Brief. Bioinformatics - Reconsideration of in silico siRNA design from a perspective of heterogeneous data integration: problems and solutions.

Tópicos

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Resumo

The success of RNA interference (RNAi) depends on the interaction between short interference RNAs (siRNAs) and mRNAs. Design of highly efficient and specific siRNAs has become a challenging issue in applications of RNAi. Here, we present a detailed survey on the state-of-the-art siRNAs design, focusing on several key issues with the current in silico RNAi studies, including: (i) inconsistencies among the proposed guidelines for siRNAs design and the incomplete list of siRNAs features, (ii) improper integration of the heterogeneous cross-platform siRNAs data, (iii) inadequate consideration of the binding specificity of the target mRNAs and (iv) reduction in the 'off-target' effect in siRNAs design. With these considerations, the popular in silico siRNAs design rules are reexamined and several inconsistent viewpoints toward siRNAs feature identifications are clarified. In addition, novel computational models for siRNAs design using state-of-art machine learning techniques are discussed, which focus on heterogeneous data integration, joint feature selection and customized siRNAs screening toward highly specific targets. We believe that addressing such issues in siRNA study will provide new clues for further improved design of more efficient and specific siRNAs in RNAi.

Resumo Limpo

success rna interfer rnai depend interact short interfer rnas sirna mrnas design high effici specif sirna becom challeng issu applic rnai present detail survey stateoftheart sirna design focus sever key issu current silico rnai studi includ inconsist among propos guidelin sirna design incomplet list sirna featur ii improp integr heterogen crossplatform sirna data iii inadequ consider bind specif target mrnas iv reduct offtarget effect sirna design consider popular silico sirna design rule reexamin sever inconsist viewpoint toward sirna featur identif clarifi addit novel comput model sirna design use stateofart machin learn techniqu discuss focus heterogen data integr joint featur select custom sirna screen toward high specif target believ address issu sirna studi will provid new clue improv design effici specif sirna rnai

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