19 papers · ranked by Valyu relevance
Maria Perera, Daniel Mas Montserrat, Míriam Barrabés, Margarita Geleta + 2 more
The generation of synthetic genomic sequences using neural networks has potential to ameliorate privacy and data sharing concerns and to mitigate potential bias within datasets due to under-representation of some population groups. However, there is not a consensus on which architectures, training procedures, 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…
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…
Sihan Xie, Thierry Tribout, Didier Boichard, Blaise Hanczar + 2 more
The development of dense genotyping platforms and high-throughput sequencing technologies has significantly advanced genetic analysis . Today, genomic studies rely on large biobanks that contain vast amounts of genomic data. However, working with such datasets presents several challenges, including high sequencing…
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…
Aditya Syam, Chris Adonizio, Xinzhu Wei
The Genotype Representation Graph (GRG) [4] is a graph representation of whole genome polymorphisms, designed to encode the variant hard-call information in phased whole genomes. It encodes the geno-types as an extremely compact graph that can be traversed efficiently, enabling dynamic programming-style algorithms on…
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…
Heegun Lee, Vitor Seiti Sagae, Julian Garcia-Abadillo, Fernando Bussiman + 3 more
Genotype-by-environment interaction (GEI) has been studied to identify environment-stable/favorable genotypes. The GEI simulation could help refine the inference by incorporating tangible factors such as genomic and environmental information. The Bayesian additive main effect and multiplicative interaction (Bayesian…
Nobuaki Masaki, Sharon R. Browning, Brian L. Browning, Xiaofeng Zhu
Genotype data include errors that may influence conclusions reached by downstream statistical analyses. Previous studies have estimated genotype error rates from discrepancies in human pedigree data, such as Mendelian inconsistent genotypes or apparent phase violations. However, uncalled deletions, which generally have…
Christian R. Werner, R. Chris Gaynor, Daniel J. Sargent, Alessandra Lillo + 2 more
'Alessandra Lillo' 'Gregor Gorjanc' 'John M. Hickey'] Key message For genomic selection in clonally propagated crops with diploid (-like) meiotic behavior to be effective, crossing parents should be selected based on genomic predicted cross-performance unless dominance is negligible. Abstract For genomic selection (GS)…
Grace Sunshine David, José Marcelo Soriano Viana, Kaio Olimpio das Graças Dias, Sindhu Sareen
'Kaio Olimpio das Graças Dias' 'Sindhu Sareen'] The objective of this simulation-based study was to assess how genes, environments, and genotype x environment (GxE) interaction affect the quantitative trait loci (QTL) mapping efficiency. The simulation software performed 50 samplings of 300 recombinant inbred lines…
Mohan Rakesh, Hélène Vézina, Catherine Laprise, Ellen E Freeman + 2 more
Founder populations with deep genealogical data are well suited for investigating genetic variants contributing to diseases. Here, we present a new function added to the genealogical analysis R package GENLIB, which can simulate the transmission of haplotypes from founders to probands along very large and complex…
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…
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…
Tingting Hou, Chang Jiang, Qing Lu
The recent development of artificial intelligence (AI) technology, especially the advance of deep neural network (DNN) technology, has revolutionized many fields. While DNN plays a central role in modern AI technology, it has been rarely used in sequencing data analysis due to challenges brought by high-dimensional…
Thinh Tuan Chu, Peter Skov Kristensen, Just Jensen
Stochastic simulation software is commonly used to aid breeders designing cost-effective breeding programs and to validate statistical models used in genetic evaluation. An essential feature of the software is the ability to simulate populations with desired genetic and non-genetic parameters. However, this feature…
Tingting Hou, Chang Jiang, Qing Lu
The advent of artificial intelligence, especially the progress of deep neural networks, is expected to revolutionize genetic research and offer unprecedented potential to decode the complex relationships between genetic variants and disease phenotypes, which could mark a significant step toward improving our…
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…