Carson M. Andorf

The paper introduces a new pangenome viewer for maize that integrates graph and linear genome visualization to enhance structural variation analysis and locus characterization.

The paper introduces a web tool and R package for analyzing the evolutionary origins of maize proteins, providing interactive visualizations and gene data for 26 maize inbreds.

reelGene evaluates gene models using machine learning and evolutionary data, finding 28% of maize gene models are incorrectly annotated or nonfunctional.

The paper benchmarks AlphaFold, ESMFold, and Boltz in maize to assess their performance on plant proteins, finding lower confidence scores and geometry issues in less conserved proteins.

The paper examines genome evolution in maize and related grasses, revealing variable outcomes of polyploidy across species.

The paper provides a unified VCF dataset from 1,498 maize accessions to explore genomic diversity using a standardized variant-calling pipeline.

This paper applies RFdiffusion to predict interspecies protein-protein interactions between fungal pathogens and cereal crops, achieving high recall in identifying validated interactions.

The paper introduces the Fusarium Protein Toolkit, a web-based resource that provides structural models and variant effect predictions for Fusarium proteins to aid in understanding and mitigating crop diseases and mycotoxin contamination.

PanEffect visualizes variant effects across 51 maize genomes using ESM scores, enabling exploration of 550 million amino acid substitutions and 2.3 million natural variations.

FASSO combines sequence and structure orthology to improve ortholog prediction across species, annotating over 270,000 functions in plant and outgroup proteomes.

ABRIDGE compresses SAM alignment files with lossless and lossy options, achieving higher compression ratios than existing tools for RNA-Seq and DNA-Seq.

A multi-genome analysis of maize reveals previously unknown variation in gene content, genome structure, and methylation.

FINDER automatically annotates eukaryotic genes from RNA-Seq data and associated protein sequences, improving accuracy by integrating raw reads and protein evidence.

GenomeQC evaluates genome assembly and gene annotation quality by integrating multiple metrics and allows benchmarking against reference genomes.

This paper provides a high-coverage, high-confidence GO annotation for maize genes, outperforming existing annotations in accuracy using a mixed-method pipeline.