Non-linear tests for identifying differentially expressed genes or genetic networks.
about
Ten years of pathway analysis: current approaches and outstanding challengesHarnessing the complexity of gene expression data from cancer: from single gene to structural pathway methodsConstruction of a reference gene association network from multiple profiling data: application to data analysis.Pathway analysis of expression data: deciphering functional building blocks of complex diseases.Assessment method for a power analysis to identify differentially expressed pathways.A de novo transcriptome analysis shows that modulation of the JAK-STAT signaling pathway by salmonid alphavirus subtype 3 favors virus replication in macrophage/dendritic-like TO-cells.A decision analysis model for KEGG pathway analysisIdentification of differential gene pathways with principal component analysisPost-transcriptional knowledge in pathway analysis increases the accuracy of phenotypes classification.Gene set analysis for self-contained tests: complex null and specific alternative hypotheses.Unite and conquer: univariate and multivariate approaches for finding differentially expressed gene sets.A flexible nonparametric approach to find candidate genes associated with disease in microarray experiments.Genetic network analysis by quasi-bayesian method.Detecting Disease Specific Pathway Substructures through an Integrated Systems Biology Approach.
P2860
Q29615564-FB60C205-7958-4762-BDB4-89E7CCA42780Q30580995-2FACAE9C-BECF-4659-9541-152B9F49FFF4Q31127118-834851A7-6BB3-43CD-98E6-65772119AD60Q33921210-9DEA62D4-0FA9-41BB-AFCD-56A16DE5B46CQ34281947-4460D8BF-6FD5-42F8-A813-4E58CB14CCB7Q36026936-6A84DD9D-C42E-4DA6-B45F-08196898B39FQ36156411-CFD2B6EB-24EF-4312-BE8E-37AA24FBBFD4Q37319658-F8015250-D22A-42D8-B371-003039FD64B6Q39701059-8E43B73B-5ED5-4C8E-8766-5C078B8E8A30Q42027546-58B52485-75D1-414C-BC03-E7AADEC3AA56Q42541255-0ECC6613-5988-461E-8836-8029C3CE385AQ43940954-C184D153-9181-4C32-B2C5-DE5C4EAB9B2CQ51813227-E929BE04-F398-4DE7-BA86-726C17407810Q54941802-2ABED7D0-274C-483D-BFAC-7602E37DABAB
P2860
Non-linear tests for identifying differentially expressed genes or genetic networks.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh-hant
name
Non-linear tests for identifying differentially expressed genes or genetic networks.
@en
Non-linear tests for identifying differentially expressed genes or genetic networks.
@nl
type
label
Non-linear tests for identifying differentially expressed genes or genetic networks.
@en
Non-linear tests for identifying differentially expressed genes or genetic networks.
@nl
prefLabel
Non-linear tests for identifying differentially expressed genes or genetic networks.
@en
Non-linear tests for identifying differentially expressed genes or genetic networks.
@nl
P356
P1433
P1476
Non-linear tests for identifying differentially expressed genes or genetic networks.
@en
P2093
P304
P356
10.1093/BIOINFORMATICS/BTL034
P407
P577
2006-02-10T00:00:00Z