The main focus in Dr. Victor Jin's lab is on two aspects:
1) Computational Biology: to apply machine learning algorithms and statistical methods to decipher the transcriptional regulatory codes in eukaryotic genomes. By working closely with bench-scientists, specifically, they will a) identify functional elements in mammalian genomes using the ChIP-seq, MBD-seq, Hi-C and RNA-seq technologies; b) construct transcriptional regulatory networks from gene expression, protein-DNA interaction and protein-protein interaction data; and c) understand genetic/epigenetic regulatory mechanisms in cancers and cancer stem cells. Our investigation will not only fundamentally contribute to the understanding of genome/chromatin organization as well as gene/epigenetic regulation mechanisms, but also provide new approaches to the treatment of cancers.
2) Translational Bioinformatics: to develop computational pipelines to aid molecular biomarker discovery. They will utilize existing software tools developed in the lab and other labs for processing various disease related ‘omics data such as ChIP-seq, RNA-seq, miRNA-seq, Hi-C and MBD-seq and integrate them into an interactive and integrated platform. The predicted genes (loci) are further correlated with disease related gene signatures and performed for experimental validations in patient samples. One of the major applications will be cancers such as breast cancer, prostate cancer and lung cancer.
Cui R, Meng W, Sun HL, Kim T, Ye Z, Fassan M, Jeon YJ, Li B, Vicentini C, Peng Y, Lee TJ, Luo Z, Liu L, Xu D, Tili E, Jin V.X., Middleton J, Chakravarti A, Lautenschlaeger T, Croce CM. MicroRNA-224 promotes tumor progression in nonsmall cell lung cancer. Proc Natl Acad Sci U S A. 2015 Jul 17. pii: 201502068. [Epub ahead of print]
Ruan J, Jin V.X., Huang Y, Xu H, Edwards JS, Chen Y, Zhao Z. Education, collaboration, and innovation: intelligent biology and medicine in the era of big data. BMC Genomics. 2015;16 Suppl 7:S1.
He H, Li W, Liyanarachchi S, Srinivas M, Wang Y, Akagi K, Wang Y, Wu D, Wang Q, Jin V.X., Symer DE, Shen R, Phay J, Nagy R, de la Chapelle A. Multiple functional variants in long-range enhancer elements contribute to the risk of SNP rs965513 in thyroid cancer. Proc Natl Acad Sci U S A. 2015 May 12;112(19):6128-33.
Wang J, Ye Z, Huang TH, Shi H, Jin V.X.. A survey of computational methods in transcriptome-wide alternative splicing analysis. Biomol Concepts. 2015 Mar;6(1):59-66.
Jadhav RR, Ye Z, Huang RL, Liu J, Hsu PY, Huang YW, Rangel LB, Lai HC, Roa JC, Kirma NB, Huang TH, Jin V.X.. Genome-wide DNA methylation analysis reveals estrogen-mediated epigenetic repression of metallothionein-1 gene cluster in breast cancer.Clin Epigenetics. 2015 Feb 24;7(1):13.
Chen Z, Lan X, Thomas-Ahner JM, Wu D, Liu X, Ye Z, Wang L, Sunkel B, Grenade C, Chen J, Zynger DL, Yan PS, Huang J, Nephew KP, Huang TH, Lin S, Clinton SK, Li W, Jin V.X., Wang Q. Agonist and antagonist switch DNA motifs recognized by human androgen receptor in prostate cancer. EMBO J. 2015 Feb 12;34(4):502-16
Wu D, Sunkel B, Chen Z, Liu X, Ye Z, Li Q, Grenade C, Ke J, Zhang C, Chen H, Nephew KP, Huang TH, Liu Z,Jin V.X., Wang Q. Three-tiered role of the pioneer factor GATA2 in promoting androgen-dependent gene expression in prostate cancer. Nucleic Acids Res. 2014 Apr;42(6):3607-22.
Ye Z, Chen Z, Lan X, Hara S, Sunkel B, Huang TH, Elnitski L, Wang Q, Jin V.X.. Computational analysis reveals a correlation of exon-skipping events with splicing, transcription and epigenetic factors. Nucleic Acids Res. 2014 Mar;42(5):2856-69.
Bonneville, R. and Jin, V.X.* “A Hidden Markov Model to Identify Combinatorial Epigenetic Regulation Patterns for Estrogen Receptor α Target Genes.” Bioinformatics, 29, 22-28 (2013).
Wang, J.#,*, Lan, X.#, Hsu, P.-Y., Huang, K., Parvin, J., Huang, T.H.-M., and Jin, V.X.* “Genome-wide analysis uncovers high frequency and strong differential chromosomal interactions and their associated epigenetic patterns in E2-mediated gene regulation.” BMC Genomics, 14:70 (2013).