← Back to cohort
Minimum Information about a Biosynthetic Gene cluster
Marnix H. Medema, Renzo Kottmann, Pelin Yilmaz, Matthew Cummings, John Biggins, Kai Blin, Irene de Bruijn, Yit‐Heng Chooi, Jan Claesen, Roger Coates, Pablo Cruz‐Morales, Srikanth Duddela, Stephanie Düsterhus, Daniel Edwards, David P. Fewer, Neha Garg, Christoph Geiger, Juan Pablo Gomez‐Escribano, Anja Greule, Michalis Hadjithomas, Anthony S. Haines, Eric J. N. Helfrich, Matthew L. Hillwig, Keishi Ishida, Adam C. Jones, Carla S. Jones, Katrin Jungmann, Carsten Kegler, Hyun Uk Kim, Peter Kötter, Daniel Krug, Joleen Masschelein, Alexey V. Melnik, Simone M. Mantovani, Emily A. Monroe, Marcus A. Moore, Nathan A. Moss, Hans‐Wilhelm Nützmann, Guohui Pan, Amrita Pati, Daniel Petras, F. Jerry Reen, Federico Rosconi, Zhe Rui, Zhenhua Tian, Nicholas J. Tobias, Yuta Tsunematsu, Philipp Wiemann, Elizabeth E. Wyckoff, Xiaohui Yan, Grace Yim, Fengan Yu, Yunchang Xie, Bertrand Aigle, Alexander K. Apel, Carl J. Balibar, Emily P. Balskus, Francisco Barona‐Gómez, Andreas Bechthold, Helge B. Bode, Rainer Borriss, Sean F. Brady, Axel A. Brakhage, Patrick Caffrey, Yi‐Qiang Cheng, Jon Clardy, Russell J. Cox, René De Mot, Stefano Donadio, Mohamed S. Donia, Wilfred A. van der Donk, Pieter C. Dorrestein, Seán Doyle, Arnold J. M. Driessen, Monika Ehling‐Schulz, Karl-Dieter Entian, Michael A. Fischbach, Lena Gerwick, William H. Gerwick, Harald Gross, Bertolt Gust, Christian Hertweck, Monica Höfte, Susan E. Jensen, Jianhua Ju, Leonard Katz, Leonard Kaysser, Jonathan L. Klassen, Nancy P. Keller, Ján Kormanec, Oscar P. Kuipers, Tomohisa Kuzuyama, Nikos C. Kyrpides, Hyung-Jin Kwon, Sylvie Lautru, Rob Lavigne, Chia Y. Lee, Linquan Bai, Xinyu Liu, Wen Liu, Andriy Luzhetskyy, Taifo Mahmud, Yvonne Mast, Cármen Méndez, Mikko Metsä‐Ketelä, Jason Micklefield, Douglas A. Mitchell, Leonilde M. Moreira, Rolf Müller, Brett A. Neilan, Markus Nett, Jens Nielsen, Fergal O’Gara, Hideaki Oikawa, Anne Osbourn, Marcia S. Osburne, Bohdan Ostash, Shelley M. Payne, Jean‐Luc Pernodet, Miroslav Petřı́ček, Jörn Piel, Olivier Ploux, Jos M. Raaijmakers, José A. Salas, E. Schmitt, Barry Scott, Ryan F. Seipke, Ben Shen, David H. Sherman, Kaarina Sivonen, Michael J. Smanski, Margherita Sosio, Evi Stegmann, Roderich D. Süßmuth, Kapil Tahlan, Christopher M. Thomas, Yi Tang, Andrew W. Truman, Muriel Viaud, Jonathan D. Walton, Christopher T. Walsh, Tilmann Weber, Gilles P. van Wezel, Barrie Wilkinson, Joanne M. Willey, Wolfgang Wohlleben, Gerard D. Wright, Nadine Ziemert, Changsheng Zhang, Sergey B. Zotchev, Rainer Breitling, Eriko Takano, Frank Oliver Glöckner
Bibliographic record
VenueNature Chemical Biology · 2015
Typearticle
Languageen
FieldMedicine
TopicMicrobial Natural Products and Biosynthesis
Canadian institutionsUniversity of AlbertaMcMaster UniversityMemorial University of Newfoundland
