ArticleBMC bioinformatics2017
In silico prediction of lncRNA function using tissue specific and evolutionary conserved expression.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 56 citations in OpenAlex.
- The RBM14/CoAA-interacting, long intergenic non-coding RNA Paral1 regulates adipogenesis and coactivates the nuclear receptor PPARγ.Scientific reports · 2017Trial
- Aggressive serous ovarian cancer subtype defined by high centrality lncRNA profiles and master transcription factors.Scientific reports · 2025Article
- Review
- Review
- Dysregulated long non-coding RNA in Sjögren's disease impacts both interferon and adaptive immune responses.RMD open · 2022Article
- Organization of gene programs revealed by unsupervised analysis of diverse gene-trait associations.Nucleic acids research · 2022Article
- Designing libraries for pooled CRISPR functional screens of long noncoding RNAs.Mammalian genome : official journal of the International Mammalian Genome Society · 2022Review
- The Emerging Roles of Long Non-Coding RNAs in Intellectual Disability and Related Neurodevelopmental Disorders.International journal of molecular sciences · 2022Review
- Long Non-Coding RNA-Based Functional Prediction Reveals Novel Targets in Notch-Upregulated Ovarian Cancer.Cancers · 2022Article
- Identification of potential regulatory long non-coding RNA-associated competing endogenous RNA axes in periplaque regions in multiple sclerosis.Frontiers in genetics · 2022Article
- Transcriptomic profiling of Indian breast cancer patients revealed subtype-specific mRNA and lncRNA signatures.Frontiers in genetics · 2022Article
- Expression profiles and functional prediction of long non-coding RNAs LINC01133, ZEB1-AS1 and ABHD11-AS1 in the luminal subtype of breast cancer.Journal of translational medicine · 2021Article
- Long Non-coding RNAs as Promising Therapeutic Approach in Ischemic Stroke: a Comprehensive Review.Molecular neurobiology · 2021Review
- SP1 induced long non-coding RNA AGAP2-AS1 promotes cholangiocarcinoma proliferation via silencing of CDKN1A.Molecular medicine (Cambridge, Mass.) · 2021Article
- Pravastatin-induced changes in expression of long non-coding and coding RNAs in endothelial cells.Physiological reports · 2021Article
- Functional Prediction of Long Noncoding RNAs in Cutaneous Melanoma Using a Systems Biology Approach.Bioinformatics and biology insights · 2021Article
- Long non-coding RNA Gm15441 attenuates hepatic inflammasome activation in response to PPARA agonism and fasting.Nature communications · 2020Article
- Machine Learning Supports Long Noncoding RNAs as Expression Markers for Endometrial Carcinoma.BioMed research international · 2020Article
- Interference with the Cannabinoid Receptor CB1R Results in Miswiring of GnRH3 and AgRP1 Axons in Zebrafish Embryos.International journal of molecular sciences · 2019Article
- Survival analysis and functional annotation of long non-coding RNAs in lung adenocarcinoma.Journal of cellular and molecular medicine · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years long non coding RNAs (lncRNAs) have been the subject of increasing interest. Thanks to many recent functional studies, the existence of a large class of lncRNAs with potential regulatory functions is now widely accepted. Although an increasing number of lncRNAs is being characterized and shown to be involved in many biological processes, the functions of the vast majority lncRNA genes is still unknown. Therefore computational methods able to take advantage of the increasing amount of publicly available data to predict lncRNA functions could be very useful.
resultsSince coding genes are much better annotated than lncRNAs, we attempted to project known functional information regarding proteins onto non coding genes using the guilt by association principle: if a gene shows an expression profile that correlates with those of a set of coding genes involved in a given function, that gene is probably involved in the same function. We computed gene coexpression for 30 human tissues and 9 vertebrates and mined the resulting networks with a methodology inspired by the rank product algorithm used to identify differentially expressed genes. Using different types of reference data we can predict putative new annotations for thousands of lncRNAs and proteins, ranging from cellular localization to relevance for disease and cancer.
conclusionsNew function of coding genes and lncRNA can be profitably predicted using tissue specific coexpression, as well as expression of orthologous genes in different species. The data are available for download and through a user-friendly web interface at www.funcpred.com .
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.