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Special Issue "Current Advances in Network Biology for Disease Understanding"
Deadline for manuscript submissions: 19 October 2019.
Dr. Sujoy Ghosh Website E-Mail
1. Duke-NUS Medical School, Singapore 169857, Singapore
2. National Heart Research Institute, Singapore 169609, Singapore
3. Pennington Biomedical Research Center, Baton Rouge, LA 70808, USA
Interests: integrative bioinformatics; systems genomics; obesity genetics and genomics; nutrigenomics; functional genomics
Biological processes involve a wide range of hierarchically layered intermolecular connections, such as protein–protein interactions, protein–DNA interactions, functional gene regulatory modules, signal transduction, etc. Similar to the more widely discussed social, professional, or internet-type networks, biological interactions can also be mathematically represented as mostly scale-free, small-world networks with nodes denoting molecules, and edges denoting specific relations or interactions between them. In addition to molecular interactions, biological networks also encompass higher-level organizations, such as those involving disease relationships (disease networks) or patient sub-groups within a clinical diagnosis (patient similarity networks). Network science is currently a highly active area of biological research. This is due to the confluence of a triumvirate of factors: (i) the generation and access to explosively large volumes of “omics” data from high-throughput experiments, and large-scale patient information from electronic medical records; (ii) the intensive development of deep computational methodologies and data visualization tools for the analysis of complex networks; and (iii) the urgent need for new approaches to interrogate complex disorders to effect transformative changes in clinical care. Network biology provides a novel conceptual framework that illuminates biological phenomena and provides new paths for their manipulation.
This Special Issue is dedicated to highlighting the current frontline status of network research today through expert commentaries on all three of the factors described above. We welcome the submission of reviews, research articles, and short communications encompassing diverse aspects of network science, including computational approaches (e.g., new algorithms for network construction, network visualization, and network analysis), investigations of network behaviour in molecular- to population-level datasets, and experimental manipulation of network components for testing predicted robustness and vulnerabilities in the context of network medicine.
Dr. Sujoy Ghosh
Dr. Enrico G. Petretto
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 papers will be 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. Genes 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 1800 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.
- biomolecular interactions
- data visualization
- computational biology