Eric A. Stone

The paper identifies a transposable element insertion in a second thyroglobulin-like gene as a mechanism of Vip3Aa resistance in Helicoverpa armigera.

Path2Omics predicts gene expression and methylation from histopathology slides across 23 cancer types, outperforming previous models and showing effectiveness in predicting patient outcomes.

This study improves genomic prediction of wheat traits by integrating gene expression and environmental data, showing that combining transcriptome and environment data enhances prediction accuracy.

The paper introduces a graph-based measure of protein fitness landscape ruggedness and shows it concentrates at regions where dominant constraints change.

AGP-Net predicts spatial gene expression from histopathology images by leveraging textual gene descriptions to generalize across unseen genes and datasets.

The paper characterizes the virulence of Puccinia coronata f. sp. avenae isolates in Australia during the 2023 growing season and identifies new or increased virulence on resistance genes.

This study constructs a high-resolution haplotype pangenome of oat crown rust, revealing somatic hybridization, recombination, and intercontinental migration as drivers of genetic diversity.

This paper introduces EGGN, an exemplar guided graph neural network for predicting gene expression from spatial transcriptomics tissue slide images, showing superior performance on benchmark datasets.

The paper compares methods for identifying fungal species from sequencing data and finds that aligning sequences to a fungi-specific database with coverage cutoffs improves accuracy.

This paper demonstrates that linked machine learning classifiers improve species classification of fungi using error-prone long-reads on extended metabarcodes, achieving high recall and low false positives.

The paper identifies and corrects phase switches in Hi-C data for dikaryotic fungus assemblies using Nanopore and HiFi sequencing, showing HiFi's superiority in phasing low heterozygosity genomes.

Permutation-based maximal matched-pairs symmetry tests show 40.8% of 3,572 partitions from 35 published phylogenetic datasets reject stationary, reversible, homogeneous evolution, frequently altering inferred tree topologies.

The paper introduces a method called private haplotype barcoding to reduce costs of genotyping offspring from multiple crosses by pooling samples and using haplotype information for deconvolution.