Lawrence A. David

Benchmarking Short-Read ITS2 and Full-Length ITS Sequencing Reveals Pipeline-Dependent Biases in Indoor Fungal Community Profiling

This paper compares short-read ITS2 and long-read full-length ITS sequencing for fungal community profiling, finding that full-length ITS improves taxonomic resolution and ecological inference.

A foundation model for microbial growth dynamics

This paper develops a foundation model for microbial growth dynamics using self-supervised learning on diverse datasets, enabling accurate reconstruction and prediction of growth patterns and antibiotic responses.

Metaproteomics and DNA metabarcoding as tools to assess dietary intake in humans

The paper compares DNA metabarcoding and metaproteomics in stool to assess dietary intake, finding both methods identify similar food taxa and provide distinct protein-based distinctions.

Interplay between particle size and microbial ecology in the gut microbiome

This study investigates the factors influencing fecal particle size in humans and finds that gut microbiota, rather than diet or behavior, primarily shape particle size.

Naught all zeros in sequence count data are the same

The paper evaluates zero-handling models in genomic and microbiome data, showing significant disagreement in identifying differentially expressed sequences and finding simple count models sufficient across processes.

Measuring and Mitigating PCR Bias in Microbiome Data

The paper measures and mitigates PCR bias in microbiome data using experimental validation and Bayesian models.

Dynamic linear models guide design and analysis of microbiota studies within artificial human guts

The paper develops a modeling framework to analyze microbiota dynamics in artificial human guts, revealing technical noise as a major source of variation and identifying sub-daily fluctuations and replicable trajectories.