We applied a dynamic Bayesian network method that identifies joint patterns from multiple functional genomics experiments to ChIP-seq histone modification and transcription factor data, and DNaseI-seq and FAIRE-seq open chromatin readouts from the human cell line K562. In an unsupervised fashion, we identified patterns associated with transcription start sites, gene ends, enhancers, CTCF elements, and repressed regions. Software and genome browser tracks are at Author contributions M.M.H., W.S.N., and J.A.B. conceived the project; M.M.H., W.S.N, and Z.W. designed computational and biological experiments. M.M.H., J.A.B., O.J.B., and J.W. developed software used in this work; M.M.H., O.J.B., and J.W. performed computational experiments and analyzed data; M.M.
are inventors on patent applications related to this work. S.V.B. and D.D.D.C. are co-founders and provide consulting for DNAMx, Inc. S.V.B. is co-inventor on patents relating to mutation-based ctDNA detection technology licensed to Roche Molecular Diagnostics. D.D.D.C. and S.V.B. have received institutional research funding from Nektar Therapeutics.Research.
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