Gili Greenbaum

This study examines how forest fragmentation affects the genetics and microbiomes of black howler monkeys, finding contrasting patterns where genetic diversity increases in fragmented areas while microbiome diversity decreases.

The paper estimates the match rate of forensic investigative genetic genealogy using a national population register in Israel.

The paper investigates how immune-related genetic variation in humans is shaped by ecological and cultural factors by analyzing MHC diversity across global populations.

The paper develops a framework to model gene drive spread in population networks and identifies network centrality measures that influence deployment outcomes.

This paper develops a network-based framework to study genetic consequences of habitat fragmentation, showing distinct genetic measure trajectories and early warning signals for rapid transitions.

This paper maps gene drive dynamics onto Mendelian models to enable classical population genetics tools for predicting gene-drive outcomes.

The paper models predator group dynamics and prey population interactions, finding that flexible group sizes lead to smaller stable groups and unexpected resource partitioning between prey types.

This study shows integrating gene drives with pest controls can reduce spillover risk by optimizing treatment strategies based on population dynamics and cost-effectiveness.

The paper introduces a method to predict the direction of phenotypic differences between individuals using genomic data, achieving over 90% accuracy in many cases.

The paper analyzes ancient genomic data to show increased disease burden in human populations over the past 12,000 years, linked to cultural shifts and domestication.

The paper identifies a previously unknown bioregion between tropical and temperate zones that explains latitudinal biodiversity and phylogenetic gradients through simulations.

The paper uses a data-driven approach to analyze social complexity in bees, revealing a major evolutionary transition in corbiculate bees that led to phenotypic diversification.

DORA is an interactive tool that integrates and visualizes ancient human DNA data with metadata and other layers, enabling analysis of spatiotemporal population genomic data.

This study analyzes tiger genomes to understand their evolutionary history, finding genetic differentiation, recent divergence, and selection pressures in different subspecies.

The paper introduces a network-based method for analyzing population structure in genomic data, demonstrating its application in Arabidopsis thaliana and human populations.

This paper introduces a model-free, computationally efficient method for inferring population structure using network theory and genetic data, validated with human data and simulations.