MétaCan
Menu
Back to cohort
Record W2411174941 · doi:10.5692/clinicalneurol.53.957

The world of functional RNA

2013· review· en· W2411174941 on OpenAlexaff
Hiromi Okada, Yoshihide Hayashizaki

Bibliographic record

VenueRinsho Shinkeigaku · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer-related molecular mechanisms research
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsRNANon-coding RNADNAComputational biologyBiologyGeneticsGene

Abstract

fetched live from OpenAlex

The development of next-generation sequences has brought not only high-throughput sequencing but also new possibilities for various kinds of analysis methods of genetic information. Dr. Hayashizaki et al. developed new technologies to construct the full-length cDNA library and applied them to high-throughput sequencing technologies for large-scale transcriptome analysis. These analysis results overturned the conventional assumption the 2% of the genome is transcribed by showing that 70% or more of the genome is transcribed as RNA through FANTOM activities which was founded in 2000 on their initiative. Further, the existence of 23,000 non-protein coding RNAs was confirmed. These new findings redefine the central dogma into a new picture containing new interaction cascade and the unexpected complexity of combined omics. The neo central dogma shows that there are three types of final products derived from genes; long ncRNA, small ncRNA, and protein. They play essential roles by forming complexes with each other to maintain life. Long ncRNA and small ncRNA play a role as a ligand with sequence information. Long ncRNA and protein play a role as a functional molecule. Here, I would like to introduce the neo central dogma concept and some of the mechanisms of ncRNAs.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.048
GPT teacher head0.338
Teacher spread0.290 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueRinsho ShinkeigakuSame topicCancer-related molecular mechanisms researchFrench-language works237,207