- A comparison of methods for training population optimization in ...🔍
- Optimizing genetic prediction🔍
- Optimizing genomic prediction model given causal genes in a dairy ...🔍
- Optimizing the genetic prediction of the eye and hair color for North ...🔍
- Optimizing Genomic|Enabled Prediction in Small|Scale Maize ...🔍
- Optimization of deep learning models for the prediction of gene ...🔍
- Optimizing genomic reference populations to improve crossbred ...🔍
- Heuristic hyperparameter optimization of deep learning models for ...🔍
Optimizing genetic prediction
A comparison of methods for training population optimization in ...
We have defined genetic space as a multivariate space in which every genotype of a dataset is characterized by its genome-wide markers encoded ...
Optimizing genetic prediction: Define-by-run DL approach in DNA ...
The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm.
Optimizing genomic prediction model given causal genes in a dairy ...
In this study, we simulated pseudo-phenotypes under a variety of genetic architectures based on the real genotypes and phenotypes of a dairy cattle population.
Optimizing the genetic prediction of the eye and hair color for North ...
Predicting the eye and hair color from genotype became an established and widely used tool in forensic genetics, as well as in studies of ...
Optimizing Genomic-Enabled Prediction in Small-Scale Maize ...
This requires the use of optimized training populations, the inclusion of non-additive genetic effects in the prediction models, and environmental information ...
Optimization of deep learning models for the prediction of gene ...
Deep learning models are increasingly being used to interpret whole-slide images (WSIs) in digital pathology and to predict genetic mutations.
Optimizing genomic reference populations to improve crossbred ...
One way to achieve this is to use genomic prediction with a crossbred reference population. A crossbred reference population benefits from ...
Heuristic hyperparameter optimization of deep learning models for ...
To date, most DL approaches used for genomic prediction have concentrated on identifying suitable hyperparameters by exploring discrete options from a subset of ...
An optimized prediction framework to assess the functional impact of ...
Prediction of phenotypic consequences of mutations constitutes an important aspect of precision medicine. Current computational tools mostly ...
Genomic prediction of optimal cross combinations to accelerate ...
Most often, these crossing decisions are made on the basis of pedigrees, genetic diversity, yield, and agronomic traits (Bernardo, 2003; Gaynor ...
Training Population Optimization for Genomic Selection - ACSESS
We used the CDmean, defined as the squared correlation between the true and the predicted contrast of genetic values, and the PEVmean, defined ...
(PDF) Optimizing genetic prediction: Define-by-run DL approach in ...
Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization ...
Application of optimization and simulation models in Genomic ...
A hybrid approach of support vector regression with genetic algorithm optimization for aquaculture water quality prediction. Mathematical and Computer ...
Using genetic programming to predict and optimize protein function
Protein engineers conventionally use tools such as Directed Evolution to find new proteins with better functionalities and traits.
Optimizing Selection and Mating in Genomic Selection with a Look ...
Our contribution is to define a new “look-ahead” metric for assessing selection decisions, which evaluates the probability of achieving high genetic gains.
Development and optimization of expected cross value for mate ...
The QU-GENE engine and QuLinePlus proposed by Ali et al. (2020) were used to simulate initial populations and the progeny in the subsequent ...
Prediction of and genetic algorithm optimization on data induced ...
Highlights. •. A method for predicting the uncertainty reduction from an integral experiment on an application is verified. •. A global optimization software ...
Genomic prediction and training set optimization in a structured ...
The impact of genetic structure on TRS optimization was investigated using structure-based optimization scenarios (Fig. 6). Two optimization ...
Optimized Breeding Selection via Genomic Prediction - Golden Helix
For example, the cattle industry uses genomic prediction to improve beef quality and palatability as well as improve dairy production (1,2). By ...
Efficient search, mapping, and optimization of multi‐protein genetic ...
First, we employ predictive biophysical models to map the relationship between sequence and expression and to develop an automated search algorithm that ...