In silico generated search for microRNAs (miRNAs) has been driven by methods compiling structural features of the miRNA precursor hairpin, as well as to some degree combining this with the analysis of RNA-seq profiles for which the miRNA typically leave the drosha/dicer fingerprint of 1-2 ~22 nt blocks of reads corresponding to the mature and star miRNA. In complement to the previous methods, we present a study where we systematically exploit these patterns of read profiles.
MicroRNAs (miRNAs) have been known to play an important role in several biological processes in both animals and plants. Although several tools for miRNA and target identification are available, the number of tools tailored towards plants is limited, and those that are available have specific functionality, lack graphical user interfaces, and restrict the number of input sequences. Large-scale computational identifications of miRNAs and/or targets of several plants have been also reported.
The prediction of novel pre-microRNA (miRNA) from genomic sequence has received considerable attention recently. However, the majority of studies have focused on the human genome. Previous studies have demonstrated that sensitivity (correctly detecting true miRNA) is sustained when human-trained methods are applied to other species, however they have failed to report the dramatic drop in specificity (the ability to correctly reject non-miRNA sequences) in non-human genomes.
RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences.
The most important means of identifying diseases before symptoms appear is through the discovery of disease-associated biomarkers. Recently, microRNAs (miRNAs) have become highly useful biomarkers of infectious, genetic and metabolic diseases in human but they have not been well studied in domestic animals. It is probable that many of the animal homologs of human disease-associated miRNAs may be involved in domestic animal diseases.
Recent advances in 'omic' technologies have created unprecedented opportunities for biological research, but current software and database resources are extremely fragmented. OMICtools is a manually curated metadatabase that provides an overview of more than 4400 web-accessible tools related to genomics, transcriptomics, proteomics and metabolomics. All tools have been classified by omic technologies (next-generation sequencing, microarray, mass spectrometry and nuclear magnetic resonance) associated with published evaluations of tool performance.
The explosion of next-generation sequencing data has spawned the design of new algorithms and software tools to provide efficient mapping for different read lengths and sequencing technologies. In particular, ABI's sequencer (SOLiD system) poses a big computational challenge with its capacity to produce very large amounts of data, and its unique strategy of encoding sequence data into color signals.
In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs) in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules.
The Atlantic salmon (Salmo salar) is a very valuable commercial salmonid species. As with other aquaculture species, intensive aquaculture of Atlantic salmon often faces disease problems especially in early life stages which can limit stable production of the species. 'Ssa miRNAs DB', a bioinformatics and manually curated database, aims at providing a comprehensive resource of microRNA in Altantic salmon, with a user friendly interface for a convenient retrieval of each entry by microRNA ID or target gene.
MicroRNAs (miRNAs) are a class of small RNAs that post-transcriptionally regulate gene expression in animals and plants. The recent rapid advancement in miRNA biology, including high-throughput sequencing of small RNA libraries, inspired the development of a bioinformatics software, miRAuto, which predicts putative miRNAs in model plant genomes computationally. Furthermore, miRAuto enables users to identify miRNAs in non-model plant species whose genomes have yet to be fully sequenced.
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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