教師基本信息
職稱:講師
職務:青年副研究員
電子郵箱:wangyi_fudan@fudan.edu.cn
辦公地點:生科大樓B603
辦公電話:13764841280
個人網頁/課題組主頁:www.drwang.top
個人簡介
2000.9-2004.7: 複旦大學生命科學學院,學士
2004.9-2009.12:複旦大學現代人類學教育部重點實驗室,遺傳學博士
2010.4-2011.8: 美國貝勒醫學院人類基因組測序中心,博士後
2012.8-2016.7: 複旦大學現代人類學教育部重點實驗室,助理研究院
2016.8-今: 複旦大學生命科學學院,青年副研究員
研究方向
醫學遺傳學、生物信息、醫學人工智能
授課情況
《生命科學中的機器學習》
招生專業
生命科學、計算機科學、醫學
代表性論文和論著
Xiaojian Liu, Yuanyuan Yang, Yan Qiu, Md. Reyad-ul-ferdous, Qiurong Ding*, Yi Wang* (2020) SeqCor: correct the effect of gRNA sequences in CRISPR/Cas9 screenings by machine learning algorithm. Journal of Genetics and Genomics. (即將出版)
Yi Li, Meng Liang, Xianhong Yin, Xiaoyu Liu, Meng Hao, Zixin Hu, Yi Wang*, Li Jin* (2020) COVID-19 epidemic outside China: 34 founders and exponential growth. J Investig Med. 2020 Oct 6;jim-2020-001491. doi: 10.1136/jim-2020-001491
Wang Y#, Li Y#, Hao M#, Liu X#, Zhang M, Wang J, Xiong M, Shugart YY, Jin L. (2019) Robust Reference Powered Association Test of Genome-Wide Association Studies. Front Genet. 2019 Apr 9;10:319. doi: 10.3389/fgene.2019.00319. eCollection 2019.
Wang Y#, Li Y#, Qiao C#, Liu X#, Hao M#, Shugart YY, Xiong M, Jin L. (2018) Nuclear Norm Clustering: a promising alternative method for clustering tasks. Sci Rep. 2018 Jul 18;8(1):10873.
Sun R#,Wang Y#, Jin M#, Chen L, Cao Y, Chen F. (2018) Identification and Functional Studies of MYO1H for Mandibular Prognathism. J Dent Res. 2018 Jul 1:22034518784936.
Li Z#,Wang Y#, Wang F, (2018) A study on fast calling variants from next-generation sequencing data using decision tree. BMC Bioinformatics. 2018 Apr 19;19(1):145
Zhou W#,Wang Y#, Fujino M, Shi L, Jin L, Li XK, Wang J.(2018) A standardized fold change method for microarray differential expression analysis used to reveal genes involved in acute rejection in murine allograft models. FEBS Open Bio. 2018 Jan 25;8(3):481-490
Wang Y#, Li Y#, Liu X#, Pu W, Wang X, Wang J, Xiong M, Yao Shugart Y, Jin L.(2017) Bagging Nearest-Neighbor Prediction independence Test: an efficient method for nonlinear dependence of two continuous variables. Sci Rep 2017 Oct 06;7(1).
Pan X#, Wang Y#, Wong EHM, Telenti A, Venter JC, Jin L.(2017).Fine population structure analysis method for genomes of many. Sci Rep 2017 Oct 03;7(1).
Li L#,Wang Y#, Yang S, Xia M, Yang Y, Wang J, Lu D, Pan X, Ma T, Jiang P, Yu G, Zhao Z, Ping Y, Zhou H, Zhao X, Sun H, Liu B, Jia D, Li C, Hu R, Lu H, Liu X, Chen W, Mi Q, Xue F, Su Y, Jin L, Li S.(2017). Genome-wide screening for highly discriminative SNPs for personal identification and their assessment in world populations. Forensic Sci Int Genet. 2017 May;28:118-127.
Chen Y#, Zhao L#,Wang Y#, Cao M, Gelowani V, Xu M, Agrawal SA, Li Y, Daiger SP, Gibbs R, Wang F, Chen R(2017). SeqCNV: a novel method for identification of copy number variations in targeted next-generation sequencing data. BMC Bioinformatics. 2017 Mar 3;18(1):147.
Liu S#,Wang Y#, Wang F(2016). A fast read alignment method based on seed-and-vote for next generation sequencing. BMC Bioinformatics. 2016 Dec 23;17(Suppl 17):466.
Wang Y#, Li Y#, Pu W, Wen K, Shugart YY, Xiong M, Jin L (2016). Random Bits Forest: a Strong Classifier/Regressor for Big Data. Sci Rep. 2016 Jul 22;6:30086.
Yi Wang#, Yi Li#, Momiao Xiong, Yin Yao Shugart, Li Jin (2016), Random Bits Regression: a Strong General Predictor for Big Data. Big Data Analytics 20161:12
Wang, Y#., Y. Li#, H. Cao, M. Xiong, Y. Y. Shugart and L. Jin (2015). "Efficient test for nonlinear dependence of two continuous variables." BMC Bioinformatics 16(1): 260.
Wang Y#, Lu J#, Yu J, Gibbs RA, Yu F (2013) An integrative variant analysis pipeline for accurate genotype/haplotype inference in population NGS data. Genome Res 23:833-842
Abecasis, G. R., A. Auton, L. D. Brooks, M. A. DePristo, R. M. Durbin, R. E. Handsaker, H. M. Kang, G. T. Marth and G. A. McVean (2012). "An integrated map of genetic variation from 1,092 human genomes." Nature 491(7422): 56-65. (5.2 Low coverage SNP calling: Baylor College of Medicine HGSC, section一作)
Ling ZQ#,Wang Y#, Mukaisho K, Hattori T, Tatsuta T, Ge MH, Jin L, Mao WM, Sugihara H (2010) Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences. Bioinformatics 26:1431-1436