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As a result of the significant disruption that is being caused by the COVID-19 pandemic we are very aware that many researchers will have difficulty in meeting the timelines associated with our peer review process during normal times. Please do let us know if you need additional time. Our systems will continue to remind you of the original timelines but we intend to be highly flexible at this time.

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New Content ItemThe coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on population health and wellbeing. Biomedical informatics is central to COVID-19 research efforts and for the delivery of healthcare for COVID-19 patients. Critical to this effort is the participation of informaticians who typically work on other basic science or clinical problems. The goal of this editorial is to highlight some examples of COVID-19 research areas that could benefit from informatics expertise. Each research idea summarizes the COVID-19 application area, followed by an informatics methodology, approach, or technology that could make a contribution. It is our hope that this piece will motivate and make it easy for some informaticians to adopt COVID-19 research projects.

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New Content ItemWe are excited to announce that our Aims & Scope has undergone some changes, incorporating an encouragement of submissions pertaining to Artificial Intelligence, Machine Learning, and Visual Analytics, and expanding the data types we consider, to include imaging, electronic health records, biobanks, environmental data, social and behavioral data, wearable devices, and social media data. Please click here to check out the new Aims & Scope and types of submissions that we readily encourage you to submit.

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New Content ItemOur new thematic series, edited by Jason Moore and Marylyn Ritchie, seeks manuscripts on the topic of machine learning. We are interested in both original research and review papers, especially those that address new and novel machine learning methods and their application to biological and biomedical big data. The series is open, and you can find out more about it (including submission instructions), here.

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New Content ItemWe are happy to announce that our Editors-in-Chief, Jason H. Moore and Marylyn D. Ritchie, have recently launched a podcast! The Biomedical Informatics Roundtable Podcast aims to bring you discussion of hot topics, recent papers, news, conferences, open data, open-source software, and advice for trainees as well as interviews and spotlights biomedical informatics colleagues from around the world. Please check out Dr Moore and Dr Ritchie’s podcast, here!

进外网能用的网站你懂得

  1. 进外网能用的网站你懂得

    Authors: Olga Fajarda, Sara Duarte-Pereira, Raquel M. Silva and José Luís Oliveira

    Content type: Research

  2. 进外网能用的网站你懂得

    Authors: J. Magaña, M. G. Contreras, K. L. Keys, O. Risse-Adams, P. C. Goddard, A. M. Zeiger, A. C. Y. Mak, J. R. Elhawary, L. A. Samedy-Bates, E. Lee, N. Thakur, D. Hu, C. Eng, S. Salazar, S. Huntsman, T. Hu…

    Content type: Research

  3. 进外网能用的网站你懂得

    Authors: Hao-Chih Lee, Osamu Ichikawa, Benjamin S. Glicksberg, Aparna A. Divaraniya, Christine E. Becker, Pankaj Agarwal and Joel T. Dudley

    Content type: Methodology

  4. 进外网能用的网站你懂得

    Authors: Pourya Naderi Yeganeh, Chrsitine Richardson, Erik Saule, Ann Loraine and M. Taghi Mostafavi

    Content type: Research

  5. 进外网能用的网站你懂得

    Authors: Shiyan Li, Hongxin Liu, Shiyu Bian, Xianzheng Sha, Yixue Li and Yin Wang

    Content type: Research

  1. 进外网能用的网站你懂得

    Authors: Georgios A Pavlopoulos, Maria Secrier, Charalampos N Moschopoulos, Theodoros G Soldatos, Sophia Kossida, Jan Aerts, Reinhard Schneider and Pantelis G Bagos

    Content type: Review

  2. 进外网能用的网站你懂得

    Authors: Emad A Mohammed, Behrouz H Far and Christopher Naugler

    Content type: Review

  3. 进外网能用的网站你懂得

    Authors: Davide Chicco

    Content type: Review

  4. 进外网能用的网站你懂得

    Authors: Masanori Arita and Kazuhiro Suwa

    Content type: Research

  5. 进外网能用的网站你懂得

    Authors: Georgios A Pavlopoulos, Anastasis Oulas, Ernesto Iacucci, Alejandro Sifrim, Yves Moreau, Reinhard Schneider, Jan Aerts and Ioannis Iliopoulos

    Content type: Review

进外网能用的网站你懂得

Dr Jason Moore, University of Pennsylvania, USA
Dr Marylyn Ritchie, University of Pennsylvania, USA

进外网能用的网站你懂得

BioData Mining is an open access, open peer-reviewed, informatics journal encompassing research on all aspects of Artificial Intelligence (AI), Machine Learning, and Visual Analytics, applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, genomic, metabolomic data and/or electronic health records, social determinants of health, and environmental exposure data. Please see here for more information on data types and topical areas.

进外网能用的网站你懂得

进外网能用的网站你懂得

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进外网能用的网站你懂得

Dr Jason Moore is the Edward Rose Professor of Informatics, Professor of Biostatistics and Epidemiology, and Professor of Genetics at the Perelman School of Medicine of the University of Pennsylvania. He serves as the first permanent Director of the Institute for Biomedical Informatics and founding Director of the Division of Informatics in the Department of Biostatistics and Epidemiology. He also serves as Senior Associate Dean for Informatics. His work has been communicated in more than 400 scientific publications and he serves as PI on several NIH R01 grants. He has been recognized as a national leader in informatics through election as a Fellow of the American Association for the Advancement of Sciences (AAAS) and as a Kavli Fellow of the National Academy of Sciences (NAS). He was recently elected a Fellow of the American College of Medical Informatics (ACMI).

Marylyn D. Ritchie, PhD is a Professor in Genetics, Director of the Center for Translational Bioinformatics, and Associate Director for Bioinformatics in the Institute for Biomedical Informatics at the University of Pennsylvania School of Medicine.  Dr. Ritchie is a computational geneticist and biomedical informatician with a focus on detecting disease-susceptibility genes associated with common, complex human disease and integrating electronic health records with genomics. She has expertise in developing novel bioinformatics tools for complex analysis of big data in genetics, genomics, and clinical databases, in particular in the area of Pharmacogenomics.  Some of her methods include Multifactor Dimensionality Reduction (MDR), the Analysis Tool for Heritable and Environmental Network Associations (ATHENA), and the Biosoftware suite for annotating/ filtering variants and genomic regions as well as building models of biological relevance for gene-gene interactions and rare-variant burden/dispersion tests.  Dr. Ritchie has over 15 years of experience in the analysis of complex data and has authored over 300 publications (H-index 76).  She is one of Thomas Reuters Most Highly Cited Researchers for 2014.  Dr. Ritchie has extensive experience in leading large collaborative efforts; has been a part of national networks using electronic health records and genomics data; has excellent organizational and leadership skills.  Dr. Ritchie is well suited to be a collaborator on this project.

进外网能用的网站你懂得

进外网能用的网站你懂得

  • Speed
    43 days to first decision for reviewed manuscripts only
    27 days to first decision for all manuscripts
    126 days from submission to acceptance
    22 days from acceptance to publication


    Citation Impact
    2.672 - 2-year Impact Factor
    2.176 - 5-year Impact Factor
    1.195 - Source Normalized Impact per Paper (SNIP)
    1.004 - SCImago Journal Rank (SJR)


    Usage 
    155,529 Downloads
    151 Altmetric mentions

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