期刊论文详细信息
BMC Bioinformatics
Integrated Bio-Search: challenges and trends for the integration, search and comprehensive processing of biological information
Review
Paolo Romano1  Erik Bongcam-Rudloff2  Stefano Ceri3  Marco Masseroli3  Alexander Kel4  François Rechenmann5  Barend Mons6  Frederique Lisacek7 
[1] Biopolymers and Proteomics, IRCCS AOU San Martino IST, 16132, Genoa, Italy;Department of Animal Breeding and Genetics, SLU-Global Bioinformatics Centre, Swedish University of Agricultural Sciences, 75124, Uppsala, Sweden;Department of Immunology, Genetics and Pathology, Uppsala University, 75108, Uppsala, Sweden;Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133, Milano, Italy;GeneXplain GmbH, 38302, Wolfenbüttel, Germany;Institute of Chemical Biology and Fundamental Medicine SBRAS, 630090, Novosibirsk, Russia;Inria Grenoble Rhône-Alpes, 38334, Saint-Ismier cedex, France;Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands;Netherlands Bioinformatics Center, 6500 HB, Nijmegen, The Netherlands;Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, 1211, Geneva 4, Switzerland;Section of Biology, University of Geneva, 1211, Geneva 4, Switzerland;
关键词: Unify Modeling Language;    Resource Description Framework;    Text Mining;    Research Infrastructure;    Gene Interaction Network;   
DOI  :  10.1186/1471-2105-15-S1-S2
来源: Springer
PDF
【 摘 要 】

Many efforts exist to design and implement approaches and tools for data capture, integration and analysis in the life sciences. Challenges are not only the heterogeneity, size and distribution of information sources, but also the danger of producing too many solutions for the same problem. Methodological, technological, infrastructural and social aspects appear to be essential for the development of a new generation of best practices and tools. In this paper, we analyse and discuss these aspects from different perspectives, by extending some of the ideas that arose during the NETTAB 2012 Workshop, making reference especially to the European context.First, relevance of using data and software models for the management and analysis of biological data is stressed. Second, some of the most relevant community achievements of the recent years, which should be taken as a starting point for future efforts in this research domain, are presented. Third, some of the main outstanding issues, challenges and trends are analysed. The challenges related to the tendency to fund and create large scale international research infrastructures and public-private partnerships in order to address the complex challenges of data intensive science are especially discussed. The needs and opportunities of Genomic Computing (the integration, search and display of genomic information at a very specific level, e.g. at the level of a single DNA region) are then considered.In the current data and network-driven era, social aspects can become crucial bottlenecks. How these may best be tackled to unleash the technical abilities for effective data integration and validation efforts is then discussed. Especially the apparent lack of incentives for already overwhelmed researchers appears to be a limitation for sharing information and knowledge with other scientists. We point out as well how the bioinformatics market is growing at an unprecedented speed due to the impact that new powerful in silico analysis promises to have on better diagnosis, prognosis, drug discovery and treatment, towards personalized medicine. An open business model for bioinformatics, which appears to be able to reduce undue duplication of efforts and support the increased reuse of valuable data sets, tools and platforms, is finally discussed.

【 授权许可】

CC BY   
© Masseroli et al.; licensee BioMed Central Ltd. 2013

【 预 览 】
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