Health and Biomedical Informatics Centre (HABIC), The University of Melbourne, Melbourne, Victoria, 3010, Australia.
Faculty of Veterinary Sciences, Department of Animal Health, Complutense University, Madrid, 28040, Spain.
Health Inf Sci Syst. 2015 Feb 24;3(Suppl 1 HISA Big Data in Biomedicine and Healthcare 2013 Con):S5. doi: 10.1186/2047-2501-3-S1-S5. eCollection 2015.
To describe the importance of bioinformatics tools to analyze the big data yielded from new "omics" generation-methods, with the aim of unraveling the biology of the pathogen bacteria Lactococcus garvieae.
The paper provides the vision of the large volume of data generated from genome sequences, gene expression profiles by microarrays and other experimental methods that require biomedical informatics methods for management and analysis.
The use of biomedical informatics methods improves the analysis of big data in order to obtain a comprehensive characterization and understanding of the biology of pathogenic organisms, such as L. garvieae.
The "Big Data" concepts of high volume, veracity and variety are nowadays part of the research in microbiology associated with the use of multiple methods in the "omic" era. The use of biomedical informatics methods is a requisite necessary to improve the analysis of these data.
描述生物信息学工具在分析新“组学”生成方法产生的大数据中的重要性,旨在揭示病原菌乳球菌的生物学特性。
本文提供了从基因组序列、微阵列基因表达谱和其他实验方法中产生的大量数据的视角,这些数据需要生物医学信息学方法进行管理和分析。
生物医学信息学方法的使用改进了大数据的分析,以便对病原菌(如乳球菌)的生物学进行全面的描述和理解。
大容量、准确性和多样性的“大数据”概念是当今与“组学”时代多种方法使用相关的微生物学研究的一部分。生物医学信息学方法的使用是改进这些数据分析的必要条件。