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Record W2942934502 · doi:10.3390/genes10050333

Functional Proteomics of Nuclear Proteins in Tetrahymena thermophila: A Review

2019· review· en· W2942934502 on OpenAlexafffund
Alejandro Saettone, Syed Nabeel‐Shah, Jyoti Garg, Jean‐Philippe Lambert, Ronald E. Pearlman, Jeffrey Fillingham

Bibliographic record

VenueGenes · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtist diversity and phylogeny
Canadian institutionsUniversité LavalCanada Research ChairsCentre hospitalier universitaire de QuébecYork UniversityUniversity of TorontoToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsTetrahymenaBiologyProteomeNuclear poreChromatinModel organismProteomicsComputational biologyGenomeProtozoaCiliateGeneticsCell biologyCytoplasmGene

Abstract

fetched live from OpenAlex

Identification and characterization of protein complexes and interactomes has been essential to the understanding of fundamental nuclear processes including transcription, replication, recombination, and maintenance of genome stability. Despite significant progress in elucidation of nuclear proteomes and interactomes of organisms such as yeast and mammalian systems, progress in other models has lagged. Protists, including the alveolate ciliate protozoa with Tetrahymena thermophila as one of the most studied members of this group, have a unique nuclear biology, and nuclear dimorphism, with structurally and functionally distinct nuclei in a common cytoplasm. These features have been important in providing important insights about numerous fundamental nuclear processes. Here, we review the proteomic approaches that were historically used as well as those currently employed to take advantage of the unique biology of the ciliates, focusing on Tetrahymena, to address important questions and better understand nuclear processes including chromatin biology of eukaryotes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.793

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.276
Teacher spread0.228 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2019
Admission routes2
Has abstractyes

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