Collaborative software for traditional and translational research

被引:3
|
作者
Berman, Ari E. [1 ]
Barnett, William K. [2 ]
Mooney, Sean D. [1 ]
机构
[1] Buck Inst Res Aging, Bioinformat Core, Novato, CA 94945 USA
[2] Indiana Univ, Bloomington, IN 47405 USA
基金
美国国家卫生研究院;
关键词
CTSA CONSORTIUM; SCIENCE;
D O I
10.1186/1479-7364-6-21
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Biomedical research has entered a period of renewed vigor with the introduction and rapid development of genomic technologies and next-generation sequencing methods. This research paradigm produces extremely large datasets that are both difficult to store and challenging to mine for relevant data. Additionally, the thorough exploration of such datasets requires more resources, personnel, and multidisciplinary expertise to properly analyze and interpret the data. As a result, modern biomedical research practices are increasingly designed to include multi-laboratory collaborations that effectively distribute the scientific workload and expand the pool of expertise within a project. The scope of biomedical research is further complicated by increased efforts in translational research, which mandates the translation of basic laboratory research results into the human medical application space, adding to the complexity of potential collaborations. This increase in multidisciplinary, multi-laboratory, and biomedical translational research identifies a specific need for formalized collaboration practices and software applications that support such efforts. Here, we describe formal technological requirements for such efforts and we review several software solutions that can effectively improve the organization, communication, and formalization of collaborations in biomedical research today.
引用
收藏
页数:9
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