Jorge Mestre‐Tomás

This paper introduces a data-driven framework for spatial thinning parameterization in ecological modelling, showing that optimal thinning parameters vary with species range size and that uniform approaches can lead to information loss or reduced spatial clustering.

This study compares two strategies for combining biologically replicated long-read RNA-seq data to identify transcripts, finding that 'Join & Call' is better for novel isoforms while 'Call & Join' is more efficient for large datasets.

The paper examines how mesopelagic fish diel vertical migration responded to Pleistocene climate changes in the Eastern Mediterranean, showing reduced migration during warming periods and implications for the biological pump.

Benchmarking six long-read RNA-seq protocol-platform combinations and 14 tools across human, mouse, and manatee shows read length and accuracy drive isoform detection, depth drives quantification.

SQANTI3 extends long-read transcriptome quality control with transcript-end subcategories, a short-read TSS ratio, rules or random-forest filters and a rescue module, raising SIRV-benchmarked F-score stepwise.

SQANTI-SIM simulates controlled transcript novelty for long-read RNA-seq data to benchmark transcriptome reconstruction pipelines.