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A comprehensive regulatory network resource for human long non-coding RNAs (lncRNAs) and cancer genes. LnCaNet contains the pre-computed 8,494,907 significant co-expression pairs of 9641 lncRNAs and 2544 well-classified cancer genes in 2922 matched TCGA samples. In detail, we integrated 10 cancer gene lists from public database and calculate the co-expression with all the lncRNAs in 11 TCGA cancer types separately. Based on the resulted 110 co-expression networks, we identified 17 common regulatory pairs related to extracellular space shared in 11 cancers. We expect LnCaNet will enable researcher to explore lncRNA expression pattern, their affected cancer genes and pathways, biological significance in the context of specific cancer types and other useful annotation related to particular kind of lncRNA-cancer gene interaction.

EVLncRNAs / Experimentally Validated lncRNAs

Provides all species and covers functional and disease-specific roles for all long non-coding RNAs (lncRNAs) validated. EVLncRNAs contains about 1543 lncRNAs from 77 species along with their annotated functions, interaction partners and relevant diseases. The database allows users to submit novel experimentally validated lncRNAs and related diseases or associated components. It can be searched by any keywords, such as lncRNA name, alias, disease name, experimental methods, associated components and level of interaction.


A manually curated database of cancer-associated long non-coding RNAs (lncRNAs) with experimental support that aims to provide a high-quality and integrated resource for exploring lncRNA deregulation in various human cancers. The Lnc2Cancer database contains 1057 manually curated associations between 531 lncRNAs and 86 human cancers. Each association includes lncRNA and cancer name, the lncRNA expression pattern, experimental techniques, a brief functional description, the original reference and additional annotation information. Lnc2Cancer provides a user-friendly interface to conveniently browse, retrieve and download data. Lnc2Cancer also offers a submission page for researchers to submit newly validated lncRNA-cancer associations.


Allows the exploration of non-coding RNAs (ncRNAs) with oncogenic potential in human cancers. oncoNcRNA characterizes the somatic copy number alterations (SCNAs) of over 58,000 long non-coding RNAs (lncRNAs), 34,000 piwi-interacting RNAs (piRNAs), 2700 microRNAs (miRNAs), 600 transfer RNAs (tRNAs) and 400 small nucleolar RNAs (snoRNAs) in 64 human cancer types. It enables researchers to rapidly and intuitively analyze the oncogenic potential of ncRNAs of interest. Indeed, we have discovered a large number of ncRNAs which are frequently amplified or deleted within and across tumor types.


A tool to explore and to compare the expression profiles of conserved loci among various tissues in three organisms. Conversed loci are pairs of adjacent homologous protein-coding genes shared between one or more species. Expression profiles are based on RNA-seq data from many sources to derive tissue enrichment or specificity. Classifications of transcripts are based on the latest release of ENSEMBL, which will be updated in a timely manner. In addition to protein-coding genes, expression profiles of yet-to-be-characterized long non-coding RNAs (lncRNAs) are included.

TANRIC / The Atlas of Noncoding RNAs in Cancer

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A user-friendly, open-access web resource for interactive exploration of long non-coding RNAs (lncRNAs) in cancer. TANRIC characterizes the expression profiles of lncRNAs in large patient cohorts of 20 cancer types, including TCGA and independent datasets (>8,000 samples overall). TANRIC has several unique features (Table 2): (i) It provides extensive, intuitive, and interactive analyses on lncRNAs of interest for their interactions with other TCGA genomic/proteomic/epigenomic and clinical data types, both within a tumor type and across tumor types; (ii) it enables users to query expression profiles of user-defined lncRNAs quickly; (iii) it includes RNA-seq data from well-characterized cell lines and other large, non-TCGA patient cohorts, thereby allowing users to validate a pattern of interest or identify model cell lines for experimental characterization.


Allows users to explore disease associations and non-coding RNAs (ncRNA) function from the perspective of disease similarity. DincRNA is a bioinformatics resource for disease similarity calculation and non-coding RNA functional analysis that provides web pages for users to query disease similarity score, ncRNA functional similarity score, and ncRNA-disease prioritization score. It also includes a search engine to query entities involving disease names, DOIDs, long non-coding RNA (lncRNA) symbols and microRNA (miRNA) symbols, and a batch processing function.

DLREFD / Disease Related LncRNAEnvironmental Factor interaction Database

Contains experimentally supported interactions among lncRNAs, Environmental factors (EFs) and phenotypes. DLREFD offers an overview of the relationship between lnRNAs and EFs. It provides useful information for the diagnosis and prevention of diseases related to both genetic and EFs. This database has permitted identification of new disease indications for Food and Drug Administration (FDA)-approved drugs, which is named drug repositioning.


Allows users to search for the prioritization scores of disease-lncRNA associations. lncRNADis is a database for querying prioritization scores of lncRNA-disease pairs. Users can choose between several methods for prioritization: SemFunSim_PBPA_RWR, Resnik_PBPA_RWR, Wang_PBPA_RWR, PSB_PBPA_RWR, Lin _PBPA_RWR, SemFunSim_PBPM_RWR, Resnik_PBPM_RWR, Wang_PBPM_RWR, PSB_PBPM_RWR, Lin _PBPM_RWR. lncRNADis is part of DincRNA, a bioinformatics resource for disease similarity calculation and non-coding RNA functional investigation.