Abstract : The concept of dynamical network biomarker (DNB) was proposed to provide early-warning signals of diseases on the basis of co-dimension 1 local bifurcation in 2012, and then is widely used in various topics and fields of biology and medicine, e.g. dynamical analyses of biological processes in biology and disease prediction/early-diagnoses in medicine. The DNB is a novel type of biomarkers to identify the critical state during disease progression, which quantifies biological systems from a dynamical and network viewpoint, thus providing reliable information on early-warning signals before onset of complex diseases. Many DNB methods as well as applications have been developed. The DNB theory with big biological data is expected to lead to ultra-early precision and preventive medicine. This symposium addresses but not limited to the recent development of theory, methodology and application of DNB in a variety of scientific areas.
Xiaoping Liu (Hangzhou Institute for Advanced Study, UCAS)
Naoki Masuda (State University of New York at Buffalo)
Chengming Zhang (The University of Tokyo)
Jun-ichi Imura (Tokyo Institute of Technology)
Wei Lin (Fudan University)
Huanfei Ma (Soochow University)
Luonan Chen (Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences)
Talks in Minisymposium :
[03348] Modelling single cell multi-omics data
Author(s) :
Yong Wang (Academy of Mathematics and Systems Science, Chinese Academy of Sciences)
Abstract : In this talk I will introduce combinatorial regulon (cRegulon) to model the combinations among TFs, which can better characterize cell types and serves as the driving forces for cell state transitions. By leveraging rapidly accumulated single multi-omics data, we develop an optimization model to systematically infer cRegulons (i.e., the representative TF modules, their associated regulatory elements and target genes formed regulatory network).
