Evidence map›Paper›PMID 37991849›Full record

ArticleBioinformatics (Oxford, England)2023

ChromaX: a fast and scalable breeding program simulator.

Omar G Younis, Matteo Turchetta, Daniel Ariza Suarez, Steven Yates, Bruno Studer, Ioannis N Athanasiadis, Andreas Krause, Joachim M Buhmann, Luca Corinzia

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Bridging tradition and innovation: a review of computer simulations in plant breeding.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Review
  2. Article
  3. A framework for simulating genotype-by-environment interaction using multiplicative models.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  4. Article
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

9 authors.

Omar G YounisDepartment of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.ORCID 0009-0004-2783-7932
Matteo TurchettaDepartment of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.
Daniel Ariza SuarezDepartment of Environmental Systems Science, Molecular Plant Breeding, ETH Zurich, Switzerland.
Steven YatesDepartment of Environmental Systems Science, Molecular Plant Breeding, ETH Zurich, Switzerland.
Bruno StuderDepartment of Environmental Systems Science, Molecular Plant Breeding, ETH Zurich, Switzerland.
Ioannis N AthanasiadisDepartment of Social Sciences, Wageningen University & Research, Wageningen, 6708, The Netherlands.
Andreas KrauseDepartment of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.
Joachim M BuhmannDepartment of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.
Luca CorinziaDepartment of Computer Science, ETH Zurich, Zürich, 8092, Switzerland.ORCID 0000-0001-8549-8351

Funding

Wageningen University and Research research
6 · The paper itself

Abstract

summaryChromaX is a Python library that enables the simulation of genetic recombination, genomic estimated breeding value calculations, and selection processes. By utilizing GPU processing, it can perform these simulations up to two orders of magnitude faster than existing tools with standard hardware. This offers breeders and scientists new opportunities to simulate genetic gain and optimize breeding schemes. AVAILABILITY AND IMPLEMENTATION: The documentation is available at https://chromax.readthedocs.io. The code is available at https://github.com/kora-labs/chromax.

Indexed as

GenomicsSoftwareComputer SimulationGene LibraryGenome

Identifiers

PMID37991849
PMCPMC10709540

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.