title: Managing, analysing, and integrating big data in medical bioinformatics: open problems and future perspectives.
abstract: The explosion of the data both in the biomedical research and in the healthcare systems demands urgent solutions. In particular, the research in omics sciences is moving from a hypothesis-driven to a data-driven approach. Healthcare is additionally always asking for a tighter integration with biomedical data in order to promote personalized medicine and to provide better treatments. Efficient analysis and interpretation of Big Data opens new avenues to explore molecular biology, new questions to ask about physiological and pathological states, and new ways to answer these open issues. Such analyses lead to better understanding of diseases and development of better and personalized diagnostics and therapeutics. However, such progresses are directly related to the availability of new solutions to deal with this huge amount of information. New paradigms are needed to store and access data, for its annotation and integration and finally for inferring knowledge and making it available to researchers. Bioinformatics can be viewed as the "glue" for all these processes. A clear awareness of present high performance computing (HPC) solutions in bioinformatics, Big Data analysis paradigms for computational biology, and the issues that are still open in the biomedical and healthcare fields represent the starting point to win this challenge.
authors.affiliation: Bioinformatics Research Unit, Institute for Biomedical Technologies, National Research Council of Italy, Segrate, 20090 Milan, Italy.
authors.forename: Ivan
authors.initials: I
authors.lastname: Merelli
authors.affiliation: Bioinformatics and High Performance Computing Research Group (BIO-HPC), Computer Science Department, Universidad Católica San Antonio de Murcia (UCAM), 30107 Murcia, Spain.
authors.forename: Horacio
authors.initials: H
authors.lastname: Pérez-Sánchez
authors.affiliation: Department of Computer Science and Engineering, Center for Research Computing, University of Notre Dame, P.O. Box 539, Notre Dame, IN 46556, USA.
authors.forename: Sandra
authors.initials: S
authors.lastname: Gesing
authors.affiliation: Advanced Computing Systems and High Performance Computing Group, Institute of Applied Mathematics and Information Technologies, National Research Council of Italy, 16149 Genoa, Italy.
authors.forename: Daniele
authors.initials: D
authors.lastname: D'Agostino
mesh_terms: D035843:Biomedical Research; D019295:Computational Biology / Q000379:methods*; D057225:Data Mining / Q000379:methods*; D003695:Delivery of Health Care; D006801:Humans; D057285:Precision Medicine; D012984:Software