Kristen L. Beck

Commensal or pathogen: computational vectorizing microbial genomes for de novo risk assessment and virulence feature discovery in Klebsiella pneumoniae

This paper predicts virulence in Klebsiella pneumoniae using expanded gene function discoveries and machine learning, achieving higher accuracy than traditional methods.

Predicting Epitope Candidates for SARS-CoV-2

The paper predicts epitope candidates for SARS-CoV-2 by analyzing epitope sequences from related coronaviruses and identifying conserved and diverse antigen regions across 62k genomes.

BioAct: Biomedical Knowledge Base Construction using Active Learning

This paper introduces BioAct, an active learning method for creating curated datasets to enable biomedical knowledge base construction, and releases an annotated dataset on antimicrobial resistance.

DNA extraction and host depletion methods significantly impact and potentially bias bacterial detection in a biological fluid

The paper evaluates DNA extraction and host depletion methods in bovine milk to improve bacterial detection for food safety, finding that magnetic-based methods are most effective and some methods introduce microbial detection bias.

Semi-supervised identification of SARS-CoV-2 molecular targets

The paper develops a semi-supervised pipeline to annotate SARS-CoV-2 genomes, identifying molecular targets with high accuracy and scalability.

Analysis and Forecasting of Global RT-PCR Primers for SARS-CoV-2

The paper analyzes how SARS-CoV-2 mutations affect RT-PCR primer specificity and finds a 2% monthly increase in mismatches and geographic-specific virus detection.

EMPress enables tree-guided, interactive, and exploratory analyses of multi-omic datasets

EMPress provides an interactive tool for visualizing phylogenetic trees alongside multi-omic data, enabling exploratory analyses of microbiome and metabolome datasets.