Rob D. Knight

The paper introduces Qemistree, a method for analyzing metabolomics mass spectrometry data using hierarchical molecular fingerprints and chemical ontologies to explore chemical composition.

The paper develops a machine learning workflow for auto-deconvolution of GC-MS data within GNPS, enabling molecular networking and applications in breathomics and volatilome mapping.

The paper examines how husbandry methods, net pen location, and anti-parasite treatment affect the mucosal microbiome of southern Bluefin Tuna.

The paper develops ReDU, a tool for discovering and re-analyzing metabolomics data in GNPS, following FAIR principles.

This paper expands the interpretability of human metabolomes by using food-based annotations, increasing the fraction of molecular features understood 7-fold.

The paper introduces a low-cost, high-accuracy method for generating long-range sequencing data using short-read NGS systems, enabling de novo genome assembly and haplotype phasing with minimal DNA input.

The paper introduces Qurro, a tool for interactively visualizing feature rankings and log-ratios in compositional omics data to improve exploratory analysis.

The paper uses metabolomics to correct metadata classifications in cheetah microbiome studies, revealing antibiotic transfer via grooming and improving understanding of medication effects.

The paper compares correlation/proportionality methods with MMvec for identifying microbe-metabolite interactions and finds MMvec performs better on real data due to its handling of sparsity.

This paper shows that incorporating species abundance data improves taxonomy classification accuracy for amplicon sequences.

This paper quantifies well-to-well contamination in microbiome studies, showing it occurs mainly during DNA extraction and affects low-biomass samples, with implications for data interpretation.

The paper generates 3D maps of microbiomes and metabolomes in cystic fibrosis lungs, revealing personalized and regiospecific chemical environments and microbial interactions.

The paper identifies novel conjugated bile acids produced by the microbiome in mice and humans using mass spectrometry and a murine 3D model.

MASST enables querying of public small-molecule tandem MS data to discover molecular relationships in metabolomics and natural product datasets.

This paper designs and evolves synthetic syntrophic E. coli pairs using a novel algorithm, revealing metabolic changes that enhance community fitness and guide co-culture optimization.

This study evaluates shallow shotgun sequencing as an alternative to 16S for affordable, high-resolution human microbiome analysis, finding it provides accurate taxonomic and functional profiles.

MetaRiPPquest identifies RiPPs by combining genome/metagenome mining with mass spectrometry analysis, discovering 5 novel natural products from 6 datasets.

BugBase assigns pathway coverage and traits (Gram stain, oxygen tolerance, pathogenicity) to individual taxa in 16S or shotgun microbiome data, detecting some functional differences bag-of-genes profiles miss.