Advanced Chemoinformatics

Subject Name:           Advanced Chemoinformatics

Subject code:            M43630210

Teacher:                     Prof. Yoshimasa Takahashi; Asc. Prof Hiroaki kato

Year grade:               Graduate students in master program.

Term:                        Spring

Credit:                      2 (Option)


[Course Description]

The purpose of this course is to introduce and explain practical and applied approaches to multivariate data analysis (or mining) and knowledge discovery with illustrative examples through chemical data space. The course is helpful for the students who are interested in not only pursuing careers in chemo-informatics but also taking general data science.



Topics to be covered:

1.Structure and information of biomacromolecules
2.Transmission and expression of the genetic information
3.Molecular biology database
4.Sequence allignment by DP matching
5.Homology searching and multuiple allignment
6.Sequence motif and knowledge base
7.Tertiary structure classification and function prediction
9.Chemical data space and multivariate data analysis
10.Quantitative structure-activity relationships (QSAR)
11.Principal component analysis (PCA) and data visualization
12.Data clustering
13.Linear binary pattern classifier and perceptron model
14.Artificial neural network and chemical application
15.Support vector machine and chemical application



Office: F-303 (Ext. 6878) Email: (Takahashi)

Office: F-304 (Ext. 6879) Email: (Kato)