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综合介绍 General Introduction 黄裕安，博士，西北工业大学副教授，硕士生导师，2020年博士毕业于香港理工大学电子计算学系，2019年至2020年于加拿大卡尔加里大学电气与软件工程系访问学习。主要从事生物医学大数据、计算生物学、人工智能与数据挖掘等方向研究。主持国家自然科学基金青年项目1项，参与国家重点研发计划和国家自然科学基金面上项目多项。近年来，发表学术论文50余篇，其中多篇代表论文发表在Bioinformatics、Briefings in Bioinformatics、PLoS Computational Biology等领域内的知名期刊上, 谷歌引用2500次，H-index=30。受邀担任《Frontiers in Pharmacology》《Journal of Computational Biophysics and Chemistry》杂志客座编辑、《Frontiers in Bioinformatics》杂志审稿副编辑、会议BIBM2022/2023程序委员会委员，长期担任Bioinformatics、Briefings in Bioinformatics、IEEE Journal of Biomedical and Health Informatics等知名期刊和会议的审稿人。 个人相册

教育教学

教育教学 Education and teaching 教育信息 2022-2023秋，算法设计与分析实验（英语教学）U10P32003.01

荣誉获奖

学术成果 Academic Achievements [04] Du Z-H, Hu W-L, Li J-Q, Shang X-Q, You Z-H, Huang Y-A*(通讯作者): scPML: Pathway-based multi-view learning for cell type annotation from single-cell RNA-seq Data, Communications Biology, 2023.[03] Wang J, Pan G-Q, Li J-Q, Shang X-Q, You Z-H, Huang Y-A*(通讯作者): Deep-USIpred: identifying substrates of ubiquitin protein ligases E3 and deubiquitinases with pretrained protein embedding and bayesian neural network, IEEE BIBM, 2023.[02] Li Y-C, You Z-H*, Yu C-Q, Wang L, Hu L, Hu P-W, Qiao Y, Wang X-F, Huang Y-A*(通讯作者): DeepCMI: a graph-based model for accurate prediction of circRNA–miRNA interactions with multiple information, Briefings in Functional Genomics 2023, elad030.[01] Wu Y-H#, Huang Y-A#,*(共同第一作者，通讯作者), Li J-Q, You Z-H, Hu P-W, Hu L,  Leung Victor C.M., Du Z-H*: Knowledge Graph Embedding for profiling the interaction between transcription factors and their target genes, PloS Computational Biology 2023.[1] Huang Y-A, Pan G-C, Wang J, Li J-Q, Chen J, Wu Y-H: Heterogeneous graph embedding model for predicting interactions between TF and target gene, Bioinformatics 2022, 38 (9), 2554-2560 [2] Du Z-H, Wu Y-H, Huang Y-A*(通讯作者), Li J-Q*, Chen J, Pan G-C, You Z-H: GraphTGI: an attention-based graph embedding model for predicting TF-target gene interactions, Briefings in Bioinformatics 2022, 23 (3), bbac148[3] Huang Y-A, Chan KC, You Z-H: Constructing prediction models from expression profiles for large scale lncRNA–miRNA interaction profiling. Bioinformatics 2018, 34(5):812-819. [4] Huang Y-A, Hu P, Chan KC, You Z-H: Graph convolution for predicting associations between miRNA and drug resistance. Bioinformatics 2020, 36(3):851-858. [5] Huang Y-A, Chan KC, You Z-H, Hu P, Wang L, Huang Z-A: Predicting microRNA–disease associations from lncRNA–microRNA interactions via Multiview Multitask Learning. Briefings in Bioinformatics 2021, 22(3):bbaa133. [6] Chen X#, Huang Y-A#(共同第一作者), You Z-H, Yan G-Y, Wang X-S: A novel approach based on KATZ measure to predict associations of human microbiota with non-infectious diseases. Bioinformatics 2017, 33(5):733-739. [7] Li Y-C, You Z-H*, Yu C-Q, Wang L, Wong L, Hu L, Hu P-W, Huang Y-A*(通讯作者): PPAEDTI: Personalized Propagation Auto-Encoder Model For Predicting Drug-Target Interactions. IEEE Journal of Biomedical and Health Informatics 2022.[8] Hu P#, Huang Y-A#(共同第一作者), Chan KC, You Z-H: Learning multimodal networks from heterogeneous data for prediction of lncRNA–miRNA interactions. IEEE/ACM Transactions on Computational Biology and Bioinformatics 2019, 17(5):1516-1524.[9] Huang Y-A, Chen X, You Z-H, Huang D-S, Chan KC: ILNCSIM: improved lncRNA functional similarity calculation model. Oncotarget 2016, 7(18):25902. [10] Huang Y-A, Huang Z-A, You Z-H, Zhu Z, Huang W-Z, Guo J-X, Yu C-Q: Predicting lncRNA-miRNA interaction via graph convolution auto-encoder. Frontiers in Genetics 2019:758. [11] Huang Y-A, You Z-H, Li X, Chen X, Hu P, Li S, Luo X: Construction of reliable protein–protein interaction networks using weighted sparse representation based classifier with pseudo substitution matrix representation features. Neurocomputing 2016, 218:131-138. [12] Huang Y-A, You Z-H, Chen X: A systematic prediction of drug-target interactions using molecular