RFRCDB-siRNA: Improved design of siRNAs by random forest regression model coupled with database searching

Jiang, Peng; Wu, Haonan; Da, Yao; Sang, Fei; Wei, Jiawei; Sun, Xiao; Zhang, Lu

doi:10.1016/j.cmpb.2007.06.001

Cited by 30 publications

(15 citation statements)

References 38 publications

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“…Such rules for designing siRNA are formulated to a table in literature16. In the formulated table, it lists the performance of nucleotide at each position to siRNA efficacy combining 12 rules from the published reports, including Reynolds’s, Ui_tei’s, and Hsieh’s rules7810132930313233. We can understand that the nucleotide at each position may prefer for active siRNA or inactive siRNA by seeking the table.…”

Section: Methodsmentioning

confidence: 99%

Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level

Han

Gong

et al. 2017

Sci Rep

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Small interfering RNAs (siRNAs) may induce to targeted gene knockdown, and the gene silencing effectiveness relies on the efficacy of the siRNA. Therefore, the task of this paper is to construct an effective siRNA prediction method. In our work, we try to describe siRNA from both quantitative and qualitative aspects. For quantitative analyses, we form four groups of effective features, including nucleotide frequencies, thermodynamic stability profile, thermodynamic of siRNA-mRNA interaction, and mRNA related features, as a new mixed representation, in which thermodynamic of siRNA-mRNA interaction is introduced to siRNA efficacy prediction for the first time to our best knowledge. And then an F-score based feature selection is employed to investigate the contribution of each feature and remove the weak relevant features. Meanwhile, we encode the siRNA sequence and existed empirical design rules as a qualitative siRNA representation. These two kinds of siRNA representations are combined to predict siRNA efficacy by supported Vector Regression (SVR) at score level. The experimental results indicate that our method may select the features with powerful discriminative ability and make the two kinds of siRNA representations work at full capacity. The prediction results also demonstrate that our method can outperform other popular siRNA efficacy prediction algorithms.

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Section: Methodsmentioning

confidence: 99%

Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level

Han

Gong

et al. 2017

Sci Rep

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“…44 RFRCDB-siRNA is another online tool for the design of siRNAs based on the random forest regression model connected with database searching. 45 Without any doubt, RNAcentral is the most complex database that has joined 12 new resources and started the importing of new types of data for ncRNAs, 46 such as nucleotides modification furnished from MODOMICS and Protein Data Bank, offering also free access. 44…”

Section: Overcoming the Challenges Of Sirna Therapymentioning

confidence: 99%

RNA interference: new mechanistic and biochemical insights with application in oral cancer therapy

Buduru

Zimța

Ciocan

et al. 2018

IJN

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Over the last few decades, the incidence of oral cancer has gradually increased, due to the negative influence of environmental factors and also abnormalities within the genome. The main issues in oral cancer treatment consist in surpassing resistance and recurrence. However, continuous discovery of altered signaling pathways in these tumors provides valuable information for the identification of novel gene candidates targeted in personalized therapy. RNA interference (RNAi) is a natural mechanism that involves small interfering RNA (siRNA); this can be exploited in biomedical research by using natural or synthetic constructs for activation of the mechanism. Synthetic siRNA transcripts were developed as a versatile class of molecular tools that have a diverse range of programmable roles, being involved in the regulation of several biological processes, thereby providing the perspective of an alternative option to classical treatment. In this review, we summarize the latest information related to the application of siRNA in oral malignancy together with molecular aspects of the technology and also the perspective upon the delivery system. Also, the emergence of newer technologies such as clustered regularly interspaced short palindromic repeats/Cas9 or transcription activator-like effector nucleases in comparison with the RNAi approach is discussed in this paper.

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“…By Q 4 ( i ) with mini-clusters, these 1,3587 siRNAs are put into different mini-clusters, where 1587 simulation siRNAs are put into effective mini-clusters, Q 4 ( i ) are estimated by all effective experimental siRNAs. The efficiency of these 1587 simulation siRNAs are de novo validated by a web-server RFRCDB-siRNA [27], which is available at http://www. bioinf.seu.edu.cn/siRNA/index.htm.…”

Section: Availabilitymentioning

confidence: 99%

Mini-clusters with mean probabilities for identifying effective siRNAs

2012

Self Cite

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BackgroundThe distinction between the effective siRNAs and the ineffective ones is in high demand for gene knockout technology. To design effective siRNAs, many approaches have been proposed. Those approaches attempt to classify the siRNAs into effective and ineffective classes but they are difficult to decide the boundary between these two classes.FindingsHere, we try to split effective and ineffective siRNAs into many smaller subclasses by RMP-MiC(the relative mean probabilities of siRNAs with the mini-clusters algorithm). The relative mean probabilities of siRNAs are the modified arithmetic mean value of three probabilities, which come from three Markov chain of effective siRNAs. The mini-clusters algorithm is a modified version of micro-cluster algorithm.ConclusionsWhen the RMP-MiC was applied to the experimental siRNAs, the result shows that all effective siRNAs can be identified correctly, and no more than 9% ineffective siRNAs are misidentified as effective ones. We observed that the efficiency of those misidentified ineffective siRNAs exceed 70%, which is very closed to the used efficiency threshold. From the analysis of the siRNAs data, we suggest that the mini-clusters algorithm with relative mean probabilities can provide new insights to the applications for distinguishing effective siRNAs from ineffective ones.

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RFRCDB-siRNA: Improved design of siRNAs by random forest regression model coupled with database searching

Cited by 30 publications

References 38 publications

Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level

Predicting siRNA efficacy based on multiple selective siRNA representations and their combination at score level

RNA interference: new mechanistic and biochemical insights with application in oral cancer therapy

Mini-clusters with mean probabilities for identifying effective siRNAs

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