Leroy Hood

A Biolink-compliant graph (∼15 million nodes, ∼113 million edges) adds RefMet and LIPID MAPS metabolite and lipid classifications, plus polygenic score and clinical data element entities, to Translator content.

The paper uses a multiomics approach to identify placental network differences among obstetric syndromes, finding unique signatures associated with specific clinical outcomes.

This study uses multiomic analysis to identify compartmentalized immune responses and tissue-vascular signatures in Lyme disease, linking local immune processes to systemic symptoms.

The paper identifies altered huntingtin-chromatin interactions in HD mouse models, linking them to transcriptional and epigenetic changes in striatal tissue.

The paper identifies APOE genotype-related metabolite associations with biological age and bioenergetics in humans, showing counterintuitive patterns in {varepsilon}2 and {varepsilon}4 carriers.

The paper examines the link between bowel movement frequency and blood metabolites in healthy individuals, finding associations with kidney function and chronic disease risk.

The paper analyzes the genetic and microbiome contributions to blood metabolite variation across 2,049 individuals, finding that over 60% of metabolites are associated with either genetics or the microbiome, with some showing interaction effects.

This study identifies blood-based biomarkers associated with Alzheimer's disease genetic risk variants in a large cohort of healthy adults, showing effects from early adulthood and sex-specific patterns.

The paper examines organ-specific proteins in mice across different genetic backgrounds to assess their diversity and define robustness scores for quality assessment.

iNetModels 2.0 provides an interactive platform for visualizing and exploring multi-omics associations in human health and disease.

The paper shows that gut microbiome uniqueness increases with age and predicts survival in humans.

The paper develops a workflow to identify transcription factor binding sites across 27 human tissues using DNase-seq data, resulting in a comprehensive footprint atlas with high-quality predictions.

The paper identifies 10 blood proteins with altered serum levels in early Lyme disease patients, developing a 10-protein panel for potential diagnostic use.

The paper identifies a blood metabolome signature that robustly predicts gut microbiome α-diversity across health and disease conditions.

The paper constructs a brain-specific transcriptional regulatory network model to identify core transcription factors involved in psychiatric and neurodegenerative diseases.

The paper uses a systems biology approach to analyze how glucocorticoid receptor sensitivity and energy deficit contribute to metabolic dysfunction in PTSD.

SIGDA provides detailed, robust visualizations of human ancestry and population structure from genetic data, outperforming PCA in detecting population axes and relationships.

The paper presents the complete genome sequence of Borrelia burgdorferi MM1 strain, identifies it as a new sequence type, and provides the first contiguous assembly of a specific plasmid.

BDQC identifies data outliers and anomalies in large-scale genomic pipelines without domain knowledge, improving data quality and enabling new insights.

This paper introduces an ultra-fast method for comparing personal genomes using genome fingerprints, enabling efficient and privacy-preserving genome analyses.

The paper builds genome-scale transcriptional regulatory networks for mouse and human striatum, identifying SMAD3 as a key regulator in Huntington’s disease.