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Record W1691146018 · doi:10.1186/1471-2105-7-305

Taking U out, with two nucleases?

2006· article· en· W1691146018 on OpenAlexaff
Shahzad I. Mian, Elizabeth A. Worthey, Reza Salavati

Bibliographic record

VenueBMC Bioinformatics · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA regulation and disease
Canadian institutionsMcGill University
FundersNational Institute of Allergy and Infectious DiseasesNational Institute on AgingNational Institutes of HealthU.S. Department of Energy
KeywordsTrypanosoma bruceiBiologyComputational biologySubfamilyRNA editingRNAFunction (biology)GeneticsProtein domainGene

Abstract

fetched live from OpenAlex

BACKGROUND: REX1 and REX2 are protein components of the RNA editing complex (the editosome) and function as exouridylylases. The exact roles of REX1 and REX2 in the editosome are unclear and the consequences of the presence of two related proteins are not fully understood. Here, a variety of computational studies were performed to enhance understanding of the structure and function of REX proteins in Trypanosoma and Leishmania species. RESULTS: Sequence analysis and homology modeling of the Endonuclease/Exonuclease/Phosphatase (EEP) domain at the C-terminus of REX1 and REX2 highlights a common active site shared by all EEP domains. Phylogenetic analysis indicates that REX proteins contain a distinct subfamily of EEP domains. Inspection of three-dimensional models of the EEP domain in Trypanosoma brucei REX1 and REX2, and Leishmania major REX1 suggests variations of previously characterized key residues likely to be important in catalysis and determining substrate specificity. CONCLUSION: We have identified features of the REX EEP domain that distinguish it from other family members and hence subfamily specific determinants of catalysis and substrate binding. The results provide specific guidance for experimental investigations about the role(s) of REX proteins in RNA editing.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.012
GPT teacher head0.245
Teacher spread0.233 · 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 designObservational
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

Citations9
Published2006
Admission routes1
Has abstractyes

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