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Record W7145640602

翻訳動態の複合的解析はAUG類似開始コドンにおける翻訳開始のeIF2依存性を明らかにする

2022· dissertation· en· W7145640602 on OpenAlexfundno aff
Kazuya Ichihara

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2022
Typedissertation
Languageen
FieldEngineering
TopicMilitary Technology and Strategies
Canadian institutionsnot available
FundersInstitute of GeneticsJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and Technology
Keywordsnot available
DOInot available

Abstract

fetched live from OpenAlex

Although ribosome-profiling and translation initiation sequencing (TI-seq) analyses have identified many noncanonical initiation codons, the precise detection of translation initiation sites (TISs) remains a challenge, mainly because of experimental artifacts of such analyses.Here, we describe a new method, TISCA (TIS detection by translation Complex Analysis), for the accurate identification of TISs.TISCA proved to be more reliable for TIS detection compared with existing tools, and it identified a substantial number of near-cognate codons in Kozaklike sequence contexts.Analysis of proteomics data revealed the presence of methionine at the NH 2terminus of most proteins derived from near-cognate initiation codons.Although eukaryotic initiation factor 2 (eIF2), eIF2A and eIF2D have previously been shown to contribute to translation initiation at nearcognate codons, we found that most noncanonical initiation events are most probably dependent on eIF2, consistent with the initial amino acid being methionine.Comprehensive identification of TISs by TISCA should facilitate characterization of the mechanism of noncanonical initiation.

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)0.005
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.061
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0030.001
Scholarly communication0.0090.009
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0610.023

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 head0.008
GPT teacher head0.236
Teacher spread0.227 · 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

Citations0
Published2022
Admission routes1
Has abstractno

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