see our article-processing charge page. A limited number of waivers for article-processing charges are also available at the editors' discretion, and authors wishing to apply for these waivers should contact the editors. Indexing services All articles published in BioData Mining are included in: ACM BIOSIS CAS Citebase DOAJ Embase EmBiology Google Scholar Index Copernicus Journal Citation Reports/Science Edition OAIster PubMed PubMed Central Science Citation Index Expanded SCImago Scirus Scopus SOCOLAR Zetoc The full text of all research articles is deposited in digital archives including e-Depot (The Netherlands). ) BioData Mining is tracked by Thomson Reuters (ISI) and has an unofficial Impact Factor of 1.76 Publication and peer review process Content overview BioData Mining considers the following types of article: <ul 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 Manuscripts will be assigned to a Monitoring Editor, who will appoint at least two referees. On receipt of their reports the Monitoring Editor will make a recommendation to accept, to accept with minor revisions, to request major revisions and resubmission, or to reject. No manuscript will be rejected without being assessed by a member of the Editorial Board and one other expert. BioData Mining operates an 'open peer review' policy meaning reviewers are asked to sign their reviews. The pre-publication history including all submitted versions, reviewers' reports and authors' responses will be linked to from the published article. Authors will be able to check the progress of their manuscript through the submission system at any time by logging into My BioData Mining, a personalized section of the site. Reprints High-quality, bound reprints can be purchased for all articles published. Please see our reprints website for further information about ordering reprints. Supplements BioData Mining will consider supplements based on proceedings (full articles or meeting abstracts), reviews or research. All articles submitted for publication in supplements are subject to peer review. Published supplements are fully searchable and freely accessible online and can also be produced in print. For further information, please contact us. Editorial policies All manuscripts submitted to BioData Mining should adhere to BioMed Central's editorial policies. Citing articles in BioData Mining Articles in BioData Mining should be cited in the same way as articles in a traditional journal. Because articles are not printed, they do not have page numbers; instead, they are given a unique article number. Article citations follow this format: Authors: Title. BioData Mining [year], [volume number]:[article number]. e.g. Roberts LD, Hassall DG, Winegar DA, Haselden JN, Nicholls AW, Griffin JL: Increased hepatic oxidative metabolism distinguishes the action of Peroxisome Proliferator-Activated Receptor delta from Peroxisome Proliferator-Activated Receptor gamma in the Ob/Ob mouse. BioData Mining 2009, 1:115. refers to article 115 from Volume 1 of the journal. Why publish your article in BioData Mining? High visibility BioData Mining's open access policy allows maximum visibility of articles published in the journal as they are available to a wide, global audience. Articles that have been especially highly accessed are highlighted with a 'Highly accessed' graphic, which appears on the journal's contents pages and search results. Speed of publication BioData Mining offers a fast publication schedule whilst maintaining rigorous peer review; all articles must be submitted online, and peer review is managed fully electronically (articles are distributed in PDF form, which is automatically generated from the submitted files). Articles are published with their final citation immediately upon acceptance in a provisional PDF form. The article will subsequently be published in both fully browsable web form, and as a formatted PDF; the article will then be available through BioData Mining and BioMed Central. Flexibility Online publication in BioData Mining gives authors the opportunity to publish large datasets, large numbers of color illustrations and moving pictures, to display data in a form that can be read directly by other software packages so as to allow readers to manipulate the data for themselves, and to create all relevant links (for example, to PubMed, to sequence and other databases, and to other articles). Promotion and press coverage Articles published in BioData Mining are included in article alerts and regular email updates. Some may be included in abstract books mailed to academics and are highlighted on BioData Mining's pages and on the BioMed Central homepage. In addition, articles published in BioData Mining may be promoted by press releases to the general or scientific press. These activities increase the exposure and number of accesses for articles published in BioData Mining. A list of articles recently press-released by journals published by BioMed Central is available here. Copyright Authors of articles published in BioData Mining retain the copyright of their articles and are free to reproduce and disseminate their work (for further details, see the BioMed Central copyright and license agreement). For further information about the advantages of publishing in a journal from BioMed Central, please click here.   Instructions to Authors Instructions for authors 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. Each article type published by BioData Mining follows a specific format, as detailed in the corresponding instructions for authors; please choose an article type from the list on the left to view the instructions for authors. The instructions for authors includes information about preparing a manuscript for submission to BioData Mining, criteria for publication and the online submission process. Other relevant information about the journal's policies, the refereeing process and so on can be found in 'About this journal'. BioData Mining publishes the following article types: Research articles Methodologies Reviews Short reports Software articles We use plagiarism detection This journal is a member of, and subscribes to the principles of, the Committee on Publication Ethics (COPE). Authors and referees are asked to declare any competing interests. Copyright rests with the authors. For more information on copyright of articles, see our publisher's copyright and license policy. Editorial Board Editors-in-Chief Prof Jesus Aguilar-Ruiz Pablo de Olavide University, Spain Dr Jason Moore Dartmouth College, USA Managing Editor Dr Marylyn Ritchie Pennsylvania State University, USA Advisory Board Prof Bernat Soria CABIMER, Spain Editorial Board Dr William Bush Vanderbilt University, USA Prof Jose-Maria Carazo National Center for Biotechnology, Spain Prof Rita Casadio University of Bologna, Italy Prof Krzysztof Cios Virginia Commonwealth University, USA Dr Dragan Gamberger Rudjer Boskovic Institute, Croatia Dr Dominik Heider University of Duisburg-Essen, Germany Prof David Jones University College London, UK Prof Simon Kasif Boston University, USA Prof Ju Han Kim Seoul National University College of Medicine, South Korea Professor Pedro Larranaga Technical University of Madrid, Spain Prof Zhigang Li Geisel School of Medicine at Dartmouth, USA Dr Elena Marchiori Radboud University Nijmegen, Netherlands Dr Brett McKinney University of Tulsa, USA Prof Andrea Omicini University of Bologna, Italy Prof Jorg Rahnenfuhrer Technical University Dortmund, Germany Dr Reinhard Schneider University of Luxembourg, Luxembourg Prof Dan Simovici University of Massachusetts Boston, USA Dr Stefano Volinia Ohio State University, USA Dr Igor Zwir Washington University in St. Louis, USA