Gene Regulatory Network inference
Gene regulatory network inference: evaluation and application to ovarian cancer allows the prioritization of drug targets
... of gene regulation underlie many complex conditions, including ...Inferring gene regulatory networks from high-throughput microarray expression data is a fundamental but challenging task in ...
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Experimental design trade-offs for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle
... for gene regulatory network inference: an in silico study of the yeast Saccharomyces cerevisiae cell cycle Johan Markdahl, Nicolo Colombo, Johan Thunberg, and Jorge Gonc¸alves Abstract— ...
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Learning a Markov Logic network for supervised gene regulatory network inference
... the huge number of negative examples of “no regulation”. Finally, the fourth issue we tackle in this paper, concerns the performance assessment of a supervised edge pre- diction tool. Although the best performance ...
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Gene Regulatory Network Inference Using Machine Learning Techniques
... steady-state gene expression data to learn the ordinary dif- ferential equation defining each gene’s transcription ...Bayesian network, ordinary differential based methods, Granger causality based methods, ...
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Gene regulatory network inference I: Dissecting structure and dynamics
... of gene network Networks are abstractions of real-life systems in terms of graphs consisting of nodes and ...analyzing network structure and its implications for the dynamics, and hence the function, ...
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NetDiff – Bayesian model selection for differential gene regulatory network inference
... in network structures between ...the network structure under a single condition does not improve on competing methods, the focus is in this work to allow for the inference of dif- ferential networks ...
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Gene regulatory network inference : connecting plant biology and mathematical modeling
... to inference ( de Luis Balaguer et ...Bayesian Network (DBN), respectively ( Friedman et al., 1998 ). In DBN inference, a time- course dataset is provided to predict probabilistic dependencies ...
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Gene regulatory network inference from sparsely sampled noisy data
... each network, and the majority of the network could be inferred ...clock network, on the other hand, was inferred from one time series, and in this case it is not possible to get the full ...
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NIMEFI: gene regulatory network inference using multiple ensemble feature importance algorithms
... topology inference of gene regulatory networks from high-throughput omics ...benchmark network inference techniques using gene expression ...the network inference ...
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A sparse Bayesian learning method for structural equation model-based gene regulatory network inference
... of gene expression data is usually high, it is difficult to process them without any ...a gene directly regu- lates or is regulated by a small number of genes relative to the total number of genes in the ...
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Inference of gene regulatory networks from genome-wide knockout fitness data
... of gene regula- tory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene ...novel gene ...
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Inference of Gene Regulatory Network using Fuzzy Logic A Review
... the network of interactions between the genes named as Gene Regulatory Networks ...microarray gene expression datasetsare available that can be used to analyse the relationships between the ...
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Bayesian Inference of gene-miRNA regulatory networks
... a network of gene-miRNA interactions, by sampling the data and parameters under the assumptions of our ...random network the original network built under our ...
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Approximate inference of gene regulatory network models from RNA-Seq time series data
... cerevisiae gene regulatory network was not contained in the 95% credible interval of the corresponding regression coefficients, and for the Lasso and glmnet methods, non-zero coefficients were taken ...
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On the Choice and Number of Microarrays for Transcriptional Regulatory Network Inference
... transcriptional regulatory interactions from large collec- tions of microarray ...in Gene Expression Omnibus (GEO) database [22]), and ...gical network, so that considerations of such issues here ...
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Wisdom of crowds for robust gene network inference
... Bayesian network methods exhibited below-average performance in this challenge, likely because they use heuristic searches, which are often too costly for systematic data resampling and may be better suited for ...
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GeRNet: A Gene Regulatory Network Tool
... the gene networks are hard to be mapped with accuracy by any other mathematical ...the inference of large size models with a higher speed of ...the network is partial, hence incomplete, for an ...
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The inference of breast cancer metastasis through gene regulatory networks
... constructed network using low-order conditional independence appears to provide modest improve- ments in GRN inference relative to full-order conditional indepen- ...prominent regulatory genes during ...
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Nonparametric Bayesian inference for perturbed and orthologous gene regulatory networks
... 3.2 Modelling of in silico time series from independent networks The results in Section 3.1 demonstrate that the hCSI framework can prove useful when the individual datasets are generated from identical networks, by ...
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Efficient and Robust Algorithms for Statistical Inference in Gene Regulatory Networks
... SPARSE GENE REGULATORY NETWORKS USING CUBATURE KALMAN FILTER AND COMPRESSED SENSING* ...for gene network modeling have been proposed recently in the literature with varying degrees of ...
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