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Record W2767591791 · doi:10.1093/nar/gkx1043

MoonProt 2.0: an expansion and update of the moonlighting proteins database

2017· article· en· W2767591791 on OpenAlexaff
Chang Chen, Shadi Zabad, Haipeng Liu, Wangfei Wang, Constance J. Jeffery

Bibliographic record

VenueNucleic Acids Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyDatabaseProtein Data BankProtein methodsFunction (biology)Structural Classification of Proteins databaseComputational biologyProtein structure databaseSequence databaseBioinformaticsPeptide sequenceProtein structureComputer scienceGeneticsBiochemistryGene

Abstract

fetched live from OpenAlex

MoonProt 2.0 (http://moonlightingproteins.org) is an updated, comprehensive and open-access database storing expert-curated annotations for moonlighting proteins. Moonlighting proteins contain two or more physiologically relevant distinct functions performed by a single polypeptide chain. Here, we describe developments in the MoonProt website and database since our previous report in the Database Issue of Nucleic Acids Research. For this V 2.0 release, we expanded the number of proteins annotated to 370 and modified several dozen protein annotations with additional or updated information, including more links to protein structures in the Protein Data Bank, compared with the previous release. The new entries include more examples from humans and several model organisms, more proteins involved in disease, and proteins with different combinations of functions. The updated web interface includes a search function using BLAST to enable users to search the database for proteins that share amino acid sequence similarity with a protein of interest. The updated website also includes additional background information about moonlighting proteins and an expanded list of links to published articles about moonlighting proteins.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.040
GPT teacher head0.335
Teacher spread0.295 · 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 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

Citations114
Published2017
Admission routes1
Has abstractyes

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