Modeling and Simulation of Gene Regulatory Network Dynamics in Evolutionary Studies

Date of Presentation: 
Wednesday, January 14, 2015
Quarter: 
2015 Winter
Research Focus: 

Gene regulatory networks (GRNs) are an essential part of the biological process that determines the biological characteristics of every living organism. In the context of evolutionary biology, one of the important goals of studying GRNs is to understand how rewiring of the network (due to genetic mutations) affects the biological properties of the individuals. In this talk, we will discuss how computational modeling and simulation of GRNs can be used to gain insights to answer these biological questions. In particular, we will review how GRN dynamics are modeled and simulated in computer simulations to collect representative data for understanding GRNs. We will then discuss how computational concepts, such as the network attractor landscape, can be used to gain a deeper understanding of network characteristics relevant for the evolution of GRNs.
SPEAKER: Mushthofa
Mushthofa was born and raised in Indonesia. He has a Bachelor's degree in Computer Science from Bogor Agricultural University in Indonesia. With the Erasmus Mundus scholarship, he completed the European Master's program in Computational Logic at Universidade Nova de Lisboa, Portugal and Technische Universitt Wien, Austria, focusing on Answer Set Programming as his thesis research topic. Currently, he is working on his PhD in Computer Science at Ghent University, Belgium (since December 2013) with a primary research topic in Bioinformatics, under the supervision of Prof. Martine De Cock, Prof. Kathleen Marchal and Prof. Yves Van de Peer.Gene regulatory networks (GRNs) are an essential part of the biological process that determines the biological characteristics of every living organism. In the context of evolutionary biology, one of the important goals of studying GRNs is to understand how rewiring of the network (due to genetic mutations) affects the biological properties of the individuals. In this talk, we will discuss how computational modeling and simulation of GRNs can be used to gain insights to answer these biological questions. In particular, we will review how GRN dynamics are modeled and simulated in computer simulations to collect representative data for understanding GRNs. We will then discuss how computational concepts, such as the network attractor landscape, can be used to gain a deeper understanding of network characteristics relevant for the evolution of GRNs.

Location: