Research:
The interests of our lab are within (i) bioinformatics and computational biology relating to genomics, epigenetics,
and network biology, and (ii) data science relating to machine learning, optimization and
statistical models and algorithms.
As to (i), we focus on developing computational methods for analyzing large-scale biological data
sets and discovering novel biological patterns. We also apply computational methods to
genomic and epigenomic data to answer specific questions about gene regulation.
As to (ii), we focus on developing powerful low-rank models and algorithms for resolving big data.
Particularly, we have strong interests in developing joint low-rank models for multi-view or multi-modal
data. We also curious about the underlying relationship between deep learning and low-rank models.
More specifically, our research interests include:
Optimization, statistics and machine learning for data science
Our group has a general interest in developing optimization, statistics and machine learning
models and algorithms for those computational problems
that arise from the biological data (e.g., single-cell transcriptomic data, 3D chromatin structure)
and generic data science (e.g., multi-view data, image data, complex networks).
We are particularly interested in computational and statistical methods
for data representation and pattern discovery in diverse big data.
Cancer genomics
The first step for clinical diagnostics, prognostics,
and targeted therapeutics of cancer is to comprehensively
understand its molecular mechanisms.
Large-scale cancer genomics projects are providing a large
volume of data about genomic, epigenomic, and gene expression
aberrations in multiple cancer types. We aim to combine data
from different sources with computational techniques to discover
the underlying combinatorial patterns and driver pathways underlying
cancer as well as other diseases. We also aim to develop methods
to integrate different data sources to classify tumor and predict
the clinical outcome of patients based on the genotype and molecular features.
Computational epigenetics
Chromatin modifications have been comprehensively
illustrated to play important roles in gene regulation
and cell diversity in recent years. Given the rapid
accumulation of genome-wide chromatin modification
maps across multiple cell types, there is an urgent
need for computational methods to analyze multiple
maps to reveal combinatorial modification patterns
and define functional DNA elements. We aim to
develop computational methods to address these
issues and answer specific biological questions.
Network biology and network science
Network science emerged as powerful tools for
studying biological systems and complex
diseases which summarizes biological systems
as nodes and edges among them. The tasks
of uncovering the organization of networks
and utilizing them for the understanding
of biology and disease complexity prompt
rich and diverse interests. We aim to
develop methods to understand the topological
organization of networks and reveal molecular
characteristics by combing network structure
and biological features.
Lab News
May 19-20, 2018
The 6th "Youth Scholar Forum on Interdisciplinary Research of Mathematics, Computer Science and Biological Science" has been held successfully!Here
The 6th "Youth Scholar Forum on Interdisciplinary Research of Mathematics, Computer Science and Biological Science" has been held successfully!Here
May 8, 2018
Papers on NetNMF and ESPCA have been accepted by Nucleic Acids Research and Bioinformatics, respectively. Congratulations, Jinyu and Wenwen!
Papers on NetNMF and ESPCA have been accepted by Nucleic Acids Research and Bioinformatics, respectively. Congratulations, Jinyu and Wenwen!
April 5, 2018
Dr. Zhang was promoted to a Full Professor.
Dr. Zhang was promoted to a Full Professor.
Feb 24, 2018
Dr. Zhang was awarded the Ten Thousand Talent Program for Young Top-notch Talent.
Dr. Zhang was awarded the Ten Thousand Talent Program for Young Top-notch Talent.
Dec 15, 2017
Paper on "Large-scale determination and characterization of cell type-specific regulatory elements in the human genome" has appeared in Journal of Molecular Cell Biology as an Editor's Choice and Cover Story article. Congratulations, Can!
Paper on "Large-scale determination and characterization of cell type-specific regulatory elements in the human genome" has appeared in Journal of Molecular Cell Biology as an Editor's Choice and Cover Story article. Congratulations, Can!
