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卫健学术沙龙:基于5G+人工智能的心理/精神健康服务与管理体系建设
Gauging spacetime inversions
AI合成化学前沿与战略研讨会暨国家智能化学数据中心启动会
Macro to micro- and nano-scale fluidic engineering for analytical chemistry
报告题目:
Extraction and Application of Geometrical Features from 3-dimensional Images for Protein Structure Prediction
 报告人:
Jing He
Department of Computer Science
CREST Center for Bioinformatics and Computational Biology
New Mexico State University, USA
报告时间:
2007-01-10 15:00
报告地点:
东主楼10-309
主办单位:
电子系
  简介:

  报告题目:

内容简介:Protein structure prediction is also known as the protein folding problem that attracts the scientists from many disciplines. Typically, the structure of a protein is predicted if its amino acid sequence is given. However, current structure prediction methods are still far from being mature. We have been investigating the problem of combining the structure prediction methods with geometrical constraints that can be obtained from the low resolution 3-dimensional image of protein density. We have developed a gradient based segmentation method to identify the helices of a protein. Using the identified helices as geometrical constraints, we developed a method to analyze a large set of possible model structures generated by Rosetta, a structure prediction software. The possible sequence assignment and topology of the visualized helices can be derived. (There is an opening for Postdoctoral Research Position)

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