Merging Medical Informatics and Bioinformatics for Personalized Medicine
A special issue of Journal of Personalized Medicine (ISSN 2075-4426).
Deadline for manuscript submissions: closed (5 June 2020) | Viewed by 442
Special Issue Editors
2. School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA
Interests: genomics for predictive health; transcriptional variation; integrative genomics and wellness; genetics of inflammatory disease
Special Issues, Collections and Topics in MDPI journals
Interests: translational bioinformatics; precision medicine; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Personalized medicine embraces a spectrum of approaches for evidence-driven medical care, ranging from precision molecular diagnosis to genome-based prediction of disease onset or progress. One emerging frontier is the merging of bioinformatics with medical informatics, i.e., the use big data analytical methods to learn the attributes of patients that may be informative for genetic analysis. Consequently, we aim to present a series of papers that describes new approaches using machine learning and very-large-scale data analytics to approaching critical problems in medicine. The scope may include practical issues such as the development of applications that facilitate the translation to bedside care, theoretical approaches for merging bioinformatics and medical informatics, or focused case studies. Medical informatics and bioinformatics have developed in parallel, with both fields attracting more and more students and generating excellent career prospects for them. We are finding that computer science, biomedical engineering, genetics, and medical trainees are increasingly interested in the interface of their disciplines. Now is an excellent time to promote integrative biomedical informatics. Big data is at the cutting edge of personalized medicine, and very large biobanks are driving the research agenda. At the same time, it is critical that translational research addresses the challenges in moving analytical discoveries into pipelines for personal care. We welcome studies that embrace machine learning, parsing of electronic medical records, processing of million-plus-sample genomic datasets, and of 10 million-plus public health datasets. Research on the subclassification of disease, joint modeling of genetic and clinical attributes, and ancestry-dependent biases in personalized medicine will also be particularly welcome.
Prof. Dr. Marylyn D. Ritchie
Prof. Jason H. Moore
Prof. Dr. Greg Gibson
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- medical informatics
- big data
- predictive health
- machine learning
- genomics
