A5071478762- Genetic Mapping and Diversity in Plants and Animals
- Genetic and phenotypic traits in livestock
- Genetics and Plant Breeding
- Wheat and Barley Genetics and Pathology
- Gene expression and cancer classification
- Data Mining Algorithms and Applications
- Neural Networks and Applications
- Bayesian Methods and Mixture Models
- Plant Pathogens and Resistance
- Plant Disease Resistance and Genetics
- Genetic diversity and population structure
- Potato Plant Research
- Fuzzy Logic and Control Systems
- Advanced Statistical Methods and Models
- Evolutionary Algorithms and Applications
- Fuzzy Systems and Optimization
- Statistical Distribution Estimation and Applications
- Agricultural pest management studies
- Radiomics and Machine Learning in Medical Imaging
- Statistical Methods and Inference
- Bioinformatics and Genomic Networks
- Cassava research and cyanide
- Advanced Clustering Algorithms Research
- Statistical Methods and Bayesian Inference
- Data Management and Algorithms
National Marrow Donor Program
2021-2025
University College Dublin
2019-2024
Michigan State University
2017-2021
Cornell University
2013-2019
Statistical Research (United States)
2018-2019
Biogen (United States)
2017
New York State College of Agriculture & Life Sciences
2017
Bowling Green State University
2013
Ohio Northern University
2011
University College London
1986
Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the value of individuals population. GS has been shown improve efficiency dairy cattle and several crop plant species, here we evaluate for first time its efficacy inbred lines rice. We performed association study (GWAS) conjunction with five-fold cross-validation on population 363 elite from International Rice Research Institute's (IRRI) irrigated rice program herein report results. The was...
Population structure must be evaluated before optimization of the training set population. Maximizing phenotypic variance captured by is important for optimal performance. The (TRS) in genomic selection has received much interest both animal and plant breeding, because it critical to accuracy prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean coefficient determination (CDmean), predictor error (PEVmean), CDmean (StratCDmean) random were...
Abstract This study examines genomic prediction within 8416 Mexican landrace accessions and 2403 Iranian stored in gene banks. The collections were evaluated separate field trials, including an optimum environment for several traits, two environments (drought, D heat, H) the highly heritable days to heading (DTH), maturity (DTM). Analyses accounting not population structure performed. Genomic models include genotype × interaction (G E). Two alternative strategies studied: (1) random...
In this article, we imagine a breeding scenario with population of individuals that have been genotyped but not phenotyped. We derived computationally efficient statistic uses genetic information to measure the reliability genomic estimated values (GEBV) for given set (test set) based on training individuals. used algorithm scheme find an optimized from larger candidate This subset was phenotyped create in selection model estimate GEBV test set. Our results show that, compared random sample...
The purpose of breeding programs is to obtain sustainable gains in multiple traits while controlling the loss genetic variation. decisions at each cycle involve multiple, usually competing, objectives; these complex can be supported by insights that are gained applying multi-objective optimization principles breeding. discussion this manuscript includes definition several optimized approaches within phenotypic or genomic frameworks and comparison with standard multi-trait schemes such as...
Phenotyping is the current bottleneck in plant breeding, especially because next-generation sequencing has decreased genotyping cost more than 100.000 fold last 20 years. Therefore, of phenotyping needs to be optimized within a breeding program. When designing implementation genomic selection scheme into cycle, breeders need select optimal method for (1) selecting training populations that maximize prediction accuracy and (2) reduce while improving precision. In this article, we compared...
Selection in breeding programs can be done by using phenotypes (phenotypic selection), pedigree relationship (breeding value selection) or molecular markers (marker assisted selection genomic selection). All these methods are based on truncation selection, focusing the best performance of parents before mating. In this article we proposed an approach to breeding, named mating, which focuses mating instead selection. Genomic uses information a similar fashion but includes complementation...
Maximizing CDmean and Avg_GRM_self were the best criteria for training set optimization. A size of 50-55% (targeted) or 65-85% (untargeted) is needed to obtain 95% accuracy. With advent genomic selection (GS) as a widespread breeding tool, mechanisms efficiently design an optimal GS models became more relevant, since they allow maximizing accuracy while minimizing phenotyping costs. The literature described many optimization methods, but there lack comprehensive comparison among them. This...
Genomic selection (GS) promises to accelerate genetic gain in plant breeding programs especially for crop species such as cassava that have long cycles. Practically, implement GS breeding, it is necessary evaluate different models and develop suitable an optimized pipeline. In this paper, we compared (1) prediction accuracies from a single-trait (uT) multi-trait (MT) mixed model single-environment evaluation (Scenario 1), (2) compound symmetric multi-environment (uE) parameterized univariate...
