Allows prediction of the cleavage propensity of a genomic site by a given single guide RNA (sgRNA). The CRISTA method incorporates a wide range of features specific to the genomic content, features that define the thermodynamics of the sgRNA, and features concerning the pairwise similarity between the sgRNA and the genomic target. This predictive model represents general patterns of the cleavage machinery across different detection techniques.
Department of Molecular Biology and Ecology of Plants, Tel Aviv University, Tel Aviv, Israel; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Graduate Program in Biophysics, Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA, USA; Blavatnik School of Computer Science, Tel-Aviv University, Tel Aviv, Israel; Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
CRISTA funding source(s)
Supported by a research grant 383/15 awarded by the ministry of agriculture of Israel and PhD fellowships provided by the Rothschild Caesarea Foundation, Edmond J. Safra Center for Bioinformatics at Tel-Aviv University, and travel fellowships provided by the Manna Program in Food Safety and Security, and the Naomi Prawer Kadar Foundation through the Tel Aviv University GRTF Program; the Simons Institute for the Theory of Computing; a Paul & Daisy Soros Fellowship for New Americans and by award Number T32GM007753 from the National Institute of General Medical Sciences.
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