1 - 12 of 12 results


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.


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.


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.


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.

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.