Javier is a quantitative geneticist and biostatistician specialising in statistical genomics and computational methods for plant breeding. His research focuses on developing and improving genomic selection methods to enhance breeding decisions and accelerate genetic gain. His expertise spans genomic prediction, genomic mating, training population optimisation, variance component estimation, field trial simulation, and the statistical analysis of complex traits. Through collaborations with private breeding companies, he has developed practical statistical solutions tailored to real-world commercial breeding programmes.
Javier holds a Bachelor’s degree in Biotechnology from the University of León, a Master’s degree in Computational Biology from the Polytechnic University of Madrid, and a PhD in Quantitative Genetics and Biostatistics from the Polytechnic University of Madrid. His doctoral research was conducted at the Centre for Biotechnology and Genomics of Plants (CBGP). Since 2025, he has worked as a quantitative genetics consultant, supporting the development and application of statistical and genomic methods for breeding programmes.
Javier has developed several software tools for genomic analyses, including MateR, an R package implementing advanced genomic mating strategies, and has contributed to the development of TrainSel, a tool for training population optimisation. He has published extensively in quantitative genetics and statistical genomics and regularly presents his work at international scientific conferences.
Education & Career
- Bachelor’s degree in Biotechnology, University of León
- Master’s degree in Computational Biology, Polytechnic University of Madrid
- PhD in Quantitative Genetics and Biostatistics, Polytechnic University of Madrid
- Doctoral research at the Centre for Biotechnology and Genomics of Plants (CBGP)
- Quantitative Genetics Consultant (since 2025)
- Collaborator with commercial plant breeding companies, developing statistical methods for modern breeding programmes
- Developer of the MateR R package and contributor to TrainSel for training population optimisation
- Author of multiple peer-reviewed publications in quantitative genetics and statistical genomics
Research Focus
Javier’s research centres on applying quantitative genetics, statistical genomics, and computational methods to improve breeding strategies and accelerate genetic gain. His research interests include:
- Genomic prediction and genomic selection
- Quantitative genetics and statistical genomics
- Genomic mating strategies
- Training population optimisation
- Variance component estimation
- Field trial simulation and experimental design
- Complex trait analysis
- Statistical modelling for plant breeding
- Computational methods for breeding programmes
Professional Consultancy
Javier provides consultancy to commercial breeding organisations, supporting the design and implementation of statistical and genomic workflows. His consultancy expertise includes:
- Genomic prediction and genomic selection
- Quantitative genetics and breeding programme optimisation
- Statistical genomics and genomic data analysis
- Experimental design and field trial analysis
- Training population optimisation
- Genomic mating strategies
- Statistical modelling in R
- Reproducible genomic analysis workflows
Teaching & Skills
- Instructor on the annual Genomic Selection Course, Polytechnic University of Madrid
- Teaches quantitative genetics, genomic prediction, and statistical genomics
- Delivers specialist training for commercial breeding organisations
- Supervisor and mentor of Master’s and PhD students
- Experienced in developing practical, reproducible genomic analysis workflows in R
- Passionate about making advanced quantitative genetics and statistical methods accessible to researchers and plant breeders through hands-on, applied training
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