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1、Tailor
A computational framework driven by an efficient and accurate aligner specifically designed for capturing the tailing events directly from the alignments without extensive post-processing. The performance of Tailor was fully tested and compared favorably with other general-purpose aligners using both simulated and real datasets for tailing analysis
(Chou et al., 2015) Tailor: a computational framework for detecting non-templated tailing of small silencing RNAs. Nucleic acids research.
2、MicroRazerS
A tool optimized for mapping short RNAs onto a reference genome
(Emde et al., 2010) MicroRazerS: rapid alignment of small RNA reads. Bioinformatics.
3、SHRiMP2
A software package for aligning genomic reads against a target genome.
(David et al., 2011) SHRiMP2: sensitive yet practical SHort Read Mapping. Bioinformatics.
4、 miRBase
A tool for ranking novel miRNAs that have been predicted from next-generation sequencing (NGS) data. Since in later miRBase versions the increase of miRNAs derived from NGS data and prediction tools is noticeable, we provide with our tool a way to compare user-defined novel miRNAs to e.g. early miRBase versions and rank the user input miRNAs according to their distance from the distribution of the selected reference miRBase versions.
(Backes et al., 2015) Prioritizing and selecting likely novel miRNAs from NGS data. Nucleic acids research.
5、omiRas
A Web service for the analysis of ncRNA datasets derived from Illumina sRNA-Seq experiments. Starting with raw sequencing data, omiRas offers an efficient way to analyze differential expression of ncRNAs between two groups and to assign functions to differentially expressed miRNAs. MiRNA–mRNA interaction databases allow the user to construct networks of interesting miRNAs and mRNAs to identify miRNAs with implications in the development of differential gene signatures.
(Muller et al., 2013) omiRas: a Web server for differential expression analysis of miRNAs derived from small RNA-Seq data. Bioinformatics.
6、LimiTT
A web-based pipeline which can automatically identify and link validated miRNA target interactions (MTIs) from extensive lists of miRNAs and target genes in batch mode, even if the provided data is not species specific
(Bayer et al., 2016) LimiTT: link miRNAs to targets. BMC bioinformatics
7、miRNA Digger
A pipeline for large-scale identification of miRNA candidates through genome-wide screening of cleavage signals based on degradome sequencing data.
(Yu et al., 2016) miRNA Digger: a comprehensive pipeline for genome-wide novel miRNA mining. Sci Rep.
8、miRA
miRA is a new tool to identify miRNA precursors in plants, allowing for heterogeneous and complex precursor populations.
(Evers et al. 2015) miRA: adaptable novel miRNA identification in plants using small RNA sequencing data. BMC bioinformatics
9、miR-isomiRExp
A web platform to analyze expression pattern of miRNA at the miRNA/isomiR levels. miR-isomiRExp is based on the biological characteristics of miRNA and isomiR, it provides insights into tracking miRNA/isomiR maturation and processing mechanisms, and reveals functional characteristics of miRNA/isomiR.
(Guo et al., 2016) miR-isomiRExp: a web-server for the analysis of expression of miRNA at the miRNA/isomiR levels. Scientific reports.
10、miReader
Detects mature miRNAs directly from next generation sequencing read data, without any need of reference/genomic sequences. miReader was tested over wide range of species, and the presented approach achieved high accuracy for all the target species. Using the same approach, 21 novel mature miRNA duplex candidates were identified for a plant species whose genome has not been sequenced yet and there is negligible miRNA data reported for this species in miRBase. This has clearly demonstrated clearly that in spite of unavailability of genomic sequences, the presented tool, miReader, could accurately identify the mature miRNAs directly from small RNA sequencing data
(Jha and Shankar, 2013) miReader: Discovering Novel miRNAs in Species without Sequenced Genome. PloS one.
