Computational approaches to phenotyping: high-throughput phenomics.
about
A collaborative knowledge base for cognitive phenomicsGenome-wide pleiotropy of osteoporosis-related phenotypes: the Framingham StudyAnalysis of AML genes in dysregulated molecular networksMechanism-anchored profiling derived from epigenetic networks predicts outcome in acute lymphoblastic leukemiaComputer aided data acquisition tool for high-throughput phenotyping of plant populations.Using flatbed scanners to collect high-resolution time-lapsed images of the arabidopsis root gravitropic response.Identifying and mitigating biases in EHR laboratory tests.A high throughput semantic concept frequency based approach for patient identification: a case study using type 2 diabetes mellitus clinical notesThe Human Phenotype Ontology: a tool for annotating and analyzing human hereditary disease.Systems Epidemiology: What's in a Name?Identification of homogeneous genetic architecture of multiple genetically correlated traits by block clustering of genome-wide associationsArray comparative genomic hybridization and computational genome annotation in constitutional cytogenetics: suggesting candidate genes for novel submicroscopic chromosomal imbalance syndromes.Automated multidimensional phenotypic profiling using large public microarray repositoriesChemobehavioural phenomics and behaviour-based psychiatric drug discovery in the zebrafishGenetic risk factors for stroke in the genome-wide association era.SHIRAZ: an automated histology image annotation system for zebrafish phenomics.Application of Natural Language Processing to VA Electronic Health Records to Identify Phenotypic Characteristics for Clinical and Research PurposesCommon Variable Immunodeficiency Non-Infectious Disease Endotypes Redefined Using Unbiased Network Clustering in Large Electronic Datasets.Whole organ, venation and epidermal cell morphological variations are correlated in the leaves of Arabidopsis mutants.Analysis of AML Genes in Dysregulated Molecular Networks.
P2860
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P2860
Computational approaches to phenotyping: high-throughput phenomics.
description
2007 nî lūn-bûn
@nan
2007年の論文
@ja
2007年論文
@yue
2007年論文
@zh-hant
2007年論文
@zh-hk
2007年論文
@zh-mo
2007年論文
@zh-tw
2007年论文
@wuu
2007年论文
@zh
2007年论文
@zh-cn
name
Computational approaches to phenotyping: high-throughput phenomics.
@ast
Computational approaches to phenotyping: high-throughput phenomics.
@en
type
label
Computational approaches to phenotyping: high-throughput phenomics.
@ast
Computational approaches to phenotyping: high-throughput phenomics.
@en
prefLabel
Computational approaches to phenotyping: high-throughput phenomics.
@ast
Computational approaches to phenotyping: high-throughput phenomics.
@en
P2860
P1476
Computational approaches to phenotyping: high-throughput phenomics
@en
P2093
P2860
P356
10.1513/PATS.200607-142JG
P577
2007-01-01T00:00:00Z