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.
本论文的研究方向是生物信息领域的基于基因表达谱的基因挖掘。
The research direction of this dissertation is about the microarray based gene mining in the bioinformatics subject.
我希望可以专注于生物信息学，数据库和数据挖掘技术。
I would like to focus on bio-informatics, database and data mining technology.
本科课程适合智能信息处理、模式识别、大规模数据挖掘、生物信息学等专业的硕士研究生。
The course is suitable for the master degree students working on intelligent information processing, pattern recognition, data mining and bioinformatics.
本研究描绘了生物信息学与数据挖掘这一交叉领域的研究概况，为后续数据挖掘方法与生物信息学研究相结合提供帮助。
This study depicts the overview of the crossing field of data mining and bioinformatics. It is helpful for combining the bioinformatics with data mining.
数据挖掘在生物信息学中的应用将取得更大的进展。
The application of data mining in bioinformatics will gain more development.
乳酸菌基因组蕴含的生物信息将对研究乳酸菌细菌素的合成代谢途径，功能基因挖掘以及新型抗菌剂的开发搭建信息平台。
The information obtained from genomics will provide anew platform for identification of pathways for the bacteriocins production, genome mining and development of new antimicrobial agents.
聚类分析是数据挖掘中重要的研究课题，在信息过滤、资料自动分类、生物信息学等领域得到广泛应用。
Clustering analysis is an important research in data mining, and has been widely used in many fields, such as message filtering, document categorization, bioinformatics, etc.
聚类分析是数据挖掘中重要的研究课题，在信息过滤、资料自动分类、生物信息学等领域得到广泛应用。
Clustering analysis is an important research in data mining, and has been widely used in many fields, such as message filtering, document categorization, bioinformatics, etc.
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