FundersLeibniz-Institut für Naturstoff-Forschung und Infektionsbiologie – Hans-Knöll-InstitutNational Institute of Allergy and Infectious DiseasesNational Institute of General Medical SciencesShanghai Institute of Organic Chemistry, Chinese Academy of SciencesCentro de Investigación y de Estudios Avanzados del Instituto Politécnico NacionalBiotechnology and Biological Sciences Research CouncilTufts University School of MedicineInstitute for Bioengineering and BiosciencesState Key Laboratory of Microbial MetabolismNovo Nordisk FondenInstitute of Oceanology, Chinese Academy of SciencesKorea Advanced Institute of Science and TechnologyInstitut National de la Recherche AgronomiqueNovartis Institutes for BioMedical ResearchVeterinärmedizinische Universität WienUniversidad de OviedoAdvanced Scientific Computing ResearchUniversidade de LisboaMemorial University of NewfoundlandTurun YliopistoShanghai Jiao Tong UniversityCentre National de la Recherche ScientifiqueUniversity of TokyoUniversität des SaarlandesUniversiteit GentSlovenská Akadémia ViedDeutsches Zentrum für InfektionsforschungAkademie Věd České RepublikyUniversity of PittsburghNational University of IrelandUniversity of New South WalesKU LeuvenDanmarks Tekniske UniversitetKoninklijke Nederlandse Akademie van WetenschappenInstituto Politécnico NacionalChalmers Tekniska HögskolaNational Cancer InstituteAlbert-Ludwigs-Universität FreiburgUniversity of California, San DiegoUniversité Paris DiderotMyongji UniversityUniversity of California, Los AngelesCurtin University of TechnologyRijksuniversiteit GroningenUniversity College CorkUniversity College DublinDirectorate for Biological SciencesKing Abdulaziz UniversityDivision of ChemistryTechnische Universität BerlinUniversity of BristolUniversity of LeedsNederlands Instituut voor EcologieCalifornia State University, ChicoUniversity of Illinois at Urbana-ChampaignWilliam Paterson University of New JerseyGordon and Betty Moore FoundationMcMaster UniversityNovo NordiskOregon State UniversityNational Science FoundationUniversity of MinnesotaUniversité de LorraineUniversity of North TexasUniversity of Arkansas for Medical SciencesSkaggs School of Pharmacy and Pharmaceutical SciencesHelsingin YliopistoMassey UniversityHokkaido UniversityUniversity of ConnecticutJoint Genome InstituteInstituto Superior TécnicoChinese Academy of SciencesNederlandse Organisatie voor Wetenschappelijk OnderzoekHarvard UniversityFriedrich-Schiller-Universität JenaEnergy Biosciences InstituteCalifornia Institute for Quantitative BiosciencesEngineering and Physical Sciences Research CouncilEuropean CommissionUniversity of AlbertaSouth China Sea Institute of Oceanology, Chinese Academy of SciencesU.S. Department of EnergyUniversity of Wisconsin-MadisonNatural Environment Research CouncilEberhard Karls Universität TübingenPrinceton UniversityLeibniz-GemeinschaftRoosevelt University
KeywordsGene clusterGeneComputational biologyCluster (spacecraft)BiologyMetabolic pathwayBiological pathwayExploitGeneticsGene expressionComputer science
Abstract
A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.
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 machine prediction
Teacher imitationNot 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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score1.000
Threshold uncertainty score0.022
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), not a consensus.
Study designNot applicable
DomainReporting
GenreMethods
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
Citations908
Published2015
Admission routes2
Has abstractno