Rapid Reconstruction of Time-Varying Gene Regulatory Networks

Rapid advancements in high-throughput technologies have resulted in genome-scale time series datasets. Uncovering the temporal sequence of gene regulatory events, in the form of time-varying gene regulatory networks (GRNs), demands computationally fast, accurate, and scalable algorithms. The existin...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics 2020-01, Vol.17 (1), p.278-291
Hauptverfasser:	Pyne, Saptarshi, Kumar, Alok Ranjan, Anand, Ashish
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayes methods Bayesian network Computational Biology - methods computational systems biology Couplings Databases, Genetic Datasets Gene expression Gene regulatory network Gene Regulatory Networks - genetics Genomes Humans Information management Machine Learning Models, Statistical network inference network reconstruction Networks Nucleotide sequence Prediction algorithms probabilistic graphical model Regulators Regulatory sequences Rejection structure learning temporal progression model Time series analysis
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