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Record W2748577514 · doi:10.1038/nbt.3947

An integrated expression atlas of miRNAs and their promoters in human and mouse

2017· article· en· W2748577514 on OpenAlexaff
Derek de Rie, Imad Abugessaisa, Tanvir Alam, Peter Arner, Haitham Ashoor, Gaby Åström, Magda Babina, Nicolas Bertin, A. Maxwell Burroughs, Ailsa J Carlisle, Carsten O. Daub, Michael Detmar, Ruslan Deviatiiarov, Alexandre Fort, Claudia Gebhard, Dan Goldowitz, Sven Guhl, Thomas J Ha, Jayson Harshbarger, Akira Hasegawa, Kosuke Hashimoto, Meenhard Herlyn, Peter Heutink, Kelly J Hitchens, Chung-Chau Hon, Edward Huang, Yuri Ishizu, Chieko Kai, Takeya Kasukawa, Peter S Klinken, Timo Lassmann, Charles‐Henri Lecellier, Weon-Ju Lee, Marina Lizio, Vsevolod J. Makeev, Anthony Mathelier, Yulia A. Medvedeva, Niklas Mejhert, Chris Mungall, Shohei Noma, Mitsuhiro Ohshima, Mariko Okada, Helena Persson, Patrizia Rizzu, Filip Roudnicky, Pål Sætrom, Hiroki Sato, Jessica Severin, Jay W. Shin, Rolf Swoboda, Hiroshi Tarui, Hiroo Toyoda, Kristoffer Vitting‐Seerup, Louise N Winteringham, Yoko Yamaguchi, Kayoko Yasuzawa, Misako Yoneda, Noriko Yumoto, Susan E. Zabierowski, Peter Zhang, Christine A. Wells, Kim Summers, Hideya Kawaji, Albin Sandelin, Michael Rehli, Yoshihide Hayashizaki, Piero Carninci, Alistair R. R. Forrest, Michiel de Hoon

Bibliographic record

VenueNature Biotechnology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicroRNA in disease regulation
Canadian institutionsChild and Family Research InstituteUniversity of British Columbia
FundersRIKENBiotechnology and Biological Sciences Research CouncilNovo Nordisk FondenRussian Science FoundationNovo NordiskMinistry of Education, Culture, Sports, Science and TechnologyNational Cancer InstituteH. Lundbeck A/SLundbeckfondenConquer Cancer Foundation
KeywordsPromotermicroRNAAtlas (anatomy)BiologyComputational biologyGene expressionGeneticsGeneAnatomy

Abstract

fetched live from OpenAlex

MicroRNAs (miRNAs) are short non-coding RNAs with key roles in cellular regulation. As part of the fifth edition of the Functional Annotation of Mammalian Genome (FANTOM5) project, we created an integrated expression atlas of miRNAs and their promoters by deep-sequencing 492 short RNA (sRNA) libraries, with matching Cap Analysis Gene Expression (CAGE) data, from 396 human and 47 mouse RNA samples. Promoters were identified for 1,357 human and 804 mouse miRNAs and showed strong sequence conservation between species. We also found that primary and mature miRNA expression levels were correlated, allowing us to use the primary miRNA measurements as a proxy for mature miRNA levels in a total of 1,829 human and 1,029 mouse CAGE libraries. We thus provide a broad atlas of miRNA expression and promoters in primary mammalian cells, establishing a foundation for detailed analysis of miRNA expression patterns and transcriptional control regions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.259
Teacher spread0.254 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations606
Published2017
Admission routes1
Has abstractno

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