The identification of human disease-related microRNAs (disease miRNAs) is important for further investigating their involvement in the pathogenesis of diseases. More experimentally validated miRNA-disease associations have been accumulated recently. On the basis of these associations, it is essential to predict disease miRNAs for various human diseases. It is useful in providing reliable disease miRNA candidates for subsequent experimental studies.
The identification of novel miRNAs has significant biological and clinical importance. However, none of the known miRNA features alone is sufficient for accurately detecting novel miRNAs. The aim of this paper is to integrate these features in a straightforward manner for detecting miRNAs with better accuracy.
miRDeepFinder is a software package developed to identify and functionally analyze plant microRNAs (miRNAs) and their targets from small RNA datasets obtained from deep sequencing. The functions available in miRDeepFinder include pre-processing of raw data, identifying conserved miRNAs, mining and classifying novel miRNAs, miRNA expression profiling, predicting miRNA targets, and gene pathway and gene network analysis involving miRNAs.
MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs that regulate gene and protein expression in plants and animals. MiRNAs have so far been identified mostly by specific cloning of small RNA molecules, complemented by computational methods. We present a computational identification approach that is able to identify candidate miRNA homologs in any set of sequences, given a query miRNA. The approach is based on a sequence similarity search step followed by a set of structural filters.[1]
Transcription factors (TFs) and microRNAs play important roles in the regulation of human gene expression, and the study of their combinatory regulations of gene expression is a new research field. We constructed a comprehensive web server, the composite regulatory signature database (CRSD), that can be applied in investigating complex regulatory behaviors involving gene expression signatures (GESs), microRNA regulatory signatures (MRSs) and TF regulatory signatures (TRSs).
MicroRNAs (miRNAs) are critical regulators in the complex cellular networks. The mirAct web server (http://sysbio.ustc.edu.cn/software/mirAct) is a tool designed to investigate miRNA activity based on gene-expression data by using the negative regulation relationship between miRNAs and their target genes. mirAct supports multiple-class data and enables clustering analysis based on computationally determined miRNA activity.
Artificially synthesized short interfering RNAs (siRNAs) are widely used in functional genomics to knock down specific target genes. One ongoing challenge is to guarantee that the siRNA does not elicit off-target effects. Initial reports suggested that siRNAs were highly sequence-specific; however, subsequent data indicates that this is not necessarily the case.
RNA interference (RNAi) with small interfering RNA (siRNA) has become a powerful tool in functional and medical genomic research through directed post-transcriptional gene silencing. In order to apply RNAi technique for eukaryotic organisms, where frequent alternative splicing results in diversification of mRNAs and finally of proteins, we need spliced mRNA isoform silencing to study the function of individual proteins.
A cattle database of candidate genes and genetic markers for milk production and mastitis has been developed to provide an integrated research tool incorporating different types of information supporting a genomic approach to study lactation, udder development and health. The database contains 943 genes and genetic markers involved in mammary gland development and function, representing candidates for further functional studies. The candidate loci were drawn on a genetic map to reveal positional overlaps.
Plant microRNAs (miRNAs) have been revealed to play important roles in developmental control, hormone secretion, cell differentiation and proliferation, and response to environmental stresses. However, our knowledge about the regulatory mechanisms and functions of miRNAs remains very limited. The main difficulties lie in two aspects. On one hand, the number of experimentally validated miRNA targets is very limited and the predicted targets often include many false positives, which constrains us to reveal the functions of miRNAs.
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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