Paper Info
Title
Mathematical Modelling Of Genetic Network For Regulating The Fate Determination Of Hematopoietic Stem Cells
Abstract
Inference of genetic network is an important task to explore and predict the regulatory mechanism inside the cell. Although a number of algorithms have been designed to reverse-engineer regulatory networks effective, it is still a challenge to introduce non-linearity into mathematical models effectively. To address this issue, this work proposes a novel framework to infer genetic networks with non-linearity. A new mathematical model using exponential ordinary differential equations is introduced to realize the non-linearity. Using the hematopoietic stem cell fate determination as the test problem, this work successfully reconstructs two networks for erythroid and granulocyte differentiation respectively, each of which includes 11 genes. Numerical results suggest that our new framework is able to provide accurate realizations of the system states. This work provide new ideas to infer regulatory networks effectively and explore novel regulatory mechanisms.
Year
DOI
Venue
2018
10.1109/BIBM.2018.8621476
PROCEEDINGS 2018 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)
Keywords
Field
DocType
Hematopoiesis, Regulatory network, Gaussian graphical model, Mathematical modelling, differential equations
Haematopoiesis,Stem cell,Computer science,Inference,Granulocyte differentiation,Artificial intelligence,Hematopoietic stem cell,Mathematical model,Genetic network,Machine learning
Conference
ISSN
Citations 
PageRank 
2156-1125
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Siyuan Wu1144.99
tiangang cui2334.55
Tianhai Tian316930.29