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Record W639841747 · doi:10.1139/o08-006

Steps towards a repertoire of comprehensive maps of human protein interaction networks: the Human Proteotheque Initiative (HuPI)This paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process.

2008· review· en· W639841747 on OpenAlexafffundvenue
Benoit Coulombe, Mathieu Blanchette, Celia Jerónimo

Bibliographic record

VenueBiochemistry and Cell Biology · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsMcGill UniversityUniversité de MontréalMontreal Clinical Research Institute
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchGénome QuébecGenome Canada
KeywordsRepertoireSelection (genetic algorithm)Computational biologyMultidisciplinary approachComputer scienceHuman diseaseHuman proteinsProtein Interaction NetworksPipeline (software)Process (computing)Data scienceWeb siteProtein–protein interactionBiologyWorld Wide WebArtificial intelligenceThe InternetGeneticsGeneSociology

Abstract

fetched live from OpenAlex

Defining human protein interaction networks has become essential to develop an overall, systems-based understanding of the molecular events that sustain cell growth in normal and disease conditions. To characterize protein interaction networks from human cells, we have undertaken the development of a systematic, unbiased technology pipeline that couples experimental and computational approaches. This discovery engine is central to the Human Proteotheque Initiative (HuPI), a multidisciplinary project aimed at building a repertoire of comprehensive maps of human protein interaction networks, the Human Proteotheque. The information contained in the Proteotheque is made publicly available through an interactive web site that can be consulted to visualize some of the fundamental molecular connections formed in human cells and to determine putative functions of previously uncharacterized proteins based on guilt by association. The process governing the evolution of HuPI towards becoming a repository of accurate and complete protein interaction maps is described.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.031
GPT teacher head0.294
Teacher spread0.263 · 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

Labeled directly by 2 models reading the full record.

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

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Other design
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

Citations5
Published2008
Admission routes3
Has abstractyes

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