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Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives

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 biomed...

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Autores principales: Merelli, Ivan, Pérez-Sánchez, Horacio, Gesing, Sandra, D'Agostino, Daniele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165507/
https://www.ncbi.nlm.nih.gov/pubmed/25254202
http://dx.doi.org/10.1155/2014/134023
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author Merelli, Ivan
Pérez-Sánchez, Horacio
Gesing, Sandra
D'Agostino, Daniele
author_facet Merelli, Ivan
Pérez-Sánchez, Horacio
Gesing, Sandra
D'Agostino, Daniele
author_sort Merelli, Ivan
collection PubMed
description 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.
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spelling pubmed-41655072014-09-24 Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives Merelli, Ivan Pérez-Sánchez, Horacio Gesing, Sandra D'Agostino, Daniele Biomed Res Int Review Article 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. Hindawi Publishing Corporation 2014 2014-09-01 /pmc/articles/PMC4165507/ /pubmed/25254202 http://dx.doi.org/10.1155/2014/134023 Text en Copyright © 2014 Ivan Merelli et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Merelli, Ivan
Pérez-Sánchez, Horacio
Gesing, Sandra
D'Agostino, Daniele
Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
title Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
title_full Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
title_fullStr Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
title_full_unstemmed Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
title_short Managing, Analysing, and Integrating Big Data in Medical Bioinformatics: Open Problems and Future Perspectives
title_sort managing, analysing, and integrating big data in medical bioinformatics: open problems and future perspectives
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4165507/
https://www.ncbi.nlm.nih.gov/pubmed/25254202
http://dx.doi.org/10.1155/2014/134023
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