22 papers · ranked by Valyu relevance
Sihan Xie, Thierry Tribout, Didier Boichard, Blaise Hanczar + 2 more
Deep generative models open new avenues for simulating realistic genomic data while preserving privacy and addressing data accessibility constraints. While previous studies have primarily focused on generating gene expression or haplotype data, this study explores generating genotype data in both unconditioned and…
Xie, Sihan, Tribout, Thierry + 8 more
Deep generative models open new avenues for simulating realistic genomic data while preserving privacy and addressing data accessibility constraints. While previous studies have primarily focused on generating gene expression or haplotype data, this study explores generating genotype data in both unconditioned and…
Kira Villiers, Eric Dinglasan, Ben J. Hayes, Kai P. Voss-Fels
Simulation tools are key to designing and optimising breeding programs that are many-year, high-effort endeavours. Tools that operate on real genotypes and integrate easily with other analysis software are needed for users to integrate simulated data into their analysis and decision-making processes. This paper…
Kira Villiers, Eric Dinglasan, Ben J Hayes, Kai P Voss-Fels + 1 more
'D -J de Koning'] Title: Abstract Simulation tools are key to designing and optimizing breeding programs that are multiyear, high-effort endeavors. Tools that operate on real genotypes and integrate easily with other analysis software can guide users toward crossing decisions that best balance genetic gains and genetic…
Roeland E Voorrips, Chris A Maliepaard
The process described in the previous section generates gametes in which each chromosome is a product of recombination between the homologous chromosomes in the parent. Two further steps are required to derive observable genotypes (e.g. marker genotypes) from these parental recombination products. The first step is to…
Torsten Günther, Inka Gawenda, Karl J Schmid
Background There is a great interest in understanding the genetic architecture of complex traits in natural populations. Genome-wide association studies (GWAS) are becoming routine in human, animal and plant genetics to understand the connection between naturally occurring genotypic and phenotypic variation. Coalescent…
Andrew Whalen, Chris Gaynor, John M Hickey
In this paper we develop and test a method which uses high-throughput phenotypes to infer the genotypes of an individual. The inferred genotypes can then be used to perform genomic selection. Previous methods which used high-throughput phenotype data to increase the accuracy of selection assumed that the…
Fabio Zanini, Richard A. Neher
The analysis of the evolutionary dynamics of a population with many polymorphic loci is challenging since a large number of possible genotypes needs to be tracked. In the absence of analytical solutions, forward computer simulations are an important tool in multi-locus population genetics. The run time of standard…
Ahmad Al Kawam, Mustafa Alshawaqfeh, James J. Cai, Erchin Serpedin + 1 more
'Aniruddha Datta'] Background Analyzing Variance heterogeneity in genome wide association studies (vGWAS) is an emerging approach for detecting genetic loci involved in gene-gene and gene-environment interactions. vGWAS analysis detects variability in phenotype values across genotypes, as opposed to typical GWAS…
Audrey AA Martin, Jeffrey Schoenebeck, Dylan N. Clements, Tom Lewis + 2 more
Collecting genomic information is crucial to advance breeding for complex traits such as health, welfare, and behaviour in domesticated populations. For that purpose, different data collection scenarios can be envisioned based on the number of individuals, the number of markers, and the genotyping technology. This…
Jon Bančič, Philip Greenspoon, Chris R. Gaynor, Gregor Gorjanc
Plant breeding plays a crucial role in the development of high-performing crop varieties that meet the demands of society. Emerging breeding techniques offer the potential to improve the precision and efficiency of plant breeding programs; however, their optimal implementation requires refinement of existing breeding…
Michael J. Burns, Rafael Della Coletta, Samuel B. Fernandes, Martin O. Bohn + 2 more
The use of computational and data-driven approaches to accelerate and optimize breeding programs is becoming common practice among plant breeders. Simulations allow breeders to evaluate potential changes in breeding schemes in a time– and cost-efficient manner. However, accurately simulating traits that match empirical…
Bert Wang-Chak Chan
Inspired by biological and cultural evolution, there have been many attempts to explore and elucidate the necessary conditions for openendedness in artificial intelligence and artificial life. Using a continuous cellular automata called Lenia as the base system, we built largescale evolutionary simulations using…
M. Pérez-Enciso, L. M. Zingaretti, G. de los Campos
Among the broad area of artificial intelligence (AI), generative AI algorithms have emerged as a revolutionary technology able to produce highly realistic ‘synthetic’ data, akin to standard simulation but with fewer contraints. The main focus of generative AI has been on phenotypes, but here we argue it can serve as…
Luyan Zhang, Huihui Li, Jiankang Wang
Simulation is an efficient approach for the investigation of theoretical and applied issues in population and quantitative genetics, and animal and plant breeding. In this study, we report a multi-module simulation platform called Blib, that is able to handle more complicated genetic effects and models than existing…
Chris Marriott, Jobran Chebib
Emergence is a phenomenon taken for granted in science but also still not well understood. We have developed a model of artificial genetic evolution intended to allow for emergence on genetic, population and social levels. We present the details of the current state of our environment, agent, and reproductive models.…
Kevin Thornton
fwdpp is a C++ library of routines intended to facilitate the development of forward-time simulations under arbitrary mutation and fitness models. The library design provides a combination of speed, low memory overhead, and modeling flexibility not currently available from other forward simulation tools. The library is…
Authors not listed
Synthetic cells emulate fundamental biological behaviors, such as growth, metabolism, and evolution, under non-equilibrium conditions, but have lacked genotype-driven selection, which is essential for Darwinian evolution. Here, we introduce short DNA sequences as genotypes into fuel-dependent, peptide-RNA-based…
Benjamin Stich, Delphine Van Inghelandt, Po-Ya Wu
The wide range of tools and methods available to plant breeders today has the potential to increase the gain of selection. However, they also result in numerous complex choices in the design of efficient crossing and selection strategies. Computer simulations are essential to optimize breeding programs that are…
Peter M. F. Emmrich, Véra Pancaldi, Hannah Roberts, Krystyna A. Kelly + 1 more
'Krystyna A. Kelly' 'David C. Baulcombe'] Background: Modelling genetic phenomena affecting biological traits is important for the development of agriculture as it allows breeders to predict the potential of breeding for certain traits. One such phenomenon is heterosis or hybrid vigor: crossing individuals from…
Jan H. Jensen
This paper presents a comparison of a graph-based genetic algorithm (GB-GA) and machine learning (ML) results for the optimisation of logP values with a constraint for synthetic accessibility and shows that GA is as good or better than the ML approaches for this particular property. The molecules found by GB-GA bear…
Authors not listed
RNA droplets assembled from co-transcriptionally folded nanostructures have recently emerged as a promising platform for constructing protocells and minimal synthetic cell models. In these systems, a custom-designed DNA template encodes an RNA nanostar, which is produced by transcription and self-assembles into…