Wolfgang Maier

The paper introduces evoPLM-Tree, a tree-aware language model that predicts viral mutations by incorporating phylogenetic context, showing it captures mutational patterns and functional constraints in SARS-CoV-2 spike protein evolution.

VEFill is a gradient boosting model that imputes missing DMS scores across protein domains, achieving strong predictive performance and generalization to new proteins.

The paper introduces BRC-Analytics, a browser-based platform for pathogen genomics, demonstrating its use in analyzing measles virus evolutionary dynamics and revealing asymmetric frame evolution under selective pressures.

The paper investigates how left-right cortical interactions drive pattern formation in Tetrahymena by analyzing the role of HPO1 and Bcd1 in oral apparatus positioning.

The paper identifies JanA, a Polo kinase in Tetrahymena, whose loss causes a dorsal/ventral intracellular homeosis by altering organelle positioning and cortical patterning.

varVAMP designs pan-specific primers for tiled sequencing and qPCR of diverse viruses, ensuring specificity through minimal variability regions and degenerate nucleotides.

This study evaluates the impact of sequencing technologies and bioinformatic protocols on SARS-CoV-2 variant calling and introduces standardized parameters to improve pipeline consistency.

The paper describes open data sharing, analysis tools, and lessons learned from the European COVID-19 Data Platform's SARS-CoV-2 data collection and analysis efforts.

The paper introduces Galaxy Training Network (GTN) as a framework for creating and sharing FAIR training materials for data analysis, with recent improvements to support educators and expand its use in various learning environments.

The paper presents a global, community-maintained platform for analyzing SARS-CoV-2 genomic data, demonstrating its utility in variant detection and reanalysis of existing datasets.

This study identifies ENDU-2, a secreted RNase in C. elegans, that maintains germline immortality by regulating mRNA abundance and preventing soma-specific gene misexpression in the germline.

The paper highlights the importance of open data and analytics in responding to public health emergencies, using COVID-19 genomic data to demonstrate the effectiveness of community-driven software tools and infrastructure.

This study uses direct RNA sequencing to identify RNA modifications in SARS-CoV-2 isolated from human lung cells, revealing conserved modification patterns across isolates.

The paper uses a novel gene-based analysis approach to identify three novel genes associated with Alzheimer’s disease using genome-wide association data.