Marc Robinson-Rechavi

Sex-Specific Changes In Gene Expression And Delayed Sex Differentiation In Response To Estrogen Pollution In Grayling (Salmonidae)

This study shows that estrogen pollution affects gene expression and delays sex differentiation in grayling, with stronger effects in females and some feminization of males.

Tissue-specificity of gene expression diverges slowly between orthologs, and rapidly between paralogs

The paper shows orthologs conserve tissue-specificity across species, while paralogs diverge rapidly, supporting a model where duplication leads to new functions through expression divergence.

State aggregation for fast likelihood computations in molecular evolution

This paper introduces state aggregation to speed up likelihood computations in codon models without introducing bias, showing up to 6.8x speedup and high correlation with full likelihood results.

A benchmark of gene expression tissue-specificity metrics

This study benchmarks nine gene expression tissue-specificity metrics to evaluate their ability to distinguish gene categories, robustness to tissue selection, and capture of evolutionary conservation signal.

Inference of evolutionary forces acting on human biological pathways

The paper introduces a new statistical method, 2DNS, to detect selection acting on human biological pathways by analyzing genetic diversity and evolutionary constraints.

Tissue-specific evolution of protein coding genes in human and mouse

The paper examines how protein-coding gene evolution varies across tissues in humans and mice, finding that purifying selection and tissue-specific expression patterns influence evolutionary rates.

Detecting patterns of species diversification in the presence of both rate shifts and mass extinctions

The paper evaluates two methods for detecting diversification patterns under scenarios with rate shifts and mass extinctions, finding lineage shifts are better detected than mass extinctions.

What to compare and how: comparative transcriptomics for Evo-Devo

The paper reviews challenges in comparative transcriptomics for Evo-Devo and discusses efforts to address them through bioinformatics tools and the Bgee database.