Alexandre Aono

[Gregor Gorjanc @GregorGorjanc]

VERY excited to announce a pre-print that represents the culmination of several years of work*: “On ARGs, pedigrees, and genetic relatedness matrices”

https://t.co/MNnonK88ep

Led by @BrieucLehmann with contributions from @epigenci @LukeAnderTroc @jeromekelleher @petrelharp

[Alexandre Aono @AonoAlexandre]

Simulating 500 million years of evolution with a language model | Science https://t.co/WMQIizDnYU

[Alexandre Aono @AonoAlexandre]

https://t.co/uG896RvjVh

[PLOS Biology @PLOSBiology]

Pleiotropy has long been assumed to hinder adaptation. @EvolSys explores a #PLOSBiology study that instead suggests that regulatory networks may evolve to ensure mutations are beneficial in correlated environments. Primer: https://t.co/BP6WkM7LSN Paper: https://t.co/1kYZ6pIXi0

[TheorApplGenet @TheorApplGenet]

Integrating targeted genetic markers to genotyping-by-sequencing for an ultimate genotyping tool
https://t.co/p2DtqVcBJ1

[Cell Press @CellPressNews]

Trait selection strategy in multi-trait GWAS: Boosting SNP discoverability by @YukaSuzuki15, @hanna_julienne, and colleagues
@HGGAdvances collection highlight
https://t.co/qfO2x8mbcs
@GeneticsSociety

[Dan Hendrycks @hendrycks]

The UC Berkeley course I co-taught now has lecture videos available:
https://t.co/kjEwnNY64q

With guest lectures from Nicholas Carlini, @JacobSteinhardt, @Eric_Wallace_, @davidbau, and more

Course site: https://t.co/xMjqHuenhB

[ASHG @GeneticsSociety]

Using multi-trait GWAS, @YukaSuzuki15, @hanna_julienne, and colleagues of @HGGAdvances' latest article aim to improve the statistical power of univariate testing by leveraging the joint genetic architecture of human phenotypes: https://t.co/5Yiz8pQLlx #ASHG #HumanGenetics

[Simon Maechling @simonmaechling]

Gene-editing improves soybean yield and quality.

Multi-year and multi-site field trials in China,
demonstrated:-

→ Improved grain yield.
→ Sustained oil content.
→ Improved Protein content.

↳ Accompanied by increased plant height and more branches and pods per plant.

[antisense. @razoralign]

SYNY: a pipeline to investigate and visualize collinearity between genomes https://t.co/mO8WYlpwRk

[Max Tegmark @tegmark]

I'e very excited about our AI latest paper, which shows that an architecture radically different from standard neural network achieves much better accuracy with fewer parameters for interesting physics and math problems. arXiv:2402.05110

[TheorApplGenet @TheorApplGenet]

Extending the breeder's equation for truncation selection from single to multiple sets of genotypes.

https://t.co/8TXbTO4WOK

[Plant Phenomics @PPhenomics]

Introducing CA-GAN: a novel approach for synthetic weed data generation in digital agriculture, reducing reliance on annotated data. Promising results in weed recognition. #DigitalAg #DeepLearning
Details: https://t.co/5qnTEKI3B7

[Heng Li @lh3lh3]

Preprint on Exploring gene content with pangenome gene graphs: https://t.co/quqnW7M50a. It describes pangene for building gene graphs and for calling gene-level variations which can be found at https://t.co/fjehEcrnyl.

Pleasant collaboration with @maxgmarin and @MahaFarhat.

[Nature Reviews Genetics @NatureRevGenet]

Plant pangenomes for crop improvement, biodiversity and evolution https://t.co/DEINnE2IpI #Review by @SchreiberMona, @murukarthickj, @Nils__Stein & Martin Mascher
@Uni_MR @LeibnizIPK @UniHalle @idiv

[GenomicPrediction @genomic_pred]

Using machine learning to integrate genetic and environmental data to model genotype-by-environment interactions https://t.co/RI1gNuUuPV

[Plant Science @sci_plant]

Haplotype-based phylogenetic analysis and population genomics uncover the origin and domestication of sweetpotato

https://t.co/SeM4fDFeK4
#plantscience ♻️

[Jente Ottenburghs | Avian Hybrids 🦆🧬 @Jente_O]

The era of the ARG: An introduction to ancestral recombination graphs and their significance in empirical evolutionary genomics | PLoS Genetics
https://t.co/zeyotO3GLn

[Plant Phenomics @PPhenomics]

Advancing crop genetics for future demands requires cost-effective phenotyping. Canopy roughness, a novel plot-level trait extracted from UAS data, proves reliable in estimating soybean biomass. #CropScience #UASPhenotyping
Details:https://t.co/Ds9dK3PVrs

[Plantae @plantae_org]

Join us for the upcoming Plantae webinar on January 26 at 10 am EST, hosted by the 2024 Plantae Fellows.

Free registration at https://t.co/722MfRHFKS