Yi Wang
wangyi_fudan@fudan.edu.cn
Chinese, English
Shanghai
Fudan University
Life Sciences
  • 2000.9-2004.7: Bachelor's Degree in Life Sciences, Fudan University
  • 2004.9-2009.12: PhD in Genetics, Key Laboratory of Contemporary Anthropology, Ministry of Education, Fudan University
  • 2010.4-2011.8: Postdoctoral Researcher, Human Genome Sequencing Center, Baylor College of Medicine
  • 2012.8-2016.7: Assistant Researcher, Key Laboratory of Contemporary Anthropology, Ministry of Education, Fudan University
  • 2016.8-Present: Young Associate Researcher, School of Life Sciences, Fudan University
Medical Genetics
Bioinformatics
Medical Artificial Intelligence
  • SeqCor: correct the effect of gRNA sequences in CRISPR/Cas9 screenings by machine learning algorithm, Xiaojian Liu, Yuanyuan Yang, Yan Qiu, Md. Reyad-ul-ferdous, Qiurong Ding, Yi Wang, 2020
  • COVID-19 epidemic outside China: 34 founders and exponential growth, Yi Li, Meng Liang, Xianhong Yin, Xiaoyu Liu, Meng Hao, Zixin Hu, Yi Wang, Li Jin, 2020
  • Robust Reference Powered Association Test of Genome-Wide Association Studies, Wang Y, Li Y, Hao M, Liu X, Zhang M, Wang J, Xiong M, Shugart YY, Jin L, 2019
  • Nuclear Norm Clustering: a promising alternative method for clustering tasks, Wang Y, Li Y, Qiao C, Liu X, Hao M, Shugart YY, Xiong M, Jin L, 2018
  • Identification and Functional Studies of MYO1H for Mandibular Prognathism, Sun R, Wang Y, Jin M, Chen L, Cao Y, Chen F, 2018
  • A study on fast calling variants from next-generation sequencing data using decision tree, Li Z, Wang Y, Wang F, 2018
  • A standardized fold change method for microarray differential expression analysis used to reveal genes involved in acute rejection in murine allograft models, Zhou W, Wang Y, Fujino M, Shi L, Jin L, Li XK, Wang J, 2018
  • Bagging Nearest-Neighbor Prediction independence Test: an efficient method for nonlinear dependence of two continuous variables, Wang Y, Li Y, Liu X, Pu W, Wang X, Wang J, Xiong M, Yao Shugart Y, Jin L, 2017
  • Fine population structure analysis method for genomes of many, Pan X, Wang Y, Wong EHM, Telenti A, Venter JC, Jin L, 2017
  • Genome-wide screening for highly discriminative SNPs for personal identification and their assessment in world populations, 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
  • SeqCNV: a novel method for identification of copy number variations in targeted next-generation sequencing data, 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
  • A fast read alignment method based on seed-and-vote for next generation sequencing, Liu S, Wang Y, Wang F, 2016
  • Random Bits Forest: a Strong Classifier/Regressor for Big Data, Wang Y, Li Y, Pu W, Wen K, Shugart YY, Xiong M, Jin L, 2016
  • Random Bits Regression: a Strong General Predictor for Big Data, Yi Wang, Yi Li, Momiao Xiong, Yin Yao Shugart, Li Jin, 2016
  • Efficient test for nonlinear dependence of two continuous variables, Wang Y, Y. Li, H. Cao, M. Xiong, Y. Y. Shugart, L. Jin, 2015
  • An integrative variant analysis pipeline for accurate genotype/haplotype inference in population NGS data, Wang Y, Lu J, Yu J, Gibbs RA, Yu F, 2013
  • An integrated map of genetic variation from 1,092 human genomes, Abecasis, G. R., A. Auton, L. D. Brooks, M. A. DePristo, R. M. Durbin, R. E. Handsaker, H. M. Kang, G. T. Marth, G. A. McVean, 2012
  • Novel statistical framework to identify differentially expressed genes allowing transcriptomic background differences, Ling ZQ, Wang Y, Mukaisho K, Hattori T, Tatsuta T, Ge MH, Jin L, Mao WM, Sugihara H, 2010
Genetics Genomics Crispr Machine Learning Artificial Intelligence Bioinformatics Medical Research Human Genome Data Analysis Computational Biology

Contact us

Let's talk!
* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.
Submit

Thank you for your message!
We will contact you soon.