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Comparision of clustering methods for genetic networks
Comparision clustering methods genetic networks
2016/1/19
The goal of network clustering algorithms is to detect dense clusters in a network, which provides a first step towards the understanding of large scale biological networks. With numerous recent advan...
Identification of Stable Genetic Networks Using Convex Programming
Identifi cation Stable Genetic Networks Convex Programming
2015/7/9
Gene regulatory networks capture interactions between genes and other cell substances, resulting in various models for the fundamental biological process of transcription and translation. The expressi...
Inferring Stable Genetic Networks from Steady-State Data
convex optimization stability of linear systems
2015/7/9
Gene regulatory networks capture the interactions between genes and other cell substances, resulting from the fundamental biological process of transcription and translation. In some applications, the...
Inferring dynamic genetic networks with low order independencies
conditional independence Dynamic Bayesian Network DirectedAcyclic Graph networks inference time series modelling
2010/4/28
In this paper, we propose a novel inference method for dynamic genetic networks
which makes it possible to deal with a number of time measurements
n much smaller than the number of genes p. The appr...
Time-Varying Networks：Recovering Temporally Rewiring Genetic Networks During the Life Cycle of Drosophila melanogaster
Time-Varying Networks Rewiring Genetic Networks Life Cycle Drosophila melanogaster
2010/3/17
Due to the dynamic nature of biological systems, biological networks underlying temporal
process such as the development of Drosophila melanogaster can exhibit signicant topological changes to facili...