Alejandro Maass

The paper identifies global hotspots of plankton-based ecosystem services by integrating satellite data with metagenomic functions and machine learning.

This study examines how Enterococcus faecalis adjusts its metabolism and transcriptional response when exposed to iron under glutathione deficiency, revealing compensatory mechanisms for oxidative stress.

The paper develops a computational framework to model soil microbiome metabolic potential in the Atacama Desert, identifying key species and functions across different environmental conditions.

The paper constructs a database of thermal performance curves for species across multiple domains, enabling ecological predictions and integration with environmental data.

The paper compiles a database of thermal response curves across species and performance tasks, revealing universal scaling relationships in thermal performance.

The paper develops a general model for genomic trait evolution that explains dynamics across diverse taxa and fits experimental and observational data.

The paper develops a genome-scale metabolic model for ocean microbial communities to infer metabolic processes and viral impacts on biogeochemical cycles.

This study identifies physiological and genetic adaptations in Cistanthe longiscapa that enable survival in the Atacama Desert, including CAM metabolism and expanded gene families.

The paper introduces a method to explore abundance-growth space for microbial communities, revealing abundance-dependent metabolic phenotypes through constraint-based modeling.

The paper discovers and validates 50,000 high-quality SNPs in Nile tilapia through whole-genome resequencing of 326 individuals, useful for genomic selection and trait analysis.

The paper uses whole-genome sequencing to fine-map sex determination genes in Nile tilapia, identifying anti-Mullerian hormone as a major gene.

The paper presents the whole genome sequences of 11 Mapuche-Huilliche individuals, identifying novel variants and structural events, and highlights their potential relevance to disease susceptibility in admixed populations.

FAST-SG is an alignment-free algorithm for hybrid genome assembly that outperforms short read aligners and enables accurate genome reconstruction with low coverage and resources.

This paper presents the genome sequence of Penicillium purpurogenum, showing a high gene dosage for lignocellulolytic enzymes and validating its potential for industrial applications.

The paper introduces FAASG, an initiative to study salmonid genomes to understand phenotypic variation and improve aquaculture and conservation.