Evidence map›Paper›PMID 41580412›Full record

ArticleNature communications2026

BiG-SCAPE 2.0 and BiG-SLiCE 2.0: scalable, accurate and interactive sequence clustering of metabolic gene clusters.

Arjan Draisma, Catarina Loureiro, Nico L L Louwen, Satria A Kautsar, Jorge C Navarro-Muñoz, Drew T Doering, Nigel J Mouncey, Marnix H Medema

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. Biosynthetic origin of anticancer dolastatin 15 reveals a noncanonical NRPS architecture enabling 2-keto acid activation.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. The Oxytetracycline ProducerInternational journal of molecular sciences · 2026
    Article
  4. Comparative Genome Mining ofMarine drugs · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Arjan Draisma *Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands.
Catarina Loureiro *Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands.
Nico L L Louwen *Bioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands.
Satria A KautsarDOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Jorge C Navarro-MuñozBioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands.ORCID 0000-0003-2992-1607
Drew T DoeringDOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
Nigel J MounceyDOE Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.ORCID 0000-0001-5380-1256
Marnix H MedemaBioinformatics Group, Wageningen University & Research, Droevendaalsesteeg 1, 6708PB, Wageningen, The Netherlands. marnix.medema@wur.nl.ORCID 0000-0002-2191-2821

Funding

Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Netherlands Organisation for Scientific Research) OSF.23.1.044U.S. Department of Energy (DOE) DE-AC02-05CH11231
6 · The paper itself

Abstract

Microbial metabolic gene clusters encode the biosynthesis or catabolism of metabolites that facilitate ecological specialization, mediate microbiome interactions and constitute a major source of medicines and crop protection agents. Here, we present BiG-SCAPE and BiG-SLiCE 2.0, next-generation methods that facilitate scalable, accurate and interactive gene cluster analyses. BiG-SCAPE 2.0 updates its classification, alignment methods, and visualizations, enabling more accurate analysis, up to 8x faster runtimes and halved memory requirements. BiG-SLiCE 2.0 updates its distance metric, pHMM database, and classification logic, resulting in increased sensitivity nearing that of BiG-SCAPE. Analysis of 260,630 biosynthetic gene clusters from publicly available genomes reveals that both tools generate concurring estimates of gene cluster diversity, thus providing significantly extended methodological support for recent evidence indicating that the vast majority of natural product diversity remains unexplored. Together, these updates will facilitate global genome mining efforts for natural product discovery and microbiome analyses scalable with current data sizes.

Indexed as

Computational BiologyMultigene FamilySoftwareCluster AnalysisClustering AlgorithmsDatabases, GeneticGenome, BacterialMicrobiota

Identifiers

PMID41580412
PMCPMC12936217

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.