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Record W2081375228 · doi:10.1016/j.cell.2014.10.050

A Proteome-Scale Map of the Human Interactome Network

2014· article· en· W2081375228 on OpenAlexafffund
Thomas Rolland, Murat Taşan, Benoît Charloteaux, Samuel Pevzner, Quan Zhong, Nidhi Sahni, S. Stephen Yi, Irma Lemmens, Celia Fontanillo, Roberto Mosca, Atanas Kamburov, Susan Dina Ghiassian, Xinping Yang, Lila Ghamsari, Dawit Balcha, Bridget E. Begg, Pascal Falter‐Braun, Marc Brehme, Martin Broly, Anne‐Ruxandra Carvunis, Dan Convery-Zupan, Roser Corominas, Jasmin Coulombe‐Huntington, Elizabeth Dann, Matija Dreze, Amélie Dricot, Changyu Fan, Eric A. Franzosa, Fana Gebreab, Bryan J. Gutierrez, Madeleine F. Hardy, Mike Jin, Shuli Kang, Ruth Kiros, Guan Ning Lin, Katja Luck, Andrew MacWilliams, Jörg Menche, Ryan R. Murray, Alexandre Palagi, Matthew M. Poulin, Xavier Rambout, John Rasla, Patrick Reichert, Viviana Romero, Elien Ruyssinck, Julie M. Sahalie, Annemarie Scholz, Akash Shah, Amitabh Sharma, Yun Shen, Kerstin Spirohn, Stanley Tam, Alexander O. Tejeda, Shelly A. Wanamaker, Jean‐Claude Twizere, Kerwin Vega, Jennifer Walsh, Michael E. Cusick, Yu Xia, Albert-Ĺaszló Barabási, Lilia M. Iakoucheva, Patrick Aloy, Javier De Las Rivas, Jan Tavernier, Michael A. Calderwood, David E. Hill, Tong Hao, Frederick P. Roth, Marc Vidal

Bibliographic record

VenueCell · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBioinformatics and Genomic Networks
Canadian institutionsCanadian Institute for Advanced ResearchMcGill UniversityLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of TorontoOntario Institute for Cancer Research
FundersNational Cancer InstituteNational Human Genome Research InstituteNational Institute of Mental HealthNational Heart, Lung, and Blood InstituteKrembil FoundationFonds Wetenschappelijk OnderzoekNatural Sciences and Engineering Research Council of CanadaVlaamse regeringUniversiteit GentEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEuropean CommissionAvon Foundation for WomenNational Institutes of HealthNational Science Foundation
KeywordsInteractomeBiologyInterconnectivityComputational biologyHuman proteome projectProteomeHuman geneticsGenomeGeneticsProteomicsGeneComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.004
GPT teacher head0.201
Teacher spread0.197 · 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 designSimulation or modeling
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

Citations1,458
Published2014
Admission routes2
Has abstractno

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