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通过机器学习进行代谢物鉴定和分子指纹预测Metabolite identification and molecular fingerprint prediction via machine learning |
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| 课程网址: | http://videolectures.net/mlsb2012_heinonen_metabolite/ |
| 主讲教师: | Markus Heinonen |
| 开课单位: | 赫尔辛基大学 |
| 开课时间: | 2012-10-23 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | **Motivation:** Metabolite identification from tandem mass spectra is an important problem in metabolomics, underpinning subsequent metabolic modelling and network analysis. Yet, currently this task requires matching the observed spectrum against a database of reference spectra originating from similar equipment and closely matching operating parameters, a condition that is rarely satisfied in public repositories. Furthermore, the computational support for identification of molecules not present in reference databases is lacking. Recent efforts in assembling large public mass spectral databases such as MassBank have opened the door for the development of a new genre of metabolite identification methods.\\ **Results:** We introduce a novel framework for prediction of molecular characteristics and identification of metabolites from tandem mass spectra using machine learning with the support vector machine (SVM). Our approach is to first predict a large set of molecular properties of the unknown metabolite from salient tandem mass spectral signals, and in the second step to use the predicted properties for matching against large molecule databases, such as PubChem. We demonstrate that several molecular properties can be predicted to high accuracy, and that they are useful in de novo metabolite identification, where the reference database does not contain any spectra of the same molecule.\\ |
| 关 键 词: | 串联质谱; 代谢组学; 网络分析 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2021-12-22：liyy |
| 阅读次数: | 58 |