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.
他们能够将数据挖掘技术应用到医学和生物学领域中的大型数据库中。
They can apply the data mining techniques for very large databases that they learn to research in the medical and biotechnology industries, along with many others.
这些问题的示例包括天气预报、数据挖掘、遗传和生物医学工程，及人工智能应用。
A sampling of these include weather prediction, data mining, genetic and biomedical engineering, and artificial intelligence applications. 5.
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.
在生物统计以及数据挖掘中，分类预测是最基本的任务之一。
Classification is one of the most basic tasks during the biological statistics and data mining.
生物序列分析是机器学习和数据挖掘技术一个重要的应用领域。
Biological sequence analysis is an important application domain of data mining technology.
受生物免疫系统启发的免疫原理已经在控制、规划、图像处理、数据挖掘、故障检测和诊断等领域得到了广泛应用。
The immune theory stimulated by biological immune system has been widely used in control, planning, image processing, data mining, fault detection and diagnosis and other areas.
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.
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.
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.
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.
聚类分析作为一种重要的非监督模式识别工具，可用于多种领域，如数据挖掘、生物学、计算机视觉、文档分析等。
As an important unsupervised pattern recognition tool clustering analysis has been used in diverse fields such as data mining, biology, computer vision, document analysis.
该方法通过挖掘不断膨胀的所有生物、特别是人类的蛋白质序列数据库，以高通量的方式在计算机上进行。
The process is carried out computationally in a high throughput manner by mining the ever-expanding databases of protein sequences of all organisms, especially human.
该方法通过挖掘不断膨胀的所有生物、特别是人类的蛋白质序列数据库，以高通量的方式在计算机上进行。
The process is carried out computationally in a high throughput manner by mining the ever-expanding databases of protein sequences of all organisms, especially human.
应用推荐