11、miRPlant
An integrated package for identification of plant miRNA from RNA sequencing data. miRPlant visualizes novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. This software can be easily used by biologists with limited bioinformatics skills, with possibility to use other species. It is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs
(An et al., 2014) miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data. BMC bioinformatics.
12、isomiR-SEA
Provides users with a complete and accurate picture of the miRNAs, isomiRs and conserved miRNA:mRNA interaction sites characterizing the tissue under examination
(Urgese et al., 2016) isomiR-SEA: an RNA-Seq analysis tool for miRNAs/isomiRs expression level profiling and miRNA-mRNA interaction sites evaluation. BMC bioinformatics.
13、miRDeep
An integrated application tool for miRNA identification from RNA sequencing data.
(An et al., 2013) miRDeep*: an integrated application tool for miRNA identification from RNA sequencing data. Nucleic acids research.
14、miRPlant
An integrated package for identification of plant miRNA from RNA sequencing data. miRPlant visualizes novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. This software can be easily used by biologists with limited bioinformatics skills, with possibility to use other species. It is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs.
(An et al., 2014) miRPlant: an integrated tool for identification of plant miRNA from RNA sequencing data. BMC bioinformatics.
15、miRDeep-P
A computational tool for analyzing the microRNA (miRNA) transcriptome in plants.
(Yang and Li, 2011) miRDeep-P: a computational tool for analyzing the microRNA transcriptome in plants. Bioinformatics.
1、SCnorm
A quantile regression method for accurate and efficient normalization of scRNA-seq data. SCnorm uses quantile regression to estimate the dependence of read counts on sequencing depth for every gene. Genes with similar dependence are then grouped, and a second quantile regression is used to estimate scale factors within each group. SCnorm does not require spike-ins, performance may be improved if good spike-ins are available.
(Bacher et al., 2016) SCnorm: A quantile-regression based approach for robust normalization of single-cell RNA-seq data. bioRxiv.
２、BASIC
Allows investigators to use scRNA-seq for assembling BCR sequences at single cell resolution. BASIC performs semi-de novo assembly in two stages: (i) uses known constant and variable regions to identify anchor sequences, and (ii) uses these anchors to guide the de novo assembly of the BCR. BASIC can help couple gene expression information from scRNA-seq with immune repertoire, and facilitate studies between B-cell receptor features, clonality, differentiation and transcriptional programming at single cell resolution.
(Canzar et al., 2016) BASIC: BCR assembly from single cells. Bioinformatics.
３、SPRING
A tool for uncovering high-dimensional structure in single-cell gene expression data. From a table of gene expression measurement for single-cells, SPRING is able to build a k-nearest neighbor (knn) graph and display the graph using a force-directed layout algorithm that renders a real-time simulation in an interactive viewing window. SPRING offers an open-ended data exploration, including interactive discovery of markers genes, genes expression comparison between different subpopulations and selection tools for isolating subpopulations of interest.
(Weinreb et al., 2016) SPRING: a kinetic interface for visualizing high dimensional single-cell expression data. bioRxiv.
４、SCODE
An efficient regulatory network interference algorithm from single-cell RNA-Sep during differentiation. SCODE is an algorithm interfering the regulatory networks, based on ordinary differential equations. SCODE uses a small number of factors to reconstruct expression dynamics, which results in a marked reduction of time complexity. This algorithm provides an approach for single-cell differentiation analysis and others studies using simulation
(Matsumoto et al., 2016) SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation. bioRxiv.
１、IRNdb
Combines microRNA, PIWI-interacting RNAs, and long non-coding RNA information with immunologically relevant target genes. IRNdb is intended to advance research on the influence of ncRNAs on immunological processes. IRNdb contains information for mouse as it is often used as a model organism for immunological research purposes. We integrated data on predicted and experimentally supported ncRNA-target interactions, ncRNA and gene annotations, biological pathways and processes and experimental data in a uniform format with a user-friendly web interface.
(Denisenko et al., 2016) IRNdb: the database of immunologically relevant non-coding RNAs. Database.
