Automated inference of gene regulatory networks using explicit regulatory modules

Improving the Inference of Gene Expression Regulatory Networks with Data Aggregation Approach

Introduction: The major issue for the future of bioinformatics is the design of tools to determine the functions and all products of single-cell genes. This requires the integration of different biological disciplines as well as sophisticated mathematical and statistical tools. This study revealed that data mining techniques can be used to develop models for diagnosing high-risk or low-risk lif...

Improving the Inference of Gene Expression Regulatory Networks with Data Aggregation Approach

Introduction: The major issue for the future of bioinformatics is the design of tools to determine the functions and all products of single-cell genes. This requires the integration of different biological disciplines as well as sophisticated mathematical and statistical tools. This study revealed that data mining techniques can be used to develop models for diagnosing high-risk or low-risk lif...

Automated Inference of Symbolic Models for Gene Regulatory Networks

Motivation: Multiple models exist to describe the topology and the dynamical behavior of gene regulatory networks (GRNs). Among them, symbolic models (such as systems of ordinary differential equations) have the advantage of providing intuitive insights into the inner workings of a network so that general laws can be derived. Obtaining such models from time series data has proven to be a diffic...

Inference of gene regulatory networks using Bayesian network

It has been attempted to reveal regulatory information from microarray data using Bayesian network [1]. However, due to limitation of microarray, successful result is obtained only under a limited condition. For this reason, Bayesian network from combining microarray with biological knowledge was proposed [2]. In this paper, we proposed Bayesian network learned by genetic algorithm to infer gen...

Computational Methods of Discovering Gene Modules and Constructing Regulatory Networks