Luis G. Serrano

The paper engineers EV-mimetic vesicles to study protein loading and uptake, finding that protein properties influence incorporation and biodistribution.

The paper develops a mathematical model of the IL-10 signaling pathway to explain its pleiotropic effects and suggests implications for IL-10-based therapies.

The paper estimates splicing factor activity from exon inclusion changes, identifying cancer-related splicing programs and their association with patient survival and cancer hallmarks.

This paper evaluates a non-antibiotic live biotherapeutic for treating Pseudomonas aeruginosa ventilator-associated pneumonia in preclinical models, showing reduced biofilm and bacterial load with improved safety and immunomodulatory effects.

The paper uses single-cell perturbation screens to decode splicing factor regulatory networks, revealing cross-regulatory loops and MYC's role in linking cancer mutations to splicing regulation.

This study maps essentiality in Mycoplasma pneumoniae at near-single-nucleotide resolution using transposon libraries and k-means clustering, revealing essential domains and structural regions.

The paper evaluates AI and first-principle methods for protein redesign, showing hybrid approaches are most reliable, while inverse folding tools and force fields have specific strengths and limitations.

The paper investigates how arboviruses like chikungunya virus maintain persistent infections in mosquito cells through translational repression of viral RNA without affecting host cell fitness.

This study identifies the structural mechanism by which Wnt7a binds to exosomes for secretion, showing it is independent of palmitoylation and involves a dilysine motif interacting with COPB2.

The paper introduces MadraX, a differentiable force field implemented as a PyTorch module to enable end-to-end integration with deep learning algorithms in structural biology.

The paper introduces a workflow for IP-MS data to detect differentially present bait proteoforms, offering insights into protein function through peptidoform analysis.

The paper uses protein-to-mRNA ratios from human tissues to develop a codon optimizer algorithm that improves tissue-specific protein expression.

robustica computes robust independent components with customizable clustering and distance metrics, showing improved precision and efficiency in analyzing tumor samples.

This study analyzes the adaptability and robustness of Mycoplasma pneumoniae's central carbon metabolism using metabolomics data and a dynamic model, identifying key control hubs.

The paper identifies Srrm3-dependent microexons as critical for photoreceptor function and vision, showing their role in outer segment maintenance and their loss leading to blindness.

pyFoldX enables integrative analysis of protein structures using FoldX, improving handling of multiple structures and integration with Python data analysis tools.

This study shows that human viruses adapt their codon usage to match the translational machinery of the tissues they infect, with SARS-CoV-2 showing improved adaptation to upper respiratory airways.

The paper identifies and corrects common nomenclature errors in lox site mutants, highlighting their impact on experimental design and replication.

This study uses a genome-scale metabolic model to design serum-free media for Mycoplasma pneumoniae, enabling growth and supporting vaccine production.

The paper identifies C-terminal amino acid biases in bacterial genomes and shows their impact on protein expression levels in M. pneumoniae mutants.

The paper examines translational efficiency across healthy and tumor tissues, finding it correlates with proliferation and specific codon usage patterns.

The paper analyzes gene essentiality across 47 bacterial species, finding a correlation between genome size and essential gene functions, and identifies conserved non-essential genes.

VarQ assesses the functional impact of single amino acid substitutions on protein activity, folding, and interactions using curated variants.