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The Bioinformatics & Drug Design Lab provides an integrated bioinformatics analysis and drug design platform focusing on the following five aspects: constructing an comprehensive and large biomedical data warehouse; data mining techniques for extraction of useful results from large amounts of biological data; undertaking assay of  omics, including proteomics and metabolomics; dealing with methods for storing, retrieving and analyzing biological data, such as nucleic acid and protein sequences, structures, functions, pathways and genetic interactions; computer-aided drug design (CADD) technology from the availability of bioinformatics applications.



Ø Biomedical Database

We construct biomedical data warehouse by collecting and integrating databases of different biomedical domains. By now, these biomedical databases including SinoMed, PubMed, OMIM, GO, NCI pathway interaction database, MeSH, PubChem, TCMDB, PDB, ChEMBL, PharmaGKB, TTD, DrugBank, UniProt, UMLS and KEGG.


Ø Data Mining

Based on the biomedical database, typical text mining tasks include text categorization, text clustering, concept / entity extraction, sentiment analysis and document summarization are performed to derive high-quality information from these texts.


Ø Assay of Proteomics & Metabolomics

The lab provides a comprehensive analysis platform for protein and metabolite. Two widely used and powerful methods, including Gas chromatography (GC) and High performance liquid chromatography (HPLC) are used for separation in the lab. Furthermore, Mass spectrometry (MS) is applied to identify and to quantify metabolites after separation by GC, HPLC. Also several statistical programs are available for analysis of MS data.


Ø Bioinformatics Analysis

By applying computationally intensive techniques, we develop new algorithms and statistics with which to assess relationships among members of large data sets, to increase the understanding of biological processes. Also commercial software, such as ingenuity pathway analysis (IPA) is often used for casual network analysis, comparison analysis, upstream regulator analysis, mechanistic networks and pathway analysis.


Ø Computer-Aided Drug Design

With understanding the structure of small molecules, proteins and nucleic acids, we apply computer-aided drug design (CADD) technology to discover or design active compounds to cure the diseases. To further understand the mechanism of effects of drug / drug combination on biological network, we also develop structure- based technology to identify targets of compounds from drug / drug combination.