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Nov 22 2021

11/22 – Xiaowei Wang, University of Illinois Chicago

CBQB Seminar

November 22, 2021

12:00 PM - 1:00 PM


Chicago, IL

Watch this webinar live with Zoom>>

Speaker: Xiaowei Wang

Professor of Pharmacology and Bioengineering, University of Illinois at Chicago
Director of Bioinformatics Core, University of Illinois Cancer Center

Title: Combined Computational and Experimental Approaches to Determine the Efficacy of RNA Targeting

One important topic in RNA research is the identification of sequence regions that are efficiently bound and targeted by functional RNA molecules. To this end, we combined computational and experimental approaches to determine the targeting efficacy of two small non-coding RNAs, miRNA and sgRNA(1) miRNAs play regulatory roles in many physiological and disease processes, and they exert their functions mainly by suppressing their gene targets. In our study, we performed a large-scale RNA sequencing study to experimentally identify genes that are downregulated by miRNAs. This RNA-seq dataset was combined with public miRNA target binding data to systematically identify miRNA targeting features that are characteristic of both miRNA binding and target downregulation. By integrating these common features in a machine learning framework, we have developed an online resource, miRDB (, for genome-wide miRNA target prediction. (2) The CRISPR/Cas9 technology has provided a simple yet powerful system for targeted genome editing. The CRISPR editing efficacy is mainly dependent on the sgRNA, which guides Cas9 for genome cleavage. Currently, there is a pressing need for greater sgRNA potency in CRISPR knockout studies. To address this issue, we employed a unique plasmid library expressed in human cells to quantify the potency of thousands of CRISPR sgRNAs. Relevant sequence and structural features extracted from this dataset were used to train an ensemble machine learning algorithm, which was further developed into an online resource for sgRNA design (



Date posted

Nov 8, 2021

Date updated

Nov 8, 2021