Trent R. Northen

Rhizonet is a deep learning model for segmenting plant root images in hydroponic systems, improving accuracy and reducing manual effort in root biomass analysis.

The paper curates LC-MS/MS data from plant extracts to create a taxonomically focused database for exploring plant-derived molecules.

This study investigates how Cynipid wasps alter plant metabolism and cell wall structure to form galls, revealing coordinated lignin and xylan deposition in gall vasculature.

The paper studies how a geothermal spring community responds to diurnal stressors, revealing structured biotic interactions across domains of life.

This study shows that disrupting the indole glucosinolate pathway in Arabidopsis thaliana alters root exudate profiles and rhizobacterial communities.

This study evaluates how different inoculation practices and harvesting times affect microbial community reproducibility in a fabricated ecosystem with Brachypodium distachyon.

BLINK rapidly computes cosine similarity scores for tandem mass spectra, achieving high accuracy and speed through sparse matrix operations.

MassQL, an open-source query language, lets users search raw mass spectrometry data from any vendor for isotope, fragmentation and neutral-loss patterns, from one file to entire public repositories.

The paper shows that secondary metabolism gene clusters in Xylariales fungi are linked to broader ecological roles and increased gene diversity.

This study uses long-read metagenomics and metatranscriptomics to analyze soil communities, revealing phylum-specific secondary metabolite dynamics during wetting events.

The paper introduces a web-based tool for collaborative analysis of mass spectrometry data, enabling remote inspection, visualization, and analysis of private and public datasets.

SIMILE aligns fragmentation mass spectra with statistical significance, identifying more structurally similar compound pairs than cosine-based methods.

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.

MAGI integrates metabolomics and genomics data to improve metabolite identifications and gene annotations by scoring consensus through biochemical reactions.

The paper introduces an algorithm to correct habitat filtering in microbial correlation networks, improving accuracy on simulated and real data.

This study uses BONCAT-FACS-Seq to show that a large fraction of soil microbes are actively translating, challenging previous assumptions about soil microbial inactivity.

The paper develops a model-guided framework to predict microbial interactions in synthetic human gut microbiome communities and identifies key ecological drivers and network design principles.

This study shows that enzyme promiscuity enables E. coli to adapt to novel substrates through computational modeling and lab evolution experiments.