课题基金 / 基金详情

Doctoral Training in Bioinformatics

Doctoral Training in Bioinformatics
生物信息学博士培训
批准号:
6748309
负责人:
CHARLES DELISI
金额:
$17.81万
依托单位国家:
美国
项目类别:
财政年份:
2004
资助国家:
美国
项目状态:
已结题
起止时间:
2004-07-01 至 2009-06-30

项目摘要

项目成果

CHARLES DELISI的其他基金

相似基金

相关文献

中文摘要
翻译
描述(由申请人提供):基因组学是进化,发育生物学,更广泛地说,是正常和病理状态下细胞的分子生物学的革命性研究。它有望通过开发基于分子指纹的新诊断、药物靶标识别和个体化医疗来彻底改变医学。这场革命依赖于高通量实验方法,密切相关的高通量计算方法——机器学习算法、数理统计等——以及现代信息技术,这些技术允许成千上万的用户之间轻松地进行多对多通信。我们的生物信息学博士课程目前旨在培养两个不同的群体:将成为该领域专业人士的研究人员;即谁将通过开发创造性实验研究所需的新方法来推动它;生物医学研究人员将成为这些技术的用户。由于计算和实验是紧密耦合的,除了在计算方法方面的强化训练外,该项目的所有学生都必须有在实验台上的动手经验。由于认识到这些技术可能对社会结构产生的深远影响,所有学生都被要求修一门关于基因组学的法律和伦理影响的全学分核心课程。
英文摘要
DESCRIPTION (provided by applicant): Genomics is revolutionizing research in evolution, developmental biology and, more generally, in the molecular biology of the cell in normal and pathological states. It promises to revolutionize medicine by the development of new diagnostics based on molecular fingerprints, the identification of drug targets, and individualized medicine. The revolution rests on high throughput experimental methods, closely associated high throughput computational methods--machine learning algorithms, mathematical statistics and the like---and modem information technologies that permit easy many to many communication between thousands of users. Our Ph.D. Program in Bioinformatics is currently directed at training two different groups: researchers who will become professionals in the field; i.e. who will move it forward by the development of new methods required for creative experimental research; and biomedical researchers who will be users of the technologies. Because computation and experiment are tightly coupled, all students in the Program must have hands on experience at the bench in addition to intensive training in computational methods. In recognition of the profound effect these technologies are likely to have on the social fabric, all students are required to take a core, full-credit course on legal and ethical implications of genomics.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
New Methods for Cancer Class Discovery and Prediction: Integration, visualization
New Methods for Cancer Class Discovery and Prediction: Integration, visualization
Computational Methods for Transcriptional Mapping of Eukaryotic Genomes
Visant-Predictome: A System for Integration, Mining, Visualization and Analysis
海外基金