Prediction of efficient oligonucleotides for RNA interference presents a serious challenge, especially for the development of genome-wide RNAi libraries which encounter difficulties and limitations due to ambiguities in the results and the requirement for significant computational resources. Here we present a fast and practical algorithm for shRNA design based on the thermodynamic parameters.
RNA interference (RNAi) serves as a powerful and widely used gene silencing tool for basic biological research and is being developed as a therapeutic avenue to suppress disease-causing genes. However, the specificity and safety of RNAi strategies remains under scrutiny because small inhibitory RNAs (siRNAs) induce off-target silencing. Currently, the tools available for designing siRNAs are biased toward efficacy as opposed to specificity.
Small silencing RNAs, including microRNAs, endogenous small interfering RNAs (endo-siRNAs) and Piwi-interacting RNAs (piRNAs), have been shown to play important roles in fine-tuning gene expression, defending virus and controlling transposons. Loss of small silencing RNAs or components in their pathways often leads to severe developmental defects, including lethality and sterility. Recently, non-templated addition of nucleotides to the 3' end, namely tailing, was found to associate with the processing and stability of small silencing RNAs.
High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens.
The Plant Small RNA Maker Site (P-SAMS) is a web tool for the simple and automated design of artificial miRNAs (amiRNAs) and synthetic trans-acting small interfering RNAs (syn-tasiRNAs) for efficient and specific targeted gene silencing in plants. P-SAMS includes two applications, P-SAMS amiRNA Designer and P-SAMS syn-tasiRNA Designer. The navigation through both applications is wizard-assisted, and the job runtime is relatively short.
Genome-wide identification of specific oligonucleotides (oligos) is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN) is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos.
RNA-dependent gene silencing is becoming a routine tool used in laboratories worldwide. One of the important remaining hurdles in the selection of the target sequence, if not the most important one, is the designing of tools that have minimal off-target effects (i.e. cleaves only the desired sequence). Increasingly, in the current dawn of the post-genomic era, there is a heavy reliance on tools that are suitable for high-throughput functional genomics, consequently more and more bioinformatic software is becoming available.
Short interfering RNAs (siRNAs) can knockdown target genes and thus have an immense impact on biology and pharmacy research. The key question of which siRNAs have high knockdown ability in siRNA research remains challenging as current known results are still far from expectation.
Our innate immune system recognizes a foreign RNA sequence of a pathogen and activates the immune system to eliminate the pathogen from our body. This immunomodulatory potential of RNA can be used to design RNA-based immunotherapy and vaccine adjuvants. In case of siRNA-based therapy, the immunomodulatory effect of an RNA sequence is unwanted as it may cause immunotoxicity. Thus, we developed a method for designing a single-stranded RNA (ssRNA) sequence with desired immunomodulatory potentials, for designing RNA-based therapeutics, immunotherapy and vaccine adjuvants.
RNAi screens are widely used in functional genomics. Although the screen data can be susceptible to a number of experimental biases, many of these can be corrected by computational analysis. For this purpose, here we have developed a web-based platform for integrated analysis and visualization of RNAi screen data named CARD (for Comprehensive Analysis of RNAi Data; available at https://card.niaid.nih.gov).
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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