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Integrative Modeling for Binding Site Identification in ChIP Experiments

This study integrates observed fragment length distributions from Raw ChIP experiments using positional priors and TF affinity to predict binding events. The platform combines Candidate Motifs Database integration, Generative model of binding data, and Comparative Genomics with Known motif databases and DNase hypersensitivity motifs for refinement. The result is an Integrated binding site identification platform.

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Integrative Modeling for Binding Site Identification in ChIP Experiments

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  1. Observed fragment length distributions Raw ChIP experiments PBM TF affinity Positional Priors, Binding Events , Candidate Motifs Database integration Generative model of binding data and sequence Comparative Genomics Known motif databases DNase hyper sensitivity Motifs for refinement Integrated binding site identification platform

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