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On the basis of this problem definition, we propose in this study a new method to infer reduced NGnet models of genetic networks. ... When we use a set of differential equations to describe genetic networks, the inference problem can be defined as a function approximation problem. ... This work is partially supported by the Ministry of Education, Culture, Sports, Science and Technology of Japan under Grant-in-Aid for Young Scientists (B) No. 18710166. ...doi:10.1186/1471-2105-9-23 pmid:18194576 pmcid:PMC2258286 fatcat:qhcunrcugvawxj5k2hwk3yctiy
Gene regulatory network is the network of genes interacting with each other performing as functional circuitry inside a cell. ... There are a number of algorithms available in the literature which use recurrent neural network for model building together with differential evolution, particle swarm optimization or genetic algorithm ... Kimura S, Katsuki S, Soichiro Y, Hideki M, Koki M and Mariko H (2008) Function approximation approach to the inference of reduced ngnet models of genetic networks. BMC Bioinformatics 9: 111-124. ...doi:10.3329/ptcb.v28i2.39682 fatcat:hebit3cr5rcpfhaekjd6y7vyvi
Moreover, we also propose a new criterion for model evaluation exploiting the sparse and scale-free nature of GRNs to effectively narrow down the search space, which not only reduces the computation time ... However, many existing modeling approaches currently applied for inferring GRNs are unable to represent both these interactions simultaneously. ... To reduce computational complexity, method of  approximated the original problem as N decoupled sub-problems, each having 2(N+1) parameters. ...doi:10.1186/1471-2105-14-196 pmid:23777625 pmcid:PMC3839642 fatcat:olbvu5aj3jbstpx633djnlerpy
equations, smoothing overly noisy data, estimating slopes of time series, reducing the complexity of the inference task, and constraining the parameter search space. ... structure and regulation of the underlying biological networks. ... Acknowledgments The authors are grateful to Dr. Siren Veflingstad and two anonymous reviewers for critically reading the manuscript and providing constructive suggestions. ...doi:10.1016/j.mbs.2009.03.002 pmid:19327372 pmcid:PMC2693292 fatcat:rqnk3f34w5g2xl4qcwicbnwtnm
A gene regulatory network (GRN) represents a set of genes along with their regulatory interactions. Cellular behavior is driven by genetic level interactions. ... The comparison of the performance of proposed model with other existing methods shows the potential of the proposed model. ... The results presented for the 50-gene highly sparse network demonstrates the potential of MMD-GRN model for real-life problems of genetic network inference. ...doi:10.1016/j.biosystems.2019.103977 pmid:31185246 fatcat:z7mmg7k37jcxbilnk2gd3ei33e
Key geometric design parameters are optimized to minimize various objective functions within geometry optimization. ... We discuss how these techniques are applied to optimize the geometries and topologies of SRMs to enhance machine performance. ... ACKNOWLEDGMENT The authors thankfully acknowledge Powersys Solutions for their support with JMAG software in this study. ...doi:10.1109/access.2022.3140440 fatcat:76eqna2mrnezboalh57f4it3qq