Results 11 to 20 of about 2,150,687 (292)

Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages [PDF]

open access: yes, 2020
Open Access Article; Published online: 11 Dec 2019Assembly of a training population (TP) is an important component of effective genomic selection‐based breeding programs.
Egesi, C.   +11 more
core   +1 more source

Assessment of landslide susceptibility mapping based on XGBoost model: A case study of Yanshan Township

open access: yesZhongguo dizhi zaihai yu fangzhi xuebao, 2023
Landslide susceptibility assessment forms the foundation for precise evaluation of landslide risk. To enhance the accuracy and robustness of landslide susceptibility mapping, a state-of-art machine learning algorithm named the extreme gradient boosting ...
Hongyang WU   +4 more
doaj   +1 more source

Fitting Prediction Rule Ensembles with R Package pre [PDF]

open access: yes, 2020
Prediction rule ensembles (PREs) are sparse collections of rules, offering highly interpretable regression and classification models. This paper presents the R package pre, which derives PREs through the methodology of Friedman and Popescu (2008).
Fokkema, Marjolein
core   +4 more sources

Differential Analysis and Prediction of Planar Shape at the Head and Tail Ends of Medium-Thickness Plate Rolling

open access: yesMetals, 2023
This paper aims to improve planar shape prediction accuracy in the rolling process of medium and thick plates. We present a model based on the strip method that addresses limitations in predicting planar shape variations at the head and tail ends of ...
Shiyu Yang, Hongmin Liu, Dongcheng Wang
doaj   +1 more source

Conotoxin Prediction: New Features to Increase Prediction Accuracy

open access: yesToxins, 2023
Conotoxins are toxic, disulfide-bond-rich peptides from cone snail venom that target a wide range of receptors and ion channels with multiple pathophysiological effects. Conotoxins have extraordinary potential for medical therapeutics that include cancer, microbial infections, epilepsy, autoimmune diseases, neurological conditions, and cardiovascular ...
Lyman K. Monroe   +8 more
openaire   +3 more sources

Pitfalls and Remedies for Cross Validation with Multi-trait Genomic Prediction Methods. [PDF]

open access: yes, 2019
Incorporating measurements on correlated traits into genomic prediction models can increase prediction accuracy and selection gain. However, multi-trait genomic prediction models are complex and prone to overfitting which may result in a loss of ...
Cheng, Hao, Runcie, Daniel
core   +1 more source

Prediction of HLA class II alleles using SNPs in an African population [PDF]

open access: yes, 2012
BACKGROUND: Despite the importance of the human leukocyte antigen (HLA) gene locus in research and clinical practice, direct HLA typing is laborious and expensive.
Adeyemo, Adebowale   +7 more
core   +7 more sources

Forecasting residue–residue contact prediction accuracy [PDF]

open access: yesBioinformatics, 2017
Abstract Motivation Apart from meta-predictors, most of today's methods for residue–residue contact prediction are based entirely on Direct Coupling Analysis (DCA) of correlated mutations in multiple sequence alignments (MSAs).
Wozniak, P.P.   +5 more
openaire   +3 more sources

Genomic Prediction Using LD-Based Haplotypes Inferred From High-Density Chip and Imputed Sequence Variants in Chinese Simmental Beef Cattle

open access: yesFrontiers in Genetics, 2021
A haplotype is defined as a combination of alleles at adjacent loci belonging to the same chromosome that can be transmitted as a unit. In this study, we used both the Illumina BovineHD chip (HD chip) and imputed whole-genome sequence (WGS) data to ...
Hongwei Li   +17 more
doaj   +1 more source

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC [PDF]

open access: yes, 2015
Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid over-fitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference.
Adams R.   +20 more
core   +2 more sources

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