To introduce new genetic diversity into the bread wheat gene pool from its progenitor, Aegilops tauschii (Coss.) Schmalh, 33 primary synthetic hexaploid genotypes (SYN) were crossed to 20 spring (BW) cultivars at International Wheat and Maize Improvement Center. Modified single seed descent was used develop 97 populations with 50 individuals per population using first back-cross, biparental, three-way crosses. Individuals each cross selected for short stature, early heading, flowering...
Genomic selection (GS) is becoming an essential tool in breeding programs due to its role increasing genetic gain per unit time. The design of the training set (TRS) GS one key steps implementation plant and animal mainly because (i) TRS optimization critical for efficiency effectiveness GS, (ii) breeders test genotypes multi-year multi-location trials select best-performing ones. In this framework, can help decrease number be tested and, therefore, reduce phenotyping cost time, (iii) we...
We found two loci on chromosomes 2BS and 6AL that significantly contribute to stripe rust resistance in current European winter wheat germplasm. Stripe or yellow rust, caused by the fungus Puccinia striiformis Westend f. sp. tritici, is one of most destructive diseases. Sustainable management can be achieved through deployment resistant cultivars. To detect effective for use breeding programs, an association mapping panel 230 cultivars lines from Northern Central Europe was employed....
In plant and animal breeding studies a distinction is made between the genetic value (additive plus epistatic effects) of an individual since it expected that some effects will be lost due to recombination. this article, we argue breeder can take advantage marker in regions low The models introduced here aim estimate local line heritability by using map information combining additive effects. To end, have used semiparametric mixed with multiple genomic relationship matrices hierarchical...
Random forests (RF) was used to correlate spectral responses known wet chemistry carotenoid concentrations including total content (TCC), all-trans β-carotene (ATBC), violaxanthin (VIO), lutein (LUT), 15-cis beta-carotene (15CBC), 13-cis (13CBC), alpha-carotene (AC), 9-cis (9CBC), and phytoene (PHY) from laboratory analysis of 173 cassava root samples in Columbia. The cross-validated correlations between the actual estimated values using RF ranged 0.62 PHY 0.97 ATBC. developed models were...
Olive (Olea europaea L.) is one of the most economically and historically important fruit crops worldwide. Genetic progress for valuable agronomic traits has been slow in olive despite its importance benefits. Advances next generation sequencing technologies provide inexpensive highly reproducible genotyping approaches such as Genotyping by Sequencing, enabling genome wide association study (GWAS). Here we present first comprehensive GWAS on using GBS. A total 183 accessions (FULL panel)...
Genomic selection involves choosing as parents those elite individuals with the higher genomic estimated breeding values (GEBV) to accelerate speed of genetic improvement in domestic animals. But after multi-generation selection, rate inbreeding and occurrence homozygous harmful alleles might increase, which would reduce performance diversity. To mitigate above problems, we can utilize mating (GM) based upon optimal mate allocation construct best genotypic combinations next generation. In...
Standard statistical methods applied to matrix random variables often fail describethe underlying structure in multiway data sets. After a review of the essential background material,this paper introduces notion array variate variable. A normal randomvariable is dened and method for estimating parameters distributionis given. We introduce technique called slicing covariance highdimensional data. Finally, principal component analysis classication techniques are developedfor observations high...
Abstract Optimal subset selection is an important task that has numerous algorithms designed for it and many application areas. STPGA contains a special genetic algorithm supplemented with tabu memory property (that keeps track of previously tried solutions their fitness number iterations), regression the on coding used to form ideal estimated solution (look ahead property) search generic optimal problems. I have initially developed programs specific problem selecting training populations...
A major barrier to the wider use of supervised learning in emerging applications, such as genomic selection, is lack sufficient and representative labeled data train prediction models. The amount quality training many applications usually limited therefore careful selection examples be can useful for improving accuracies predictive tasks. In this paper, we present an R package, TrainSel, which provides flexible, efficient, easy-to-use tools that used populations (STP). We illustrate its use,...
Abstract The objectives of this study were to apply alternative machine learning (ML) algorithms predict consumers’ garment fit satisfactions (real satisfaction [RFS]) and compare the efficiencies these RFS. Skirts made from different fabrics used as test garments. Mechanical properties skirts’ assigned predictor variables estimate Study participants’ virtual body models created by using 3D scanner for fitting. Each participant physically tried on skirts evaluated fit. Participants also...