２、 LncRBase
A comprehensive database for long noncoding RNA (lncRNA) in Human and Mouse. LncRBase hosts information on basic lncRNA transcript features, with additional details on genomic location, overlapping small noncoding RNAs, associated Repeat Elements, associated imprinted genes, and lncRNA promoter information. Users can also search for microarray probes mapped to specific lncRNAs and associated disease information as well as search for lncRNA expression in a wide range of tissues
(Chakraborty et al., 2014) LncRBase: an enriched resource for lncRNA information. PLOS One.
３、ncFANs
A user-friendly web interface for functional annotation of human and mouse lncRNAs. ncFANs, on the basis of the re-annotated Affymetrix microarray data, provides two alternative strategies for lncRNA functional annotation: one utilizing three aspects of a coding-non-coding gene co-expression (CNC) network, the other identifying condition-related differentially expressed lncRNAs. ncFANs introduces a highly efficient way of re-using the abundant pre-existing microarray data. It includes re-annotated CDF files for human and mouse Affymetrix microarrays.
(Liao et al., 2011) ncFANs: a web server for functional annotation of long non-coding RNAs. Nucleic Acids Research.
４、NSDNA
manually curated database that provides comprehensive experimentally supported associations about nervous system diseases (NSDs) and noncoding RNAs (ncRNAs). NSDNA database documents 24713 associations between 142 NSDs and 8593 ncRNAs in 11 species, curated from more than 1300 articles. This database provides a user-friendly interface for browsing and searching and allows for data downloading flexibility. In addition, NSDNA offers a submission page for researchers to submit novel NSD-ncRNA associations. It represents a useful and valuable resource for researchers who seek to understand the functions and molecular mechanisms of ncRNA involved in NSDs.
(Wang et al., 2016) NSDNA: a manually curated database of experimentally supported ncRNAs associated with nervous system diseases. Nucleic Acids Research.
５、PLNlncRbase
Provides detailed information for experimentally identified plant lncRNAs. In the current version, PLNlncRbase has manually collected data from nearly 200 published literature, covering a total of 1187 plant lncRNAs in 43 plant species. The user can retrieve plant lncRNA entries from a well-organized interface through a keyword search by using the name of plant species or a lncRNA identifier. Each entry upon a query will be returned with detailed information for a specific plant lncRNA, including the species name, a lncRNA identifier, a brief description of the potential biological role, the lncRNA sequence, the lncRNA classification, an expression pattern of the lncRNA, the tissue/developmental stage/condition for lncRNA expression, the detection method for lncRNA expression, a reference literature, and the potential target gene(s) of the lncRNA extracted from the original reference.
(Xuan et al., 2015) PLNlncRbase: A resource for experimentally identified lncRNAs in plants. Gene.
６、 LNCediting
A database of comprehensive information about Adenosine-to-Inosine editing sites in long non-coding RNAs (lncRNAs) across human, rhesus, mouse, and fly, to explore their potential functions. LNCediting contains editing sites in lncRNAs, structure change by editing and the binding sites of lncRNA:miRNA which may be impacted by editing sites. LNCediting provides customized tools to predict functional effects of novel editing sites in lncRNAs.
(Gong et al., 2016) LNCediting: a database for functional effects of RNA editing in lncRNAs. Nucleic Acids Research.
７、PLEK
PLEK (predictor of long non-coding RNAs and messenger RNAs based on k-mer scheme), which uses an improved computational pipeline based on k-mer and support vector machine (SVM) to distinguish long non-coding RNAs (lncRNAs) from messenger RNAs (mRNAs).
(Li et al., 2014) PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme. BMC bioinformatics,
Yotsukura S, Hancock T, Natsume-Kitatani Y, et al. Computational recognition for long non-coding RNA (lncRNA): Software and databases[J]. Briefings in bioinformatics, 2016: bbv114.
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