Hi. This is Xin from the Department of Biomedical Informatics (DBMI) of Harvard Medical School. I recently joined Peter Kharchenko lab for a Consortium effort project and spatial deep learning project with single-cell analysis. Before coming to Boston, I spent two years at Northwestern University Chicago campus. My previous postdoctoral research focused on the mechanism of gene regulations via single-cell analysis of cancers and machine/deep learning.

I received my Ph.D. in Bioinformatics and Computational Biology at the University of New South Wales in Sydney, NSW, Australia under Joshua Ho in 2018. My Ph.D. research focused on developing machine learning models for the grammar of transcriptional regulation and chromatin state study.

Before coming to UNSW, I got my Bachelor’s degree at Sun Yat-sen University in Guangzhou, China in 2009. I also got my Master of Research degree in 2013 under Dr. Zhongsheng Sun who is a PI in the Beijing Institutes of Biological Science, Chinese Academy of Science(CAS). After master graduation, I was in Biocant Institute (@Portugal) for one year as a Bioinformatician.

Contact: xin.leo.wang@outlook.com

Predict the functional impact of genetic variants via ultra-deep neural networks such as Resnet

Predict the functional impact of non-coding genetic variants is crucial for related diseases' diagnosis and clinical applications. Based on the sate-of-the-art ResNet (Residual neural network paper), a recent published work "SpliceAI" shows unbelievable accuracy on predicting variants caused splicing. I'm quite familiar with SpliceAI as established and re-ran it on our current GPU workstation. It would be a good combination for Resnet structure and other mutation effect predictions such as polyadenylation (manuscript in preparation) or other diseases mutation study with/without the related CRISPR/cas9 cell-line screening data.

Single-cell RNA-seq analysis on diseases (e.g. cancers)

Single-cell RNA-seq technology now becomes more and more popular and useful in disease studies as well as related immunotherapy studies. I have the experience on analyzing single-cell RNA-seq data generated from both SMART-seq2 protocol (our chemoresistance index project with Vadim Backman lab) and 10X Genomics protocol (a preliminary exploration analysis collaborated with Kevin Struhl lab). My single-cell RNA-seq analysis on the SMART-seq2 data revealed interesting biology in chemoresistance (manuscript in preparation).

Discovery of cell-type specific DNA motif grammar in cis-regulatory elements

I developed a Random Forest (RF) based approach to build a multi-class classifier to predict the cell-type specificity of a TF binding site given its motif content. I applied this RF classifier to two published ChIP-seq datasets of TF (TCF7L2 and MAX) across multiple cell types. Using cross-validation, I show that motif combinations alone are indeed predictive of cell types. I also present a rule mining approach to extract the most discriminatory rules in the RF classifier, thus allowing us to discover the underlying cell-type specific motif grammar.

(* indicate co-first authors):

Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using random Forest
​Xin Wang, Peijie Lin, Joshua W. K. Ho
BMC Genomics, 2018

Biologically active constituents of the secretome of human W8B2+ cardiac stem cells
​Shuai Nie*, Xin Wang* , Priyadharshini Sivakumaran*, ...,Joshua W. K. Ho, Nicholas Williamson, Shiang Y. Lim
Scientific Reports, 2018

PBrowse: a web-based platform for real-time collaborative exploration of genomic data
​Peter S. Szot, Andrian Yang, Xin Wang, Chirag Parsania, Uwe Röhm, Koon Ho Wong, Joshua W. K. Ho,
Nucleic Acids Research, 2017

Epigenomic analysis of chromatin organization and DNA methylation (Book Chapter)
​Xin Wang, Helen M. McCormick, Djordje Djordjevic, Eleni Giannoulatou, Catherine M. Suter, Joshua WK Ho
Computational Biology and Bioinformatics: Gene Regulation, CRC Press, 2016

Ras-induced epigenetic inactivation of the RRAD (Ras-related associated with diabetes) gene promotes glucose uptake in a human ovarian cancer model
(The bioinformatics analysis part of this paper are also mostly in my Master Thesis)
​Yan Wang, Guiling Li, Fengbiao Mao, Xianfeng Li, Qi Liu, Lin Chen, Lu Lv, Xin Wang, Jinyu Wu, Wei Dai, Guan Wang, Enfeng Zhao, Kai-Fu Tang and Zhong Sheng Sun
The Journal of Biological Chemistry, 2014

mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing
​Jinyu Wu, Qi Liu, Xin Wang, Jiayong Zheng, Tao Wang, Mingcong You, Zhong Sheng Sun and Qinghua Shi
RNA Biology, 2013

Exome-assistant: A rapid and easy detection of disease-related genes and genetic variations from exome sequencing
​Qi Liu, Enjian Shen, Qingjie Min, Xueying Li, Xin Wang, Xianfeng Li, Zhong Sheng Sun & Jinyu Wu
BMC Genomics, 2012

Submitted paper

Antibody targeting tumor-derived soluble NKG2D ligand sMIC reprograms NK cell function and enhances melanoma response to PD1 blockade therapy
​Fahmin Basher, Xin Wang, Payal Dhar, Zhe Ji, Jennifer Wu
Submitted to Journal for ImmunoTherapy of Cancer

Software

POMP: a-Powerful-Motif-discovery-Pipeline (from my 2018 Random Forest paper)
​Xin Wang, Joe Godbehere

Posters

Single-cell RNA-seq reveals transcriptional heterogeneities in oxidative stress response and metabolic processes mediating chemoresistance
​Xin Wang, Vadim Backman, Zhe Ji
Symposium on Physical Genomics, 2019

Comprehensive analysis of chromatin landscape in filamentous fungus Aspergillus nidulans
​Xin Wang, Djordje Djordjevic, Zhengqiang Miao, Chirag Parsania, Kaeling Tan, Joshua W. K. Ho, Koon Ho Wong
Intelligent Systems for Molecular Biology (ISMB), 2016

Talks

Single-Cell RNA-Seq Reveals Transcriptional Heterogeneities Mediating Chemoresistance
Department of Pharmacology annual retreat, Northwestern University (May 2nd, 2019)

Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using Random Forest
International Conference on Bioinformatics (InCoB) 2017

Comprehensive analysis of chromatin landscape in filamentous fungus Aspergillus nidulans
Oral presentation at Student Council Symposium of ISMB 2016

Honors/Awards

Tuition Fee Scholarship (TFS) plus a Research Stipend (2014 - 2018)

The Postgraduate Research Student Support (PRSS) Conference Travel Funds (2016)

International Conference on Bioinformatics (InCoB) Travel Fellowship (2017)

Nomination for the Higher Degree Research Thesis Award of UNSW (2018)





Last update: March 6, 2020