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Biomedical subjects

G Elidan

Publications and source records attributed to G Elidan.

2 recordsLinked to original sources

CIS: compound importance sampling method for protein-DNA binding site p-value estimation.

MOTIVATION: A key aspect of transcriptional regulation is the binding of transcription factors to sequence-specific binding sites that allow them to modulate the expression of nearby genes. Given models of such binding sites, one can scan regulatory regions for putative binding sites and construct a genome-wide regulatory network. In such genome-wide scans, it is crucial to control the amount of false positive predictions. Recently, several works demonstrated the benefits of modeling dependencies between positions within the binding site. Yet, computing the statistical significance of putative binding sites in this scenario remains a challenge. RESULTS: We present a general, accurate and efficient method for computing p-values of putative binding sites that is applicable to a large class of probabilistic binding site and background models. We demonstrate the accuracy of the method on synthetic and real-life data. AVAILABILITY: The procedure for scanning DNA sequences and computing the statistical significance of putative binding site scores is available upon request at http://compbio.cs.huji.ac.il/CIS/ CONTACT: nir@cs.huji.ac.il.

Algorithms↗

Inferring subnetworks from perturbed expression profiles.

Genome-wide expression profiles of genetic mutants provide a wide variety of measurements of cellular responses to perturbations. Typical analysis of such data identifies genes affected by perturbation and uses clustering to group genes of similar function. In this paper we discover a finer structure of interactions between genes, such as causality, mediation, activation, and inhibition by using a Bayesian network framework. We extend this framework to correctly handle perturbations, and to identify significant subnetworks of interacting genes. We apply this method to expression data of S. cerevisiae mutants and uncover a variety of structured metabolic, signaling and regulatory pathways.

Bayes Theorem↗