Márcio F. R. Resende

Single-kernel near-infrared spectroscopy enables haploid kernel sorting in field and sweet corn using high-oil haploid inducers across diverse donor-inducer combinations

This study shows a single-kernel NIR sorter can accurately identify haploid kernels in maize using a general model across diverse donor-inducer combinations.

InteracTor: Feature Engineering and Explainable AI for Profiling Protein Structure-Interaction-Function Relationships

InteracTor extracts 3D structural interaction features and uses XAI to improve protein family classification beyond primary/secondary structure features.

Integrating Phenomic Selection Using Single-Kernel Near-Infrared Spectroscopy and Genomic Selection for Corn Breeding Improvement

This study combines genomic and phenomic selection in corn breeding using single-kernel NIRS to improve predictive accuracy and reduce genotyping costs.

Intrinsic DNA motif-binding capability of OsCLSY3 guides female-preferential RNA-directed DNA methylation

The paper identifies a rice-specific mechanism for female-preferential RNA-directed DNA methylation mediated by OsCLSY3 recognizing a GC-rich DNA motif.

SimpleMating: R-package for prediction and optimization of breeding crosses using genomic selection

SimpleMating predicts and optimizes breeding crosses using genomic selection to maximize genetic gain while minimizing inbreeding in simulated maize breeding programs.

InteracTor: A new integrative feature extraction toolkit for improved characterization of protein structural properties

InteracTor extracts interatomic interaction features from protein 3D structures to improve characterization of structural properties and functional insights.

Genomic Prediction in Family Bulks Using Different Traits and Cross-Validations in Pine

This study evaluates genomic prediction in family bulks for loblolly pine, finding that GWFP outperforms individual GEBV predictions and is suitable for breeding programs using family-level selection.

Genomic prediction of autotetraploids; influence of relationship matrices, allele dosage, and continuous genotyping calls in phenotype prediction

This paper evaluates genomic prediction methods for autotetraploid blueberry using continuous genotyping and relationship matrices, finding marker-based models improve prediction accuracy and reduce computational time.

Integration of Dominance and Marker x Environment Interactions into Maize Genomic Prediction Models

This study improves genomic prediction models for maize hybrids by incorporating dominance effects and genotype-by-environment interactions, enhancing accuracy for grain yield and moisture.