Bioinformatics introduction

Content:

In the two lectures in this week, the main topic mainly focuses on the bioinformatics. Dr.Dinu gave us a well organized introduction from the what kind of data in bioinformatics study to the usually used computational methods in this field. In the first part, many important bioinformatics data was introduced, including the microarray data, genomic data, DNA/Protein sequence, also many important bioinformatics data source are also talked about, such as the NCBI, uniprot, PDB bank, where is usually the starting point for getting initial bioinformatics information for research. In the second part of the class, the prevelant bioinformatics research methods were discussed, which covers the statistics method, such as the chi_square test, t-test, and also the datamining method used in bioinformatics study was also covered. From the second part, I got an understanding about how to connect the previous learned datamining method to the applications in real bioinformatics research. Take the clustering as an exampl. The functional catagorizing similar gene expression to a group is just based on the clustering method. The other usually used bioinformatics analysis method is the blaster method, which can search the gene or protein database to match the most similar gene or protein sequence to the enquiry sequence. In the bioinformatics study for protein, based on the most similar sequence, the homology modeling can be performed to build up the 3 dimensional protein structure for further molecular simulation. The above two applications are mainly in the physical simulation domain, which is a subdomain under the computational biology field. The other fields of bioinformatics, I feel the statistics technologies would be more invovled.

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Di Pan