Wen Jia

Wen Jia

Bioinformatics
704-687-5014
Bioinformatics 302B

Degree Institution: Nanjing Agricultural University
Degree: Ph. D – Statistical Genomics 2014

Dr. Wen earned a B.S. in Statistics and her Ph.D in Statistical Genomics from Nanjing Agricultural University. During her Ph.D research, she is interested in the biostatistics and statistical genomics. Within this framework, her major research focuses on three areas: detection of epistasis for complex traits, GWAS and gene expression data analysis. After she got the Ph.D degree, she joined Dr Shi’s lab as a Postdoctoral fellow on March 2015. She is now interested in developing new methods on the epistasis analysis using the real large human genetic data, exploring the function genomic analysis (ASE analysis et al.) and eQTL analysis in biomedical research and big data health.

Publications:

  1. Wen J, Quitadamo A, Hall B, and Shi X. An Empirical Bayesian Elastic Nets Method for Epistasis Analysis of microRNAs on Pathological Stages in Colon Cancer. BMC Genomics. 2016, In submission.
  2. Wang Y, Wen J, Wu X, and Shi X. Infringement of Individual Privacy via Mining Differentially Private GWAS Statistics. In Proceedings of the 2nd International Conference on Big Data Computing and Communication (BIGCOM 2016), July 29-31, 2016, Shenyang, Liaoning, China, Springer Lecture Notes in Computer Science.
  3. Wen J, Quitadamo A, Hall B, and Shi X. Epistasis Analysis of microRNAs in Colon Cancer Using Empirical Bayesian Elastic Nets. In Proceedings of The 12th International Symposium on Bioinformatics Research and Applications (ISBRA2016, Track 2 paper and oral presentation), Minsky, Belaruse, June 6-8, 2016 (invited journal submission to BMC Genomics).
  4. Wen J, Quitadamo A, Hall B, and Shi X. Apply Empirical Bayesian Elastic Net Method to microRNA Epistasis Analysis in Colon Cancer. The Biology of Genomes Meeting, Cold Spring Harbor, NY, May 10 – 14, 2016 (poster).
  5. Wen J, Quitadamo A, and Shi X. Allele Specific Expression Analysis of Structural Variation in Human Populations. The Biology of Genomes Meeting, Cold Spring Harbor, NY, May 10 – 14, 2016 (poster).
  6. He A, Hall B, Wen J, Liang Y, and Shi X. Sequential and Parallel LASSO: Novel Scalable Methods for eQTL Mapping. In Proceedings of the 8th International Conference on Bioinformatics and Computational Biology (BICoB, oral presentation), Pages 533-534, April 4-6, 2016 Las Vegas, Nevada, USA. (seqParLASSO: code, GitHub).
  7. He A, Hall B, Wen J, Liang Y, and Shi X. Sequential Parallel LASSO Models for eQTL Analysis. In Proceedings of The 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB 2015), Atlanta, GA, September 9-12, 2015 (poster).
  8. Zhou L, Luo L, Zuo JF, Yang L, Zhang L, Guang X, Niu Y, Jian J, Geng QC, Liang L, Song Q, Dunwell JM, Wu Z, Wen J, Liu YQ, Zhang YM. Identification and Validation of Candidate Genes Associated with Domesticated and Improved Traits in Soybean. The Plant Genome. 2016, Apr 1.
  9. Wen J, Zhao X, Wu GR, Dan X, Liu Q, Bu SH, Yi C, Song Q, Dunwell JM, Tu JX and Zhang TZ, Zhang YM. Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design. Scientific reports, 2015, 5.
  10. Bu SH, Zhao XW, Yi C, Wen J, Tu JX and Zhang YM. Interacted QTL Mapping in Partial NCII Design Provides Evidences for Breeding by Design. PloS ONE, 2015, 10(3), p. e0121034.
  11. Zhou L, Wang SB, Jian J, Geng QC, Wen J, Song Q, Wu Z, Li GJ, Liu YQ, Dunwell JM, Zhang J, Feng JY, Niu , Zhang L, Ren WL, Zhang YM. Identification of domestication-related loci associated with flowering time and seed size in soybean with the RAD-seq genotyping method. Scientific reports, 2015, 5, p.9350.
  12. Xie SQ, Wen J and Zhang YM. Multi-QTL mapping for quantitative traits using epistatic distorted markers. PloS ONE, 2013, 8(7), p.e68510.
  13. Wen J and Zhang YM. Multi-QTL mapping for quantitative traits using distorted markers. Molecular breeding, 2013, 31(2), pp.395-404.
  14. Liu GF, Li M, Wen J, Du Y and Zhang YM. Functional mapping of quantitative trait loci associated with rice tillering. Molecular Genetics and Genomics, 2010, 284(4), pp.263-271.

Research Areas: