现在他的目标是挖掘和整合数据来以便更好地参透广阔的生物界图景。
Now the goal is to mine and integrate these data sets to better understand the big biological picture.
通过有效手段从整合的异构生物信息资源中获取高质量的生物数据，能够为生物信息的分析和挖掘提供强有力的支持。
The analysis and mining of bioinformation can be strongly supported by means of acquiring high quality bio-data efficiently and conveniently from integrated heterogeneous bioinformation resource.
来自这两种实验的数据非常庞大而计算繁琐，令生物学家们非常苦恼，不知如何进行整合。
The data that results from these types of experiments is substantial and computational biologists have struggled with how to integrate them.
为了最大化基因组序列的价值，它们需要用其他类型的生物学数据及彼此进行整合。
To maximize the value of genome sequences they need to be integrated with other types of biological data and with each other.
定义了新兴数字生物学学科的三个关键领域：科学数据整合，多尺度建模和网络科学。
Three key areas that define the emerging discipline of digital biology are: scientific data integration, multi-scale modeling and networked science.
微阵列非常适合于整合的系统生物学方式，但是没有一个现有的微阵列数据库是集中于拷贝数变化的。
Microarrays are well suited for the integrative systems biology approach, but none of the existing microarray databases is focusing on copy number changes.
为了构建新的知识，生物学数据的多种来源常常必需被整合。
In order to build new knowledge, various sources of biological data must often be combined.
MGD也是一个整合的生物学数据的计算评估平台，目的是识别与复杂表型相关的候选基因。
MGD is also a platform for computational assessment of integrated biological data with the goal of identifying candidate genes associated with complex phenotypes.
计算系统生物学是一个多学科交叉的新兴领域，旨在通过整合海量数据建立其生物系统相互作用的复杂网络。
Computational systems biology is a multi-disciplinary field which aims at simulating the interactions of complex biological systems by integrating large quantities of biological data.
GOBASE是包含了关于细胞器的整合序列、RNA二级结构及生物化学和分类学信息的一个关系数据库。
GOBASE is a relational database containing integrated sequence, RNA secondary structure and biochemical and taxonomic information about organelles.
生物医学本体论提供了必要的领域知识以驱动数据整合、信息检索、数据注释、自然语言处理和决策支持。
Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support.
生物医学本体论提供了必要的领域知识以驱动数据整合、信息检索、数据注释、自然语言处理和决策支持。
Biomedical ontologies provide essential domain knowledge to drive data integration, information retrieval, data annotation, natural-language processing and decision support.
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