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Record W4307840280 · doi:10.1021/acs.jproteome.2c00498

The 2022 Report on the Human Proteome from the HUPO Human Proteome Project

2022· review· en· W4307840280 on OpenAlexafffund
Gilbert S. Omenn, Lydie Lane, Christopher M. Overall, Charles Pineau, Nicolle H. Packer, Ileana M. Cristea, Cecilia Lindskog, Susan T. Weintraub, Sandra Orchard, Michael H. A. Roehrl, Edouard C. Nice, Siqi Liu, Nuno Bandeira, Yu‐Ju Chen, Tiannan Guo, Ruedi Aebersold, Robert L. Moritz, Eric W. Deutsch

Bibliographic record

VenueJournal of Proteome Research · 2022
Typereview
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersU.S. National Library of MedicineNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesDivision of Biological InfrastructureNational Institute of General Medical SciencesNational Cancer InstituteNIH Office of the DirectorAustralian Research CouncilNational Science FoundationCanadian Institutes of Health ResearchStand Up To CancerFarmer Family FoundationKnut och Alice Wallenbergs StiftelseUniversity of California, San DiegoSwiss Institute of BioinformaticsNational Institute on AgingCanada Research ChairsNational Institutes of Health
KeywordsHuman proteome projectProteomeComputational biologyProteomicsBiologyBioinformaticsGeneticsGene

Abstract

fetched live from OpenAlex

The 2022 Metrics of the Human Proteome from the HUPO Human Proteome Project (HPP) show that protein expression has now been credibly detected (neXtProt PE1 level) for 18 407 (93.2%) of the 19 750 predicted proteins coded in the human genome, a net gain of 50 since 2021 from data sets generated around the world and reanalyzed by the HPP. Conversely, the number of neXtProt PE2, PE3, and PE4 missing proteins has been reduced by 78 from 1421 to 1343. This represents continuing experimental progress on the human proteome parts list across all the chromosomes, as well as significant reclassifications. Meanwhile, applying proteomics in a vast array of biological and clinical studies continues to yield significant findings and growing integration with other omics platforms. We present highlights from the Chromosome-Centric HPP, Biology and Disease-driven HPP, and HPP Resource Pillars, compare features of mass spectrometry and Olink and Somalogic platforms, note the emergence of translation products from ribosome profiling of small open reading frames, and discuss the launch of the initial HPP Grand Challenge Project, "A Function for Each Protein".

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)0.016
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.002
Science and technology studies0.0070.001
Scholarly communication0.0010.000
Open science0.0070.002
Research integrity0.0010.014
Insufficient payload (model declined to judge)0.0020.000

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 head0.274
GPT teacher head0.506
Teacher spread0.232 · 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.

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

Citations60
Published2022
Admission routes2
Has abstractyes

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