translational research highly depends on Translational research organizations.America is the leading country in science and technology. It is very important to learn from America successful experience in order to develop perfect translational research organization.This paper analyzed the needs of changing the current research organization,and provided some suggestions for Chinese translational research organization based on understanding the differences between America and Chinese present research organization.

The nature of collaborative innovation is to share the resources for innovation through management,which would play great role in scientific policy change in China. Translational medicine actually is combine theory and daily practice,basic and clinic research,which need multidiscipline,collaboration between different areas.Collaborative innovation is the requirement of translational medicine.Therefore,establishing research organization with characteristic of collaborative innovation is the key for the development of translational medicine.

The replicase genes of five isolates of Cucumber green mottle mosaic virus from Jiangsu, Zhejiang, Hunan and Beijing were amplificated, sequenced and analyzed. The similarities of nucleotide acid sequences indicated that 129 kD and 57 kD replicase genes of CGMMV-No. 1, CGMMV-No. 2, CGMMV-No. 3, CGMMV-No. 4 and CGMMV-No. 5 were 99.64% and 99.74%, respectively. The similarities of 129 kD and 57 kD replicase genes of CGMMV-No. 1, CGMMV-No. 3 and CGMMV-No. 4 were 99.95% and 99.94%, while they were lower between CGMMV-No. 2 and the rest of four reference sequences, just from 99.16% to 99.27% and from 99.04% to 99.18%. All reference sequences could be divided into six groups in neighbor-joining (NJ) phylogenetic trees based on the replicase gene sequences of 129 kD, 57 kD protein respectively. CGMMV-No. 1, CGMMV-No. 3 and CGMMV-No. 4 were clustered together with Shandong isolate (Accession No. KJ754195) in two NJ trees; CGMMV-No. 5 was clustered together with Liaoning isolate (Accession No. EF611826) in two NJ trees; CGMMV-No. 2 was clustered together with Korea watermelon isolate (Accession No. AF417242) in phylogenetic tree of 129 kD replicase gene of CGMMV; Interestingly, CGMMV-No. 2 was classified as a independent group in phylogenetic tree of 57 kD replicase gene of CGMMV. There were no significant hydrophobic and highly coiled coil regions on 129 kD and 57 kD proteins of tested CGMMV isolates. Except 129 kD protein of CGMMV-No. 4, the rest were unstable protein. The number of transmembrane helical segments (TMHs) of 129 kD protein of CGMMV-No. 1, CGMMV-No. 2, CGMMV-No. 3 and CGMMV-No. 5 were 6, 6, 2 and 4, respectively, which were 13, 13 and 5 on the 57 kD protein of CGMMV-No. 2, CGMMV-No. 4 and CGMMV-No. 5. The glycosylation site of 129 kD protein of tested CGMMV isolates were 2, 4, 4, 4 and 4, and that of 57 kD protein were 2, 5, 2, 5 and 2. There were difference between the disorders, globulins, phosphorylation sites and B cell antigen epitopes of 129 kD and 57 kD proteins of tested CGMMV isolates. The current results that there was no significant difference between the replicase gene sequences, it was stable and conservative for intra-species and clearly difference for inter-species. CGMMV-No. 1, CGMMV-No. 3, CGMMV-No. 4 and CGMMV-No. 5 had. a close genetic relationship with Shandong and Liangning isolates (Accession No. KJ754195 and EF611826), they are potentially originate from the same source. CGMMV-No. 2 was closer with Korea isolate. High sequence similarity of tested samples were gathered for a class in phylogenetic tree. It didn't show regularity of the bioinformatics analysis results of 129 kD and 57 kD proteins of tested CGMMV isolates. There was no corresponding relationship among the molecular phylogeny and the bioinformatics analysis of the tested CGMMV isolates.
Computational Biology ; Cucumis sativus ; chemistry ; classification ; enzymology ; genetics ; Molecular Sequence Data ; Phylogeny ; Plant Diseases ; virology ; RNA Replicase ; chemistry ; genetics ; metabolism ; Sequence Homology, Nucleic Acid ; Viral Proteins ; chemistry ; genetics ; metabolism

Objective To explore the impact of biological big data on clinical study management.Methods To understand the changeof clinical study resulted from big data from the perspectiveof scientific study management.Results Bigdata Clinical Trial (BCT) based on massive clinical study data will turn out to be one of the most important parts of clinical study gradually.General rules target population will be obtained from clinical study model of the whole population.Reality fact will be more closely approached by the results of study on macro factors.Precise trend of dynamic changes can be demonstrated via data of full time linear tracking studies.Data collection will include those unordered data which are potentially inaccurate andregarded as useless in small data time.Conclusions Revolutionary changes will be presented in clinical study model in which data acquisition and info analysis are used as the primary approaches in big data era,and prediction of clinical study developmenttrend based on big data as well as innovation of management model for clinical study will make power ful support for better utilization of big data tools and accomplishment for big data realization and precision technology.