Alencar Xavier
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
Publications
52
Citations
1,295
Est. group size
~1
Recurring co-author estimate
Active years
14
Publishing since 2013
Alencar Xavier works on genomic prediction and machine learning methods for plant and animal breeding, with a strong focus on maize and soybean. Their work combines statistical genetics, environmental data, and computational tools to predict traits like crop yield, disease resistance, and genetic markers, and includes some applications extending to human genetics (e.g., Alzheimer's disease marker identification). This research helps breeders use genetic and environmental information to make better predictions about which plant varieties will perform well.
Publication output has been relatively steady but modest over the last decade, with a slight dip around 2020-2023 followed by a recent uptick in 2024-2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Genomes to fields 2024 maize genotype by environment prediction competition
BMC Research Notes · 2026
- Machine learning after a decade: is it still a missing keystone in genomic-based plant breeding?
Artificial Intelligence Review · 2025
- Scalable Prediction of Northern Corn Leaf Blight and Gray Leaf Spot Diseases to Predict Fungicide Spray Timing in Corn
Agronomy · 2025
- Comparative Analysis of Machine Learning Algorithms for Identifying Genetic Markers Linked to Alzheimer’s Disease
Lecture notes in computer science · 2025
- pegs: Pseudo-Expectation Gauss-Seidel
2025
- GIS‐based G × E modeling of maize hybrids through enviromic markers engineering
New Phytologist · 2024
- Global genotype by environment prediction competition reveals that diverse modeling strategies can deliver satisfactory maize yield estimates
Genetics · 2024
- Megavariate methods capture complex genotype-by-environment interactions
Genetics · 2024
- Global Genotype by Environment Prediction Competition Reveals That Diverse Modeling Strategies Can Deliver Satisfactory Maize Yield Estimates
bioRxiv (Cold Spring Harbor Laboratory) · 2024
- Editorial: Enriching genomic breeding with environmental covariates, crop models, and high-throughput phenotyping
Frontiers in Genetics · 2024
- Enhanced Data Pre-processing for the Identification of Alzheimer’s Disease-Associated SNPs
medRxiv · 2024
- A marker weighting approach for enhancing within-family accuracy in genomic prediction
G3 Genes Genomes Genetics · 2023
- An assessment of the interaction between sucrose content and seed quality traits in soybeans
Crop Science · 2023
- Two decades of association mapping: Insights on disease resistance in major crops
Frontiers in Plant Science · 2022
- High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean (<i>Glycine max</i>) nested association mapping population
Genetics · 2022
- G3 Genes Genomes Genetics×6
- Genetics×4
- Agronomy×3
- BMC Bioinformatics×3
- Crop Science×3
- Sirlene Fernandes Lázaro
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Gabriel Soares Campos
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Gerardo Cornelio Mamani Mamani
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- André Campêlo Araujo
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
- Ayooluwa O Ojo
Biochemistry, Genetics and Molecular Biology · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile