Carlos Martí‐Gómez

GaugeFixer is a Python package that efficiently fixes gauge freedoms in sequence-function models, enabling faster and more scalable analysis of large parameter sets.

This paper introduces a framework to infer fitness landscapes with structured epistasis and applies it to protein and RNA mutagenesis data, revealing complex genetic interactions.

The paper establishes the relationship between Gaussian process priors and regularized regression in sequence-to-function mapping, showing how to construct regularizers that correspond to explicit Gaussian process priors and characterize implicit function space priors.

The paper introduces interpretable Gaussian process models for sequence-function relationships, capturing epistasis and achieving superior predictive performance on large biological datasets.

The paper identifies cryptic genetic variants in tomato that drive phenotypic change through hierarchical epistasis in a gene regulatory network.

gpmap-tools uses Gaussian processes to infer and visualize genotype-phenotype maps with higher-order epistasis; across 262,144 Shine-Dalgarno variants it reveals register-specific peaks linked by three-nucleotide-offset ridges.

The paper investigates alternative splicing (AS) in cardiac pathophysiology, identifying PTBP1 as a key regulator of AS changes that drive cardiac hypertrophy and diastolic dysfunction.

dSreg is a Bayesian model that integrates RNA-seq and regulatory data to identify alternative splicing changes and RNA binding protein activity, improving sensitivity and specificity.

The paper presents a high-quality zucchini genome assembly and identifies a whole genome duplication in the Cucurbita genus.