James Riley Broach

The paper develops fluorescent probes to detect Paenibacillus thiaminolyticus in mixed populations by removing an S-layer that blocks probe access.

This study identifies Ikaros and HDAC1's roles in regulating heterochromatin and tumor suppression in T-ALL by modulating EZH2 activity and chromatin structure.

This study shows that genomic instability occurs before viral integration in HPV-transformed cells and that episomal virus leads to less tumorigenicity than integrated virus.

This study identifies mitochondrial genome variants associated with ALS and reports haplogroup distribution patterns in ALS patients.

The paper identifies 66 Neanderthal single nucleotide variants in modern human mitochondrial genomes, suggesting convergent evolution rather than recombination.

This study evaluates Optical Genome Mapping (OGM) for detecting structural variants in myeloid neoplasms, showing high concordance and identifying additional clinically relevant variants compared to standard of care methods.

The paper introduces a method to infer differential richness in 16S rRNA surveys by accounting for spurious taxa generated during sequencing, using an R package called Prokounter.

The paper compares TDP-43's transcriptional and splicing effects in muscle and neuronal cells, showing tissue-specific roles in disease.

This study uses microbial topic modeling to identify associations between vaginal microbiome composition and intrapartum fever in Ugandan laboring women, improving prediction beyond clinical variables.

This paper describes a method using optical genome mapping to identify somatic structural variants in solid tumors, showing high reliability and functional relevance.

This study evaluates optical genome mapping (OGM) for detecting genomic aberrations in AML, finding it identifies all clinically relevant SVs and CNVs and detects additional variants missed by standard methods.

The paper develops a custom ENCODE annotation for cancer genomics, highlighting TF-RBP interactions and network rewiring during oncogenesis, and validates findings using experimental assays.

The paper uses unsupervised machine learning to identify three molecular subtypes in ALS cortex samples, associated with oxidative stress, retrotransposon activation, and glial activation.

This paper presents an integrative framework to detect structural variants in cancer genomes using multiple methods and finds that non-coding structural variation significantly impacts genome function in cancer cells.

The paper investigates the role of PAFR in ALS and suggests PAFR inhibitors as potential therapeutic agents, particularly for SOD1 familial ALS.