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The Pharmacogenomics Group is directed by Dr. Zhan Zhou, Associate Professor at College of Pharmaceutical Sciences, Zhejiang University. Dr. Zhou was graduated as a Ph.D. from Zhejiang University, majoring in Biochemistry and Molecular Biology. He also studied at the University of Texas at San Antonio as a joint-PhD student. After graduation, he worked as a postdoctoral fellow at the School of Life Sciences, Fudan University. He joined the College of Pharmaceutical Sciences, Zhejiang University in 2014 and is currently Associate Director of the Department of Pharmacy, and also Associate Director of the Institute of Drug Metabolism and Pharmaceutical Analysis. The main research interests of our group are focused on the pharmacogenomics and precision medicine. With the help of big data of multi-omics and artificial intelligence technology, we would like to identify cancer driver genes and mutations, screen tumor-specific neoantigen targets, and design neoantigen-targeting drugs using antibodies and immunotherapies. At present, our group has published more than 80 SCI papers, in the academic journals such as Nat Commun, Mol Ther, Mol Biol Evol, Brief Bioinform and Genom Proteom Bioinform. We also have developed several bioinforamtics tools and databases, such as DeepHLApan, TSNAD, TSNAdb, CovEpiAb, CanDriS,MODIG, and so on.
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detect somatic mutation and predict potential tumor-specific mutated antigens.
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a novel software based on the RNNs which can predict peptide binding affinity with HLA alleles pan-specifically.
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MATTE is a python package aiming to analyze transcriptome from samples with different phenotypes in a module view.
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DeepCIP is a Deep learning method for CircRNA IRES Prediction.
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the database about Tumor-Specific NeoAntigens.
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a web browser about predicted driver sites and corresponding driver genes with statistical parameters.
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predict all the potential B/T cell epitopes for 2019-nCoV, RaTG13-CoV, SARS-CoV and MERS-CoV.
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DeepTAP is a novel RNN-based, using BiGRU, developed for the accurate prediction of TAP-binding peptides.
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An ultra fast tool for detecting Spatial dependent Expressed Genes
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OncoTriMD is an integrated database that enables streamlined and simultaneous searches for multi-scale cancer drivers.
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T-cell Receptor Interactive Database, provides landscape of experimentally verified interactive and non-interactive TCR-antigen pairs
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CovEpiAb is a curated database and analysis resource for human coronaviruses (HCoVs) immune epitopes and antibodies.
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Integrating Multi-Omics and Multi-Dimensional Gene Network for Cancer Driver Gene Identification based on Graph Attention Network Model
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