PlantcircBase
Abstract is not available.[1]
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Arabidopsis
miRAFinder and GeneAFinder scripts
In recent times, information on miRNAs and their binding sites is gaining momentum. Therefore, there is interest in the development of tools extracting miRNA related information from known literature. Hence, we describe GeneAFinder and miRAFinder scripts (open source) developed using python programming for the semi-automatic extraction and arrangement of updated information on miRNAs, genes and additional data from published article abstracts in PubMed. The scripts are suitable for custom modification as per requirement.
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miRQuest
This report describes the miRQuest - a novel middleware available in a Web server that allows the end user to do the miRNA research in a user-friendly way. It is known that there are many prediction tools for microRNA (miRNA) identification that use different programming languages and methods to realize this task. It is difficult to understand each tool and apply it to diverse datasets and organisms available for miRNA analysis. miRQuest can easily be used by biologists and researchers with limited experience with bioinformatics.
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miRPursuit
miRPursuit is a pipeline developed for running end-to-end analyses of high-throughput small RNA (sRNA) sequence data in model and nonmodel plants, from raw data to identified and annotated conserved and novel sequences. It consists of a series of UNIX shell scripts, which connect open-source sRNA analysis software. The involved parameters can be combined with convenient workflow management by users without advanced computational skills.
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CePa
CePa is an R package aiming to find significant pathways through network topology information. The package has several advantages compared with current pathway enrichment tools. First, pathway node instead of single gene is taken as the basic unit when analysing networks to meet the fact that genes must be constructed into complexes to hold normal functions. Second, multiple network centralities are applied simultaneously to measure importance of nodes from different aspects to make a full view on the biological system.
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NoiseMaker
High-throughput screening (HTS) is a common technique for both drug discovery and basic research, but researchers often struggle with how best to derive hits from HTS data. While a wide range of hit identification techniques exist, little information is available about their sensitivity and specificity, especially in comparison to each other. To address this, we have developed the open-source NoiseMaker software tool for generation of realistically noisy virtual screens.
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AtCircDB
Circular RNAs are widely existing in eukaryotes. However, there is as yet no tissue-specific Arabidopsis circular RNA database, which hinders the study of circular RNA in plants. Here, we used 622 Arabidopsis RNA sequencing data sets from 87 independent studies hosted at NCBI SRA and developed AtCircDB to systematically identify, store and retrieve circular RNAs. By analyzing back-splicing sites, we characterized 84685 circular RNAs, 30648 tissue-specific circular RNAs and 3486 microRNA-circular RNA interactions.
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OfftargetFinder
RNA interference (RNAi) technology is being developed as a weapon for pest insect control. To maximize the specificity that such an approach affords we have developed a bioinformatic web tool that searches the ever-growing arthropod transcriptome databases so that pest-specific RNAi sequences can be identified. This will help technology developers finesse the design of RNAi sequences and suggests which non-target species should be assessed in the risk assessment process.
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comTAR
MicroRNAs (miRNAs) are major regulators of gene expression in plants and animals. They recognize their target messenger RNAs (mRNAs) by sequence complementarity and guide them to cleavage or translational arrest. So far, the prediction of plant miRNA-target pairs generally relies on the use of empirical parameters deduced from known miRNA-target interactions.
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Semirna
Many plant genomes are already known, and new ones are being sequenced every year. The next step for researchers is to identify all of the functional elements in these genomes, including the important class of functional elements known as microRNAs (miRNAs), which are involved in posttranscriptional regulatory pathways. However, computational tools for predicting new plant miRNAs are limited, and there is a particular need for tools that can be used easily by laboratory researchers.
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