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UbiHub: a data hub for the explorers of ubiquitination pathways

2018· article· en· W2907957654 on OpenAlexafffund
Lihua Liu, David Damerell, Leonidas Koukouflis, Yufeng Tong, Brian D. Marsden, Matthieu Schapira

Bibliographic record

VenueBioinformatics · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of WindsorStructural Genomics ConsortiumUniversity of Toronto
FundersEshelman Institute for Innovation, University of North Carolina at Chapel HillJanssen BiotechInnovative Medicines InitiativeNovartis PharmaOntario Genomics InstituteCanada Foundation for InnovationWellcome TrustOntario Ministry of Research, Innovation and ScienceOntario GenomicsFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaAbbVieEuropean Federation of Pharmaceutical Industries and AssociationsStructural Genomics ConsortiumMerck KGaAPfizerBoehringer Ingelheim
KeywordsUbiquitinProteasomeDrug discoveryDeubiquitinating enzymeComputational biologyProtein degradationBiologyUbiquitin-Protein LigasesUbiquitin ligaseCell biologyBioinformaticsBiochemistry

Abstract

fetched live from OpenAlex

MOTIVATION: Protein ubiquitination plays a central role in important cellular machineries such as protein degradation or chromatin-mediated signaling. With the recent discovery of the first potent ubiquitin-specific protease inhibitors, and the maturation of proteolysis targeting chimeras as promising chemical tools to exploit the ubiquitin-proteasome system, protein target classes associated with ubiquitination pathways are becoming the focus of intense drug-discovery efforts. RESULTS: We have developed UbiHub, an online resource that can be used to visualize a diverse array of biological, structural and chemical data on phylogenetic trees of human protein families involved in ubiquitination signaling, including E3 ligases and deubiquitinases. This interface can inform target prioritization and drug design, and serves as a navigation tool for medicinal chemists, structural and cell biologists exploring ubiquitination pathways. AVAILABILITY AND IMPLEMENTATION: https://ubihub.thesgc.org.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.635
Threshold uncertainty score0.294

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 science0.0010.000
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 head0.075
GPT teacher head0.294
Teacher spread0.219 · 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

Citations68
Published2018
Admission routes2
Has abstractyes

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