Nothing Special   »   [go: up one dir, main page]

Yang et al., 2007 - Google Patents

Bayesian shrinkage analysis of quantitative trait loci for dynamic traits

Yang et al., 2007

View HTML
Document ID
11297068915699665606
Author
Yang R
Xu S
Publication year
Publication venue
Genetics

External Links

Snippet

Many quantitative traits are measured repeatedly during the life of an organism. Such traits are called dynamic traits. The pattern of the changes of a dynamic trait is called the growth trajectory. Studying the growth trajectory may enhance our understanding of the genetic …
Continue reading at www.ncbi.nlm.nih.gov (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/12—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for modelling or simulation in systems biology, e.g. probabilistic or dynamic models, gene-regulatory networks, protein interaction networks or metabolic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/22—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for sequence comparison involving nucleotides or amino acids, e.g. homology search, motif or SNP [Single-Nucleotide Polymorphism] discovery or sequence alignment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30386—Retrieval requests
    • G06F17/30424—Query processing
    • G06F17/30533—Other types of queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/26—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for data visualisation, e.g. graphics generation, display of maps or networks or other visual representations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30—Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data

Similar Documents

Publication Publication Date Title
Yang et al. Bayesian shrinkage analysis of quantitative trait loci for dynamic traits
Yi et al. Stochastic search variable selection for identifying multiple quantitative trait loci
Frachon et al. Intermediate degrees of synergistic pleiotropy drive adaptive evolution in ecological time
Aguillon et al. Deconstructing isolation-by-distance: The genomic consequences of limited dispersal
Resende Jr et al. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.)
Yi et al. Bayesian LASSO for quantitative trait loci mapping
Cheema et al. Computational approaches and software tools for genetic linkage map estimation in plants
Ma et al. Functional mapping of quantitative trait loci underlying the character process: a theoretical framework
Yi et al. Bayesian model choice and search strategies for mapping interacting quantitative trait loci
Blischak et al. SNP genotyping and parameter estimation in polyploids using low-coverage sequencing data
Legarra et al. Performance of genomic selection in mice
Rosenberg et al. Genealogical trees, coalescent theory and the analysis of genetic polymorphisms
US20220361428A1 (en) Systems and methods for use in identifying multiple genome edits and predicting the aggregate effects of the identified genome edits
Wang Computationally efficient sibship and parentage assignment from multilocus marker data
Stephan et al. A random forest approach to capture genetic effects in the presence of population structure
Yi et al. Bayesian mapping of quantitative trait loci for complex binary traits
Knowles The burgeoning field of statistical phylogeography
Xu et al. Genomewide analysis of epistatic effects for quantitative traits in barley
Mulder et al. Prediction of breeding values and selection responses with genetic heterogeneity of environmental variance
Zhao et al. A non-stationary model for functional mapping of complex traits
Wu et al. A general framework for analyzing the genetic architecture of developmental characteristics
Smouse et al. Parentage analysis in Chamaelirium luteum (L.) Gray (Liliaceae): why do some males have higher reproductive contributions?
Wu et al. Functional mapping of quantitative trait loci underlying growth trajectories using a transform-both-sides logistic model
Yang et al. Mapping quantitative trait loci for longitudinal traits in line crosses
Dos Santos et al. Novel bayesian networks for genomic prediction of developmental traits in biomass sorghum