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FEELnc / FlExible Extraction of LncRNAs
An alignment-free program which accurately annotates lncRNAs based on a Random Forest model trained with general features such as multi k-mer frequencies and relaxed open reading frames. Benchmarking versus five state-of-art tools shows that FEELnc achieves similar or better classification performance on GENCODE and NONCODE datasets. FEELnc also provides several specific modules that enable to fine-tune classification accuracy, to formalize the annotation of lncRNA classes and to annotate lncRNAs even in the absence of training set of noncoding RNAs.
LncFunNet / lncRNA Functional inference through integrated Network
Provides an approach dedicated to the forecasting, ranking and annotation of functional long non-coding RNAs (lncRNAs). LncFunNet supplies an algorithm that exploits throughput sequencing data and the gene network which is derived from it. It intends to furnish a computational framework highlighting and assessing the functional importance of newly discovered long non-coding RNAs (lncRNAs) in various biological systems.
A web app for predicting the interaction between long noncoding RNAs and proteins. By coding RNA and protein sequences into vectors, a matrix multiplication is used to give score to each RNA-protein pair. This score can be the measurement of interactions between the RNA-protein pair. Comparing to existing approaches, this method shortens the time for training matrix. It also theoretically guarantees the results to be the best solution. The method has shown good ability to discriminate interacting/non-interacting RNA-protein pairs and to predict the RNA-protein interaction within a given complex.
An online portal for systematically annotating newly identified human lncRNAs. AnnoLnc offers a full spectrum of annotations covering genomic location, RNA secondary structure, expression, transcriptional regulation, miRNA interaction, protein interaction, genetic association and evolution, as well as an abstraction-based text summary and various intuitive figures to help biologists quickly grasp the essentials. In addition to an intuitive and mobile-friendly Web interactive design, AnnoLnc supports batch analysis and provides JSON-based Web Service APIs for programmatic analysis.
Classifies protein coding and long non-coding RNA (lncRNA) transcripts using support vector machine (SVM). lncRScan-SVM is a python package for lncRNA prediction that aims at classifying PCTs and LNCTs. The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.
TERIUS / Translationdependent Ensemble classifier with RIbosome and UPF1 association Score
Deletes false lncRNA annotations. TERIUS starts by calculating the ribosome periodicity score (RPS) and separating coding transcripts. It then determines the 3’UTR-specific association with regulator of nonsense transcripts 1 (UPF1) association score (UAS) that detects invalid lncRNAs. This tool evaluates the protein coding potential per input transcripts with ribosome profiling data. It is useful for finding protein-coding transcripts and possible 3’UTR fragments.
Allows identification and annotations of human long non-coding RNAs. Co-LncRNA is a web application allowing users to study gene ontology (GO) annotations and KEGG pathways. It uses genome-scale bio-molecular interactions and expression correlation to better understand the potential function of long non-coding RNAs (lncRNAs). This tool offers possibility for users to upload their own lncRNA and protein-coding gene expression profiles to investigate the lncRNA combinatorial effects.
A comprehensive pipeline for computationally screening putative long non-coding RNA (lncRNA) transcripts over large multimodal datasets. lncRNA-screen main objective is to facilitate the computational discovery of lncRNA candidates to be further examined by functional experiments. lncRNA-screen provides a fully automated easy-to-run pipeline which performs data download, RNA-seq alignment, assembly, quality assessment, transcript filtration, novel lncRNA identification, coding potential estimation, expression level quantification, histone mark enrichment profile integration, differential expression analysis, annotation with other type of segmented data (copy number variations (CNVs), single nucleotide polymorphisms (SNPs), Hi-C, etc.) and visualization. Importantly, lncRNA-screen generates an interactive report summarizing all interesting lncRNA features including genome browser snapshots and lncRNA-mRNA interactions based on Hi-C data. In summary, lncRNA-screen pipeline provides a comprehensive solution for lncRNA discovery and an intuitive interactive report for identifying promising lncRNA candidates.
ncFANs / non-coding RNA Function ANnotation server
Annotates human and mouse long non-coding RNA (lncRNA). 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.
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