fingerprints and protein sequences. Current Protein and Peptide Science 2018, 19(5):468-478. [13] Huang Y-A, You Z-H, Chen X, Chan K, Luo X: Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding. BMC Bioinformatics 2016, 17(1):1-11. [14] Hu P#, Huang Y-A#(共同第一作者), Mei J, Leung H, Chen Z-h, Kuang Z-m, You Z-h, Hu L: Learning from low-rank multimodal representations for predicting disease-drug associations. BMC Medical Informatics and Decision Making 2021, 21(1):1-13. [15] Huang Y-A, You Z-H, Chen X, Yan G-Y: Improved protein-protein interactions prediction via weighted sparse representation model combining continuous wavelet descriptor and PseAA composition. BMC Systems Biology 2016, 10(4):485-494. [16] Huang Y-A, Huang Z-A, Li J-Q, You Z-H, Wang L, Yi H-C, Yu C-Q: GBDR: A Bayesian Model for Precise Prediction of Pathogenic Microorganisms using 16S rRNA Gene Sequences. BMC Genomics 22, 916 (2021).  [17] Huang Y-A, You Z-H, Li L-P, Huang Z-A, Xiang L-X, Li X-F, Lv L-T: EPMDA: an expression-profile based computational model for microRNA-disease association prediction. Oncotarget 2017, 8(50):87033.[18] Huang Y-A, You Z-H, Gao X, Wong L, Wang L: Using weighted sparse representation model combined with discrete cosine transformation to predict protein-protein interactions from protein sequence. BioMed Research International 2015, 2015. [19] Huang Y-A, You Z-H, Chen X, Huang Z-A, Zhang S, Yan G-Y: Prediction of microbe–disease association from the integration of neighbor and graph with collaborative recommendation model. Journal of Translational Medicine 2017, 15(1):1-11.[20] Wang T, Li L, Huang Y-A(通讯作者), Zhang H, Ma Y, Zhou X: Prediction of protein-protein interactions from amino acid sequences based on continuous and discrete wavelet transform features. Molecules 2018, 23(4):823.[21] Jiang H-J, You Z-H*, Huang Y-A*(通讯作者): Predicting drug-disease associations via sigmoid kernel-based convolutional neural networks. Journal of Translational Medicine 2019, 17(1):1-11. [22] Jiang H-J, Huang Y-A*(通讯作者), You Z-H*: Predicting drug-disease associations via using gaussian interaction profile and kernel-based autoencoder. BioMed Research International 2019, 2019.[23] Sun Y, Zhu Z, You Z-H, Zeng Z, Huang Z-A*, Huang Y-A*(通讯作者): FMSM: a novel computational model for predicting potential miRNA biomarkers for various human diseases. BMC Systems Biology 2018, 12(9):57-68. [24] Li Y, Huang Y-A*(通讯作者), You Z-H*, Li L-P, Wang Z: Drug-target interaction prediction based on drug fingerprint information and protein sequence. Molecules 2019, 24(16):2999.[25] Wong L, Huang Y-A*(通讯作者), You ZH*, Chen ZH, Cao MY: LNRLMI: Linear neighbour representation for predicting lncRNA‐miRNA interactions. Journal of Cellular and Molecular Medicine 2020, 24(1):79-87. [26] Zheng K, You Z-H, Li J-Q, Wang L, Guo Z-H, Huang Y-A: iCDA-CGR: Identification of circRNA-disease associations based on Chaos Game Representation. PLoS Computational Biology 2020, 16(5):e1007872.[27] You Z-H, Huang W-Z, Zhang S, Huang Y-A, Yu C-Q, Li L-P: An efficient ensemble learning approach for predicting protein-protein interactions by integrating protein primary sequence and evolutionary information. IEEE/ACM transactions on computational biology and bioinformatics 2018, 16(3):809-817.[28] Wang L, You Z-H, Li Y-M, Zheng K, Huang Y-A: GCNCDA: a new method for predicting circRNA-disease associations based on graph convolutional network algorithm. PLOS Computational Biology 2020, 16(5):e1007568.[29] Wang L, You Z-H, Li J-Q, Huang Y-A: IMS-CDA: prediction of CircRNA-disease associations from the integration of multisource similarity information with deep stacked autoencoder model. IEEE Transactions on Cybernetics 2020, 51(11):5522-5531.[30] Wang L, You Z-H, Huang Y-A, Huang D-S, Chan KC: An efficient approach based on multi-sources information to predict circRNA–disease associations using deep convolutional neural network. Bioinformatics 2020, 36(13):4038-4046.

科学研究

学术成果

综合介绍