Chao TANG
We are interested in quantitative studies of biological systems. We apply, develop and integrate theoretical, computational and experimental methods and tools to address key biological questions. We believe that interdisciplinary approaches focusing on quantitative questions at systems level will gain new insights and uncover new principles in biological systems. Our current research areas include: relationship between function and topology in biological networks; design principles in cell cycle
Luhua LAI
(1) Protein sequence and structure relationship and de novo protein design;(2) Protein interactions and biomolecular recognition mechanism, functional protein design;(3) Structural based and systems based drug design
Qi OUYANG
Biological relative nonlinear dynamics, microfluidics, pattern formation.
Shunong BAI
How an plant organ is formed from a group of undifferentiated cells, focusing on stamen;whild particular interest in the regulatory mechanism at chromatin level.
Jianguo CHEN
Cell migration and tumor metastasis; Centrosome and mitotic spindle assembly; Morphogenesis of Neuron
Minghua DENG
(1) Preprocessing of gene chip data; (2) whole-genome cis-module finding;(3) Analysis of the complex gene network with microRNA;(4) Reconstruction of gene regulatory network from high-throughput data.
Jingdong HAN
Our research focuses on the structure and dynamic inference of molecular networks，using a combination of large-scale experiments and computational analysis to probe the networks and to integrate functional interaction data in order to explore the design principles of the networks and to find how the complex phenotypes, such as aging, cancer and stem cell development are regulated through molecular networks
Ming Han
Research interests: 1. Elucidate Gene Regulatory Networks: Utilizing temporal metabolite profiles to infer complex gene regulation networks. 2. Multicellular Dynamics Modeling: Employing both theoretical and data-driven approaches to uncover intricate cell-cell interactions at the physical and chemical dimensions. 3. Early Embryonic Development: Investigating the initial developmental stages of model organisms like Drosophila melanogaster (fruit fly) and Caenorhabditis elegans to shed light on fundamental biological processes.
Yuling JIAO
Yuling Jiao’s lab combines multidisciplinary approaches to study plant development, in particular shoot lateral appendage formation and patterning. In combination with mathematical simulation...
Ying LIU
Our research focus is on protein-ligand interaction. We base on three-dimensional structure of the proteins or biologic network to design, synthesize and bioassay the potential drugs. We synthesize novel organic molecules as probes to modulate the biosystem.
Hao LI
1) Accurately reconstruct the cellular transcription networks using functional genomics and bioinformatics tools;2) Study the dynamics of gene regulatory networks quantitatively at a systems level;3) Derive principles governing the evolution of gene regulatory networks.
Fangting LI
Dynamical properties of biological regulatory networks ；The cell cycle process of both budding and fission yeast ；The genetic interaction maps of yeast cell cycle
Chunxiong LUO
The influence of culture environments to cells
Donggen LUO
My laboratory is interested in the neural mechanisms underlying animal sensation and behavior. We study: 1) the molecular mechanisms of converting physical/chemical cues into neuronal responses, 2) the principles of sensory coding and processing, and 3) the circuits of rhythmic behaviors such as circadian clock, sleep/wake, and feeding.
Yihan LIN
Quantitative single-cell biology, Systems biology, Synthetic biology
Zhiyuan LI
I am particularly fascinated by emergent behavior at various scales of life science, where interactions between individual parts give rise to interesting properties at the system level. Below are some questions I'm currently interested in and pursuing:(1)How more becomes different? -- from regulatory networks to collective cell fate decisions(2)CAN WE GET ALONG?-- Chemostat, competitive exclusion principle, and species-environment feedback(3)What Do We Learn from [NOT HAVING] History?
Jie LIN
Theoretical biological physics, gene expression, cell size control, soft matter physics, population and evolution dynamics
Youdong MAO
The main goal of my research group is to develop cryo-EM methodology, in combination with various biochemical, biophysical and computational approaches, to address fundamental mechanistic problems in biological complexity, with emphasis on the complex dynamics and energetics of significant biomolecular machineries at the atomic level. We are interested in the following topics in the interdisciplinary areas across cryo-electron microscopy (cryo-EM), molecular medicine, machine learning, and bioin
Jianfeng PEI
Molecular Docking, De Novo Drug Design, Systems-Based Drug Design, Multi-target Drug Design, Lead Optimization, Drug Design Applications.
Zhi QI
Single-molecule approaches have tremendous potential for revealing new insights into biological problems that cannot be accessed through more traditional ensemble level biochemical approaches. One of the greatest advantages of single-molecule methods is the ability to directly access information about heterogeneous reactions and transient reaction intermediates. In my lab, I will leverage these tools to begin analyzing key biological questions related to the maintenance of genome integrity and b
Long QIAN
We seek to understand biological evolution by a nonequilibrium thermodynamic approach. Specifically, we are interested in solving the evolutionary trajectories of complex biological systems including regulatory networks, linked genetic information, and in general any natural or synthetic cellular programs involving large degrees of freedom.
Chen SONG
We are interested in computational biophysics. We aim at revealing the function mechanisms of membrane proteins by using multi-scale computer simulations, in collaboration with experimental studies. Our main interests currently involve the permeation mechanism of ion channels, signaling through membrane-associated proteins, and interaction between antimicrobial peptides and lipid bilayers. Our ultimate goal is to contribute to membrane protein- or membrane-targeted drug design or optimization, a
Letian TAO
Computational neuroscience；Visual and olfactory processing；Optical imaging of neural circuitry of model organisms；Systems biology and mathematical modeling of biological systems
Chung TANG
bimolecular dynamics; data-assisted modeling of ensemble structure; biophysical chemistry; nuclear magnetic resonance.
Ping WEI
Our research interests are applying synthetic biology to rationally design and reprogram important cellular signaling networks. We will focus on developing signaling protein tools and engineer custom signaling circuits to understand how the signaling network topology correlate to specific signaling dynamics, and how the spatial, temporal and quantitative changes of signaling dynamics determine cell-fate. We want to introduce these basic network design principles to engineer human immune cells for cell and gene-based cancer immunotherapy.
Hongli WANG
Nonlinear problems in biological systems; Pattern formation
Si WU
My research areas are Computational Neuroscience and Brain-inspired Computing. I am particularly interested in understanding the general principles of neural information processing, and based on which to develop brain-inspired computing algorithms.
Xiaojing YANG
System Biology,Synthetic Biology,Cell cycle regulation,Cell decision making,
Huaiqiu ZHU
Research in the Zhu lab is currently centered at developing bioinformatics methods and tools for basic biomedicine studies. Recently methodology development includes gene finding algorithms for prokaryotes and eukaryotes, gene calling and sequence assembly in metagenomic shotgun reads. The lab also focuses on the regulatory mechanisms studies based on genome sequence and chip data analysis, comparative genomics, molecular evolution, and protein molecular dynamic simulation.
Lei ZHANG
(1) Scientific computing and numerical methods of Partial Differential Equations;(2) Computational biology;(3) Computational materials science
Zexian ZENG
Cancer immunology and immunotherapy, cell signaling, and gene expression regulation
Peijie ZHOU
AI for Biology, Computational Systems Biology, Analysis of Omics Data
