Jennifer M. Taylor

This paper develops a method to analyze chromatin architecture in formaldehyde-preserved specimens up to 117 years old, revealing preserved patterns and new insights into chromatin dynamics.

EffectorP 2.0 improves fungal effector protein prediction with higher accuracy and reduced false positives compared to previous versions.

This study presents haplotype-phased genome assemblies of two dikaryotic Puccinia coronata f. sp. avenae isolates, revealing structural variation and heterozygous SNPs, and identifies co-expressed effector candidates associated with virulence differences.

ApolystP predicts apoplastic localization of plant proteins and effectors using machine learning, achieving high sensitivity and low false positive rate.

LOCALIZER predicts subcellular localization of plant and effector proteins, showing improved accuracy for chloroplast and mitochondrial targeting and identifying a new chloroplast transit peptide in ToxA.