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Web-based interface portal for querying RBP-gene regulatory networks in specific cancer types. Users can select specific cancer types, input RBPs, genes or specific mutations of interest, the RBP-gene regulation or perturbed regulation by mutations will be returned. All datasets can be downloaded from the download page. Detailed instructions for using this resource can be found at the help page.
ImmLnc is a web-based resource for investigating the immune-related function of lncRNAs across cancer types. In this resource, the users can query the lncRNA-pathways, lncRNA-immune cell type's correlation, and cancer-related lncRNAs across 33 cancer types. The ImmLnc pipeline and the resulting data provided here are intended to serve as a valuable resource for understanding the lncRNA function and to further advance the identification of immunotherapy targets.
The lncSpA aims at providing the spatial atlas of expression for lncRNAs across normal and cancer tissues by 21230 RNA-seq samples, including 38 different normal tissues, 33 adult cancer types and 7 pediatric cancer types of the human body. TE lncRNAs in each individual tissues under either normal or cancer conditions (“TE” and “Cancer TE”), as well as cancer clinical related TE lncRNAs (“Clinical related TE”) are identified.
A systems-level dissection of lncRNA mediated TF-gene regulatory perturbations in cancer, also presented a valuable tool and resource for investigating the function of lncRNAs in cancer, greatly facilitating lncRNA-related biological discoveries and therapeutic intervention.
FACER (Functional Atlas of Chromatin Epigenetic Regulators) is a compilation of prioritized functional CRs across multiple cancer types, involving their specific functions, biological categories and their roles in cancers. FACER offers the search and download for basic information and multi-omics features of 640 functional CRs across 33 cancer types.
The landscape of the lncRNA transcriptome in human heart was summarized. We summarized all lncRNA transcripts from publicly available human transcriptome resources (156 heart samples and 210 samples from 29 other tissues) and systematically analysed all annotated and novel lncRNAs expressed in heart. A total of 7,485 lncRNAs whose expression was elevated in heart (HE lncRNAs) and 453 lncRNAs expressed in all 30 analysed tissues (EIA lncRNAs) were extracted.
A network-based framework to identify mutations that could mediate differential AS events in cancer. This model was built upon the idea that gene mutations with functional effects on AS exhibited their impact in the functional association networks. By applying this method to 33 types of cancer, we identified approximately 60–900 drivers that may determine differential AS events for each cancer type.
A framework-LncMod, for identifying the lncRNA modulator by integrating genome-wide gene expression profiles and transcription regulations. The proposed method takes four inputs: the gene expression profile dataset for lncRNA, TF and target genes, the context-specific TF-gene regulations. For each TF-gene regulations, we reported the lncRNA modulators along with their mode of action.
LncRNA Ontology aims to infer the functions of lncRNAs based on their chromatin states and expression patterns. A total of 9 histone modification marks (H2A.Z, H3K4me1/2/3, H3K9ac, H3K27ac, H3K9me3, H3K27me3 and H3K36me3) associated with transcription start sites (TSSs) of lncRNAs and mRNAs in thirteen different human cell types and their expression were considered. We employed the nearest shrunken centroid algorithm to build models for each Gene Ontology term using the 10 profiles of mRNAs, and demonstrated that incorporating chromation states with transcriptional feature yields improved gene function predictions over models training from individual datasets. By applying our chromatin-based model, probable functions for more than 97% human lncRNAs were predicted.
Here, we assembled and functionally characterized a consensus lncRNA transcriptome by curating hundreds of RNA-seq datasets across normal human tissues from 16 independent studies. As results, besides the strong tissue-specificity of lncRNA transcriptome, a general ubiquitously expressed feature is delineated. In total, 1,184 UE lncRNAs and 2,583 TS lncRNAs are further identified.
Pan-cancer associated ceRNA database (Pan-ceRNADB) is offered to the public as a freely available resource to investigate mRNA related ceRNA-ceRNA landscape and significance across 20 major cancer types. Cross-talk between competitive endogenous RNAs (ceRNAs) through shared miRNAs represents a novel layer of gene regulation that plays important roles in the physiology and development of cancers. Here, we constructed the mRNA related ceRNA-ceRNA interaction landscape across 20 cancer types by systematically analyzing molecular profiles of 5,203 tumours and miRNA regulations.
Here, we describe a practical and user-friendly web interface called Co-LncRNA, a web-based computational tool that allows users to identify GO annotations and KEGG pathways that may be affected by co-expressed protein-coding genes (CEGs) of a single or multiple lncRNAs. The current release of Co-LncRNA includes high-throughput RNA sequencing data involved in 28 human tissues/cell lines including 6,560 individuals (29,012 samples) from 241 datasets.
The VmiReg database is an integrated resource for viral miRNAs whose natural host is mainly Homo sapiens, and is expected to provide a convenient platform for researchers to get viral miRNA-related information.
PD_NGSAtlas aims at providing a reference resource combining both next-generation sequencing epigenomic and transcriptomic data and quantitative analysis of epigenetic and transcriptional alternations involved in psychiatric disorders. The current release of PD_NGSAtlas contains 43 methylation profiles and 37 expression profiles detected by MeDIP-seq and RNA-Seq respectively, in peripheral blood and two distinct brain regions of SZ, BP and non-psychiatric control individuals. In addition to these data generated in-house, we have and will continue to include published DNA methylation and gene expression data from other research groups with the focus on psychiatric disorders. The website offers open and easy access to obtain expression and methylation levels of interesting genes and tools to facilitate the comprehensive annotation and discovery of dysfunctional genes or functional regions. A genome browser is developed to provide integrative and detailed views of multidimensional data under a given genomic context, which can help researchers to better understand pathophysiological mechanism from epigenetic and transcriptional views.
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