ArticleGenome research2013
Functional transcriptomics in the post-ENCODE era.
Article in Genome research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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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.
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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.
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Who cites it
34 citing papers in PubMed.
- Pervasive non-triplet alternative splicing drives functional isoform diversity.Nature communications · 2026Article
- Housekeeping protein-coding genes interrogated with tissue and individual variations.Scientific reports · 2024Article
- Tissue-specific regulation of gene expression via unproductive splicing.Nucleic acids research · 2023Article
- Methods to Analyze the Non-Coding RNA Interactome-Recent Advances and Challenges.Frontiers in genetics · 2022Review
- Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells.Genome biology · 2021Article
- LncRNA HOTAIR: A Potential Prognostic Factor and Therapeutic Target in Human Cancers.Frontiers in oncology · 2021Review
- Long Non-Coding RNA Neighbor of BRCA1 Gene 2: A Crucial Regulator in Cancer Biology.Frontiers in oncology · 2021Review
- FuncPEP: A Database of Functional Peptides Encoded by Non-Coding RNAs.Non-coding RNA · 2020Article
- Discovery of high-confidence human protein-coding genes and exons by whole-genome PhyloCSF helps elucidate 118 GWAS loci.Genome research · 2019Article
- Integrative transcriptomic analysis suggests new autoregulatory splicing events coupled with nonsense-mediated mRNA decay.Nucleic acids research · 2019Article
- Machine Learning Classifiers for Endometriosis Using Transcriptomics and Methylomics Data.Frontiers in genetics · 2019Article
- Biological classification with RNA-seq data: Can alternatively spliced transcript expression enhance machine learning classifiers?RNA (New York, N.Y.) · 2018Article
- Inherited, not acquired, Gitelman syndrome in a patient with Sjögren's syndrome: importance of genetic testing to distinguish the two forms.CEN case reports · 2017Article
- Genome annotation for clinical genomic diagnostics: strengths and weaknesses.Genome medicine · 2017Review
- The state of play in higher eukaryote gene annotation.Nature reviews. Genetics · 2016Review
- Extension of human lncRNA transcripts by RACE coupled with long-read high-throughput sequencing (RACE-Seq).Nature communications · 2016Article
- Functional annotation of the vlinc class of non-coding RNAs using systems biology approach.Nucleic acids research · 2016Article
- Identifying and functionally characterizing tissue-specific and ubiquitously expressed human lncRNAs.Oncotarget · 2016Article
- Long non-coding RNAs display higher natural expression variation than protein-coding genes in healthy humans.Genome biology · 2016Article
- What is an RNA? A top layer for RNA classification.RNA biology · 2016Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The last decade has seen tremendous effort committed to the annotation of the human genome sequence, most notably perhaps in the form of the ENCODE project. One of the major findings of ENCODE, and other genome analysis projects, is that the human transcriptome is far larger and more complex than previously thought. This complexity manifests, for example, as alternative splicing within protein-coding genes, as well as in the discovery of thousands of long noncoding RNAs. It is also possible that significant numbers of human transcripts have not yet been described by annotation projects, while existing transcript models are frequently incomplete. The question as to what proportion of this complexity is truly functional remains open, however, and this ambiguity presents a serious challenge to genome scientists. In this article, we will discuss the current state of human transcriptome annotation, drawing on our experience gained in generating the GENCODE gene annotation set. We highlight the gaps in our knowledge of transcript functionality that remain, and consider the potential computational and experimental strategies that can be used to help close them. We propose that an understanding of the true overlap between transcriptional complexity and functionality will not be gained in the short term. However, significant steps toward obtaining this knowledge can now be taken by using an integrated strategy, combining all of the experimental resources at our disposal.
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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.