Please use this identifier to cite or link to this item:
Title: Loregic: A Method to Characterize the Cooperative Logic of Regulatory Factors
Authors: Yan, K-K
Sisu, C
Cheng, C
Rozowsky, J
Meyerson, W
Gerstein, MB
Keywords: Science & Technology;Life Sciences & Biomedicine;Biochemical Research Methods;Mathematical & Computational Biology;Biochemistry & Molecular Biology;CELL-CYCLE;SACCHAROMYCES-CEREVISIAE;TRANSCRIPTION FACTORS;GENOMIC ANALYSIS;GENE-EXPRESSION;BOOLEAN LOGIC;C-MYC;NETWORKS;IDENTIFICATION;BINDING
Issue Date: 2015
Citation: PLOS COMPUTATIONAL BIOLOGY, 2015, 11 (4), pp. ? - ? (21)
Abstract: The topology of the gene-regulatory network has been extensively analyzed. Now, given the large amount of available functional genomic data, it is possible to go beyond this and systematically study regulatory circuits in terms of logic elements. To this end, we present Loregic, a computational method integrating gene expression and regulatory network data, to characterize the cooperativity of regulatory factors. Loregic uses all 16 possible twoinput- one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target. We attempt to find the gate that best matches each triplet’s observed gene expression pattern across many conditions. We make Loregic available as a generalpurpose tool ( We validate it with known yeast transcriptionfactor knockout experiments. Next, using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs. Furthermore, we show that MYC, a well-known oncogenic driving TF, can be modeled as acting independently from other TFs (e.g., using OR gates) but antagonistically with repressing miRNAs. Finally, we inter-relate Loregic’s gate logic with other aspects of regulation, such as indirect binding via protein-protein interactions, feed-forward loop motifs and global regulatory hierarchy.
ARTN e1004132
ARTN e1004132
Appears in Collections:Dept of Life Sciences Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext.pdf1.32 MBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.