Bin LIU
The Chair Professor in the Faculty of Engineering at SMBU
The head of the Group of Computer Science and Engineering
The director of the Lab of Bioinformatics and Biological Big Data
劉濱
工程系首席教授
計算機(jī)科學(xué)與工程團(tuán)隊負(fù)責(zé)人
生物信息學(xué)與生物大數(shù)據(jù)分析實驗室主任
He received the bachelor’s, master’s degrees from the Harbin Engineering University in 2004 and 2007 respectively. He received the PhD degree from the Harbin Institute of Technology in 2010 and has been awarded the National Outstanding Young Scholar (2023), the National Excellent Young Scholar (2018), the Guangdong Outstanding Young Scholar (2016), the Beijing Outstanding Young Scholar (2019), and the CCF Outstanding Member. He has published more than 130 SCI papers in top-tier journals such as Bioinformatics, Nucleic Acids Research, PLoS Computational Biology, and BMC Biology, many of which have been selected as China's 100 Most Influential International Academic Papers. He serves as the deputy director of the Biomedical Data Mining and Computational Professional Group of the Bioinformatics Society, member of the Bioinformatics Special Interest Group (SIG) of China Computer Federation (CCF), member of the Professional Committee of Bioinformatics and Artificial Life of the China Association for Artificial Intelligence, the first member of the Professional Committee of Intelligent Health and Bioinformatics of the Chinese Association of Automation (CAA), and the executive director of the Computational Systems Biology Branch of the Operational Research Society of China (ORSC). He has won the Ho Ying-Tong Young Teachers Fund of Ministry of Education, the Shenzhen Youth Science and Technology Award, and the Second Prize of the Ministry of Education's Natural Science Award (first contributor).
Research interests: Big Data, Natural Language Processing and applications in the analysis of Life and Health Big Data
2004、2007年分別獲得哈爾濱工程大學(xué)學(xué)士和碩士學(xué)位。2010年在哈爾濱工業(yè)大學(xué)獲得博士學(xué)位、曾獲國家杰青（2023）、國家優(yōu)青（2018）、廣東省杰青（2016）、北京市杰青（2019）、CCF杰出會員。在Bioinformatics、Nucleic Acids Research、PLoS Computational Biology、BMC Biology等權(quán)威期刊發(fā)表SCI論文130余篇，其中多篇論文入選中國百篇最具影響國際學(xué)術(shù)論文，擔(dān)任生物信息學(xué)學(xué)會生物醫(yī)學(xué)數(shù)據(jù)挖掘與計算專業(yè)組副主任、中國計算機(jī)學(xué)會生物信息學(xué)專委會委員、中國人工智能學(xué)會生物信息學(xué)與人工生命專委會委員、中國自動化學(xué)會智能健康與生物信息專委會首屆委員、中國運籌學(xué)會計算系統(tǒng)生物學(xué)分會常務(wù)理事，曾獲教育部霍英東青年教師基金、深圳市青年科技獎、教育部自然科學(xué)二等獎（第一完成人）等。
研究方向：主要從事大數(shù)據(jù)、自然語言處理、及其在生命健康大數(shù)據(jù)分析的應(yīng)用研究。
Selected Papers
1. Ke Yan; Hongwu Lv; Yichen Guo; Wei Peng; Bin Liu*; sAMPpred-GAT: prediction of antimicrobial peptide by graph attention network and predicted peptide structure, Bioinformatics, 2023, 39(1): btac715
2. Yi-Jun Tang, Ke Yan, Xingyi Zhang, Ye Tian, Bin Liu*. Protein intrinsically disordered region prediction by combining Neural Architecture Search and Multi-objective genetic algorithm. BMC Biology 2023; DOI: 10.1186/s12915-023-01672-5
3. Ke Yan; Hongwu Lv; Yichen Guo; Yongyong Chen; Hao Wu; Bin Liu*; TPpred-ATMV: therapeutic peptide prediction by adaptive multi-view tensor learning model, Bioinformatics, 2022, 38(10): 2712-2718
4. Yihe Pang; Bin Liu*; DMFpred: Predicting protein disorder molecular functions based on protein cubic language model, PLOS Computational Biology, 2022, 18(10): e1010668
5. Jun Zhang; Ke Yan; Qingcai Chen; Bin Liu*; PreRBP-TL: prediction of species-specific RNAbinding proteins based on transfer learning, Bioinformatics, 2022, 38(8): 2135-2143
6. Wenxiang Zhang; Bin Liu*; iSnoDi-LSGT: identifying snoRNA-disease associations based on local similarity constraints and global topological constraints, RNA, 2022, 28(12): 1558-1567
7. Hong-Liang Li; Yi-He Pang; Bin Liu*; BioSeq-BLM: a platform for analyzing DNA, RNA and protein sequences based on biological language models, Nucleic Acids Research, 2021, 49(22):e129
8. Xiaopeng Jin; Qing Liao; Bin Liu*; S2L-PSIBLAST: a supervised two-layer search framework based on PSI-BLAST for protein remote homology detection, Bioinformatics, 2021, 37(23): 4321-4327
9. Jun Zhang; Qingcai Chen; Bin Liu*; iDRBP_MMC: Identifying DNA-Binding Proteins and RNA Binding Proteins Based on Multi-Label Learning Model and Motif-Based Convolutional Neural Network, Journal of Molecular Biology, 2020, 432(22): 5860-587
10. Bin Liu*; Xin Gao; Hanyu Zhang ; BioSeq-Analysis2.0: an updated platform for analyzing DNA, RNA and protein sequences at sequence level and residue level based on machine learning approaches, Nucleic Acids Research, 2019, 47(20): e127
