Results 101 to 110 of about 3,820,379 (274)

Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data [PDF]

open access: yes, 2014
We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as ...
arxiv   +1 more source

ShinyGPAS: interactive genomic prediction accuracy simulator based on deterministic formulas

open access: yesGenetics Selection Evolution, 2017
Background Deterministic formulas for the accuracy of genomic predictions highlight the relationships among prediction accuracy and potential factors influencing prediction accuracy prior to performing computationally intensive cross-validation ...
Gota Morota
doaj   +1 more source

Efficacy of plant breeding using genomic information

open access: yesThe Plant Genome, 2023
Genomic selection (GS) proposed by Meuwissen et al. more than 20 years ago, is revolutionizing plant and animal breeding. Although GS has been widely accepted and applied to plant and animal breeding, there are many factors affecting its efficacy.
Osval A. Montesinos‐López   +8 more
doaj   +1 more source

Genome-wide nucleotide-resolution model of single-strand break site reveals species evolutionary hierarchy [PDF]

open access: yesarXiv, 2022
Single-strand breaks (SSBs) are the major DNA damage in the genome arising spontaneously as the outcome of genotoxins and intermediates of DNA transactions. SSBs play a crucial role in various biological processes and show a non-random distribution in the genome.
arxiv  

Empowering global rice breeding programs using genomic selection. [W291] [PDF]

open access: yes, 2020
Rice is the staple food for half of the global population and irrigated rice contributes 70% of total rice produced. Given the strategic importance of this market segment to global food security, the irrigated rice breeding program at IRRI is mandated to
Arbelaez Velez, Juan David   +11 more
core  

Optimizing genomic prediction for Australian Red dairy cattle.

open access: yesJournal of Dairy Science, 2020
The reliability of genomic prediction is influenced by several factors, including the size of the reference population, which makes genomic prediction for breeds with a relatively small population size challenging, such as Australian Red dairy cattle ...
I. Berg   +4 more
semanticscholar   +1 more source

Haplotype analysis of genomic prediction by incorporating genomic pathway information based on high-density SNP marker in Chinese yellow-feathered chicken

open access: yesPoultry Science, 2023
: Genomic selection using single nucleotide polymorphism (SNP) markers is now intensively investigated in breeding and has been widely utilized for genetic improvement.
Haoqiang Ye   +10 more
doaj  

A Guide on Deep Learning for Complex Trait Genomic Prediction

open access: yesGenes, 2019
Deep learning (DL) has emerged as a powerful tool to make accurate predictions from complex data such as image, text, or video. However, its ability to predict phenotypic values from molecular data is less well studied.
M. Pérez-Enciso, L. Zingaretti
semanticscholar   +1 more source

Genomic prediction of maize microphenotypes provides insights for optimizing selection and mining diversity

open access: yesPlant Biotechnology Journal, 2020
Summary Effective evaluation of millions of crop genetic stocks is an essential component of exploiting genetic diversity to achieve global food security.
Xiaoqing Yu   +10 more
semanticscholar   +1 more source

Learning Clinical Outcomes from Heterogeneous Genomic Data Sources [PDF]

open access: yesarXiv, 2019
Translating the vast data generated by genomic platforms into reliable predictions of clinical outcomes remains a critical challenge in realizing the promise of genomic medicine largely due to small number of independent samples. In this paper, we show that neural networks can be trained to predict clinical outcomes using heterogeneous genomic data ...
arxiv  

Home - About - Disclaimer - Privacy