David Juan

The paper presents an eDNA workflow integrating metabarcoding and real-time analysis to improve biodiversity monitoring by overcoming limitations in sensitivity, taxonomic range, and processing time.

The paper identifies convergent amino-acid substitutions in primate species linked to male-fertility genes and longevity.

The paper identifies associations between macrophage enhancers and cardiovascular disease variants using epigenomic data from immune cells.

Cross-species genome-phenome mapping in primates reveals thousands of protein-coding variants linked to the evolution of complex traits.

The paper evaluates the reliability of phylogenetic inference using primate enamel proteins by simulating sequence fragmentation and comparing results to a reference species tree.

The paper analyzes gene age co-localization within TADs and finds that whole genome duplications mark a transition in gene age patterns and their association with TAD insulation and essentiality.

The paper identifies proteins and regulatory elements associated with vocal learning by analyzing bat neural activity and epigenomic data.

CAAStools identifies and validates convergent amino acid substitutions in orthologous protein alignments for predefined species groups.

The paper uses long-read sequencing to generate and compare Y chromosome assemblies across haplogroups and assesses epigenetic modifications in human populations.

The paper uses primate genetic data to predict human variant pathogenicity with a deep learning classifier trained on 4.3 million common missense variants.

This study presents whole-genome data from 233 primate species, revealing patterns of genetic diversity, mutation rates, and recurrent missense mutations across primate clades.

TOGA integrates gene annotation and orthology inference across hundreds of genomes, improving ortholog detection and creating large comparative gene resources.

A machine learning approach identifies enhancer-phenotype associations across mammals, revealing links to brain size and behavior evolution.

The paper curates TE content in 248 mammalian genomes, finding trends in recent TE accumulation and associations with dietary habits.

The paper uses evolutionary constraint scores to identify functional genomic regions and finds they are enriched for variants associated with common diseases.

The paper identifies bats as a hotspot for horizontal transfer of DNA transposons, finding over 200 putative elements and shared transposons across mammals and reptiles.

DeepMosaic detects mosaic single nucleotide variants without control samples using deep convolutional neural networks, achieving high accuracy and uncovering many variants missed by existing methods.

The paper analyzes ACE2 gene sequences in strepsirrhine primates to assess their susceptibility to SARS-CoV-2, finding high variability and potential risk in some species.

This study identifies somatic SNVs in non-cancerous human brain tissues and establishes best practices for detecting low-frequency variants.

The paper introduces a machine learning method to detect somatic L1 insertions in human brain tissue, revealing their widespread distribution in neurons and glia and potential role in neuropsychiatric diseases.

The paper identifies intronic copy number variants (CNVs) as a significant source of gene expression variation in human populations, showing their association with gene expression differences and 3D genomic interactions.

The paper develops a method to sequence and assemble a human Y chromosome of African origin using native DNA and nanopore sequencing, achieving high continuity and enabling epigenetic modification detection.

The paper constructs a disease interaction network from patient molecular profiles to uncover molecular mechanisms of comorbidity and identify associated genes and drugs.

The paper develops a bioinformatic workflow to classify blood epigenomes by cell type and identifies chromatin determinant regions linked to cell identity and disease.

The paper measures and compares transcriptional and epigenetic variability across immune cell types and finds neutrophils exhibit higher variability linked to immune pathways and environmental exposure.

The paper uses co-evolutionary analysis to predict conserved protein-protein interfaces between prokaryotes and eukaryotes, even when sequences are distantly related.

The paper identifies 5hmC as a central hub in the chromatin network of ESCs, linking DNA demethylation to chromatin remodeling and pluripotency factors through epigenomic co-localization and co-evolution analysis.

The paper maps peptides from proteomics studies to human genes, finding that only 3% of 2,001 genes with non-protein-like features show peptide detection, suggesting many may not code for proteins.