Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study |
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Authors: | Qi Liu Qian Xu Vincent W Zheng Hong Xue Zhiwei Cao Qiang Yang |
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Institution: | (1) College of Life Science and Biotechnology, Tongji University, China;(2) Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong;(3) Department of Biochemistry, Hong Kong University of Science and Technology, Hong Kong;(4) Shanghai Center for Bioinformation Technology, China |
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Abstract: | Background Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study
and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into
the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins.
Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of
different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint
analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different
datasets and experimental conditions can often provide new clues on the design of potent siRNAs. |
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