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A community resource for paired genomic and metabolomic data mining
Michelle Schorn, Stefan Verhoeven, Lars Ridder, Florian Huber, Deepa Acharya, Alexander A. Aksenov, Gajender Aleti, Jamshid Amiri Moghaddam, Allegra T. Aron, Saefuddin Aziz, Anelize Bauermeister, Katherine D. Bauman, Martin Baunach, Christine Beemelmanns, J. Michael Beman, María Victoria Berlanga‐Clavero, Alex Blacutt, Helge B. Bode, Anne Boullié, Asker Brejnrod, Tim S. Bugni, Alexandra Calteau, Liu Cao, Víctor J. Carrión, Raquel Castelo‐Branco, Shaurya Chanana, Alexander B. Chase, Marc G. Chevrette, Letícia V. Costa‐Lotufo, Jason M. Crawford, Cameron R. Currie, Bart Cuypers, Tam Dang, Tristan de Rond, Alyssa M. Demko, Elke Dittmann, Chao Du, Christopher Drozd, Jean‐Claude Dujardin, Rachel J. Dutton, Anna Edlund, David P. Fewer, Neha Garg, Julia M. Gauglitz, Emily C. Gentry, Lena Gerwick, Evgenia Glukhov, Harald Gross, Muriel Gugger, Dulce G. Guillén Matus, Eric J. N. Helfrich, Benjamin-Florian Hempel, Jae-Seoun Hur, Marianna Iorio, Paul R. Jensen, Kyo Bin Kang, Leonard Kaysser, Neil L. Kelleher, Chung Sub Kim, Ki Hyun Kim, Irina Koester, Gabriele M. König, Tiago Leão, Seoung Rak Lee, Yi-Yuan Lee, Xuanji Li, Jessica Little, Katherine N. Maloney, Daniel Männle, Christian Martin, Andrew C. McAvoy, Willam W. Metcalf, Hosein Mohimani, Carlos Molina‐Santiago, Bradley S. Moore, Michael W. Mullowney, Mitchell N. Muskat, Louis‐Félix Nothias, Ellis C. O’Neill, Elizabeth I. Parkinson, Daniel Petras, Jörn Piel, Emily C. Pierce, Karine Pires, Raphael Reher, Diego Romero, M. Caroline Roper, Michael Rust, Hamada Saad, Carmen Saenz, Laura M. Sanchez, Søren J. Sørensen, Margherita Sosio, Roderich D. Süßmuth, Douglas Sweeney, Kapil Tahlan, Regan J. Thomson, Nicholas J. Tobias, Amaro E. Trindade-Silva, Gilles P. van Wezel, Mingxun Wang, Kelly C. Weldon, Fan Zhang, Nadine Ziemert, Katherine Duncan, Max Crüsemann, Simon Rogers, Pieter C. Dorrestein, Marnix H. Medema, Justin J. J. van der Hooft
Bibliographic record
VenueNature Chemical Biology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolomics and Mass Spectrometry Studies
Canadian institutionsMemorial University of Newfoundland
FundersLeibniz-Institut für Naturstoff-Forschung und Infektionsbiologie – Hans-Knöll-InstitutCarl R. Woese Institute for Genomic BiologyNational Center for Complementary and Integrative HealthNational Institute of General Medical SciencesNational Cancer InstituteHarvard UniversityDet Sundhedsvidenskabelige Fakultet, Københavns UniversitetSchool of Chemistry, University of NottinghamConsejo Superior de Investigaciones CientíficasFundação para a Ciência e a TecnologiaLeibniz-GemeinschaftGreat Lakes Bioenergy Research CenterUniversität PotsdamDirectorate for Biological SciencesNovo Nordisk Foundation Center for Basic Metabolic ResearchNovo Nordisk FondenWageningen University and ResearchFaculty of Health and Medical Sciences, University of Western AustraliaUniversity of Illinois at Urbana-ChampaignRheinische Friedrich-Wilhelms-Universität BonnPrinceton UniversityUniversiteit AntwerpenNorthwestern UniversityUniversidade do PortoUniversidade de São PauloWageningen University FundSungkyunkwan UniversityJenderal Soedirman UniversityTechnische Universität BerlinSunchon National UniversityUniversity of California, San DiegoMemorial University of NewfoundlandUniversity of Wisconsin-MadisonU.S. Department of EnergyYale UniversityEberhard Karls Universität TübingenUniversity of GlasgowNetherlands eScience CenterSookmyung Women's UniversityEuropean CommissionInstituut voor Tropische GeneeskundeSkaggs School of Pharmacy and Pharmaceutical SciencesHelsingin YliopistoDeutsches Zentrum für InfektionsforschungNovo NordiskGeorgia Institute of TechnologyNational Research CentreUniversidad de MálagaUniversity of California MercedNational Institutes of HealthBiotechnology and Biological Sciences Research CouncilPurdue UniversityNational Science Foundation
KeywordsMetabolomicsMetabolomeIdentification (biology)GenomicsComputational biologyMetaboliteBiologyOmicsData scienceGenomeComputer scienceBioinformaticsGeneticsGeneEcologyBiochemistry
Abstract
Genomics and metabolomics are widely used to explore specialized metabolite diversity. The Paired Omics Data Platform is a community initiative to systematically document links between metabolome and (meta)genome data, aiding identification of natural product biosynthetic origins and metabolite structures.
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 imitationNot 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)0.001
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 score0.484
Threshold uncertainty score0.638
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 head0.031
GPT teacher head0.304
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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
Citations129
Published2021
Admission routes2
Has abstractyes