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J Comput Biol

Title:		Explore biological pathways from noisy array data by directed acyclic Boolean networks
Author(s):		Li LM; Lu HH;
Address:		"Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA. lilei@hto.usc.edu"
Journal Title:		J Comput Biol
Year:		2005
Volume:		12
Issue:		2
Page Number:		170 - 185
DOI:		10.1089/cmb.2005.12.170
ISSN/ISBN:		1066-5277 (Print) 1066-5277 (Linking)
Abstract:		"We consider the structure of directed acyclic Boolean (DAB) networks as a tool for exploring biological pathways. In a DAB network, the basic objects are binary elements and their Boolean duals. A DAB is characterized by two kinds of pairwise relations: similarity and prerequisite. The latter is a partial order relation, namely, the on-status of one element is necessary for the on-status of another element. A DAB network is uniquely determined by the state space of its elements. We arrange samples from the state space of a DAB network in a binary array and introduce a random mechanism of measurement error. Our inference strategy consists of two stages. First, we consider each pair of elements and try to identify their most likely relation. In the meantime, we assign a score, s-p-score, to this relation. Second, we rank the s-p-scores obtained from the first stage. We expect that relations with smaller s-p-scores are more likely to be true, and those with larger s-p-scores are more likely to be false. The key idea is the definition of s-scores (referring to similarity), p-scores (referring to prerequisite), and s-p-scores. As with classical statistical tests, control of false negatives and false positives are our primary concerns. We illustrate the method by a simulated example, the classical arginine biosynthetic pathway, and show some exploratory results on a published microarray expression dataset of yeast Saccharomyces cerevisiae obtained from experiments with activation and genetic perturbation of the pheromone response MAPK pathway"
Keywords:		"Algorithms Arginine/biosynthesis Computational Biology/*statistics & numerical data Metabolism/*physiology Mitogen-Activated Protein Kinases/biosynthesis/genetics Models, Biological Oligonucleotide Array Sequence Analysis/*statistics & numerical data Sacc;"
Notes:		"MedlineLi, Lei M Lu, Henry Horng-Shing eng Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, P.H.S. 2005/03/16 J Comput Biol. 2005 Mar; 12(2):170-85. doi: 10.1089/cmb.2005.12.170"