Eran Elhaik

This study analyzes ancient sediment DNA to identify plant-microbe association signals in a 2-million-year-old Arctic ecosystem, finding rhizosphere-like microbial taxa and functional traits.

This paper develops a polygenic score for metabolic syndrome in early adulthood and shows it predicts cardiometabolic risk across the life course in Asian populations.

This paper challenges the use of the D-statistic to infer Neanderthal introgression, showing it instead reflects mutation rate variation across human populations.

The paper introduces predicTTE, a tool for time-to-event prediction in neurological diseases, demonstrating its utility in genetic discovery and personalized medicine.

CAMP provides a modular metagenomics analysis system that enables scalable, extensible workflows with integrated data visualization and reporting.

This study identifies 690 candidate ALS genes using a hierarchical Bayesian model, highlighting genetic convergence on the distal axon and functional significance in motor neurons.

The paper uses systems biology analysis of whole-genome sequences from 298 SB case-control pairs to identify key pathways and genes associated with spina bifida risk.

The paper shows PCA results in population genetics are unreliable and can be manipulated, suggesting a need for alternative methods.

The paper introduces TPS, a genomic dating method for ancient genomes, which accurately dates Eurasian samples and resolves conflicts in paleogenomic data.

This study identifies two distinct GR-regulated transcription pathways in zebrafish brains, showing synaptic activity's role in GR-mediated transcription of aplp1.

This paper critiques Mikheyev et al.'s 2019 study on Khazar genomes, highlighting methodological flaws, irreproducibility, and unsupported claims.

This paper defines ancient ancestry informative markers (aAIMs) and evaluates methods to identify them, showing a PCA-based method outperforms others in classifying ancient Eurasian populations.

Pair Matcher (PaM) optimizes treatment-control matches using genetic and demographic data to reduce population stratification bias, improving study accuracy and reproducibility.