MicroRNAs (miRNAs) regulate gene expression by binding to partially complementary sequences on target mRNA transcripts, thereby causing their degradation, deadenylation, or inhibiting their translation. Genomic variants can alter miRNA regulation by modifying miRNA target sites, and multiple human disease phenotypes have been linked to such miRNA target site variants (miR-TSVs).
MicroRNAs (miRNAs) impact various biological processes within animals and plants. They complementarily bind target mRNAs, effecting a post-transcriptional negative regulation on mRNA level. The investigation of miRNA target interactions (MTIs) by high throughput screenings is challenging, as frequently used in silico target prediction tools are prone to emit false positives. This issue is aggravated for niche model organisms, where validated miRNAs and MTIs both have to be transferred from well described model organisms.
Biological systems are increasingly being studied by high throughput profiling of molecular data over time. Determining the set of time points to sample in studies that profile several different types of molecular data is still challenging. Here we present the Time Point Selection (TPS) method that solves this combinatorial problem in a principled and practical way. TPS utilizes expression data from a small set of genes sampled at a high rate.
RNA editing is a widespread post-transcriptional mechanism that can make a single base change on specific nucleotide sequence in an RNA transcript. RNA editing events can result in missense codon changes and modulation of alternative splicing in mRNA, and modification of regulatory RNAs and their binding sites in noncoding RNAs. Recent computational studies accurately detected more than 2 million A-to-I RNA editing sites from next-generation sequencing (NGS).
Small non-coding RNAs, in particular microRNAs, are critical for normal physiology and are candidate biomarkers, regulators, and therapeutic targets for a wide variety of diseases. There is an ever-growing interest in the comprehensive and accurate annotation of microRNAs across diverse cell types, conditions, species, and disease states. Highthroughput sequencing technology has emerged as the method of choice for profiling microRNAs.
Recently, as the research of microRNA (miRNA) continues, there are plenty of experimental evidences indicating that miRNA could be associated with various human complex diseases development and progression. Hence, it is necessary and urgent to pay more attentions to the relevant study of predicting diseases associated miRNAs, which may be helpful for effective prevention, diagnosis and treatment of human diseases.
Epigenetic mechanisms play key roles in initiation and progression of prostate cancer by changing gene expression. The Prostate Epigenetic Database (PEpiD: http://wukong.tongji.edu.cn/pepid) archives the three extensively characterized epigenetic mechanisms DNA methylation, histone modification, and microRNA implicated in prostate cancer of human, mouse, and rat. PEpiD uses a distinct color scheme to present the three types of epigenetic data and provides a user-friendly interface for flexible query.
microRNAs and microRNA-independent RNA-binding proteins are 2 classes of post-transcriptional regulators that have been shown to cooperate in gene-expression regulation. We compared the genome-wide target sets of microRNAs and RBPs identified by recent CLIP-Seq technologies, finding that RBPs have distinct target sets and favor gene interaction network hubs. To identify microRNAs and RBPs with a similar functional context, we developed simiRa, a tool that compares enriched functional categories such as pathways and GO terms.
A group of miRNAs can regulate a biological process by targeting genes involved in the process. The unbiased miRNA functional enrichment analysis is the most precise in silico approach to predict the biological processes that may be regulated by a given miRNA group. However, it is computationally intensive and significantly more expensive than its alternatives.
BACKGROUND: Long noncoding RNAs (lncRNAs) have been shown to play essential roles in almost every important biological process through multiple mechanisms. Although the repertoire of human lncRNAs has rapidly expanded, their biological function and regulation remain largely elusive, calling for a systematic and integrative annotation tool. RESULTS: Here we present AnnoLnc ( http://annolnc.cbi.pku.edu.cn ), a one-stop portal for systematically annotating novel human lncRNAs.
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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