PROBABILISTIC GRAPHICAL MODELLING OF CAUSAL EFFECTS AMONG THE OCCURRENCES OF TRANSCRIPTION FACTORS IN DNA SEQUENCE

DOI10.17654/JB015010039zbMath1433.62307OpenAlexW2806819018MaRDI QIDQ5204772

B. K. Nkansah, Gabriel Kallah-Dagadu, Nathaniel K. Howard

Publication date: 5 December 2019

Published in: JP Journal of Biostatistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.17654/jb015010039

zbMATH Keywords

causal effectsBayesian networkprobabilistic graphical modeltranscriptional factors

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) General biostatistics (92B15) Protein sequences, DNA sequences (92D20) Graphical methods in statistics (62A09)

Uses Software

• glasso
• glmnet
• bnlearn
• ebdbNet
• bnstruct

Cites Work

• Sparse inverse covariance estimation with the graphical lasso
• Evidential reasoning using stochastic simulation of causal models
• Bayesian network classifiers
• An empirical Bayesian method for estimating biological networks from temporal microarray data
• FLEXIBLE STATISTICAL MODELLING OF THE OCCURRENCES OF TRANSCRIPTION FACTOR BINDING SITES ALONG A DNA SEQUENCE
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