PACK: Profile Analysis using Clustering and Kurtosis to find molecular classifiers in cancer.
about
Prolactin-induced protein mediates cell invasion and regulates integrin signaling in estrogen receptor-negative breast cancerDART: Denoising Algorithm based on Relevance network Topology improves molecular pathway activity inferenceGene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB familyDetection of patient subgroups with differential expression in omics data: a comprehensive comparison of univariate measuresThe genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroupsReduced androgen receptor expression accelerates the onset of ERBB2 induced breast tumors in female mice.SIBER: systematic identification of bimodally expressed genes using RNAseq dataThe bimodality index: a criterion for discovering and ranking bimodal signatures from cancer gene expression profiling dataBimodal gene expression patterns in breast cancerComparison of scores for bimodality of gene expression distributions and genome-wide evaluation of the prognostic relevance of high-scoring genes.Increased entropy of signal transduction in the cancer metastasis phenotype.Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modulesCommon germ-line polymorphism of C1QA and breast cancer survivalThe most informative spacing test effectively discovers biologically relevant outliers or multiple modes in expressionA comparison of feature selection and classification methods in DNA methylation studies using the Illumina Infinium platform.A feedback loop between androgen receptor and ERK signaling in estrogen receptor-negative breast cancer.MMP1 bimodal expression and differential response to inflammatory mediators is linked to promoter polymorphisms.A peculiar mutation spectrum emerging from young peruvian patients with hepatocellular carcinoma.An atypical age-specific pattern of hepatocellular carcinoma in Peru: a threat for Andean populations.Denoising perturbation signatures reveal an actionable AKT-signaling gene module underlying a poor clinical outcome in endocrine-treated ER+ breast cancer.Synergy between inhibitors of androgen receptor and MEK has therapeutic implications in estrogen receptor-negative breast cancer.Cross-regulation between FOXA1 and ErbB2 signaling in estrogen receptor-negative breast cancerOutlier analysis of functional genomic profiles enriches for oncology targets and enables precision medicine.Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation.An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer.A robust classifier of high predictive value to identify good prognosis patients in ER-negative breast cancer.Basal phenotype breast cancer: implications for treatment and prognosis.Benign and malignant apocrine lesions of the breast.Targeted BMI1 inhibition impairs tumor growth in lung adenocarcinomas with low CEBPα expression.A functionally significant cross-talk between androgen receptor and ErbB2 pathways in estrogen receptor negative breast cancer.C1orf64 is a novel androgen receptor target gene and coregulator that interacts with 14-3-3 protein in breast cancer.Rab25 acts as an oncogene in luminal B breast cancer and is causally associated with Snail driven EMT.A variational Bayes beta mixture model for feature selection in DNA methylation studies.Semiparametric tests for identifying differentially methylated loci with case-control designs using Illumina arrays.Gene-sharing networks reveal organizing principles of transcriptomes in Arabidopsis and other multicellular organisms.Genes and functions from breast cancer signatures.On the role of extrinsic noise in microRNA-mediated bimodal gene expression.
P2860
Q21195199-207F311B-CB01-42FA-A1B6-C2070D29D149Q21284334-7A8ED86B-9C74-4E0D-ABCC-B06CF30447B6Q28258227-9B7F6AE3-ACE4-42D8-86C3-95AE9A9F3D73Q28535386-8C8EE9A7-AF8E-43A0-9364-7F7AEE5D1F34Q29614700-09984312-9802-46DE-A7B5-627841DAEEE7Q30419961-24E3B7E5-A196-4016-9E27-36A33FB486ACQ30585364-B8DFEB98-AF7F-4C9B-8204-EEF72305BB33Q33498527-09F25501-69F5-4798-9950-33CB8873E614Q33531526-E6C70F93-847F-4BB4-9B97-58385EF1F942Q33586734-A77D2192-4151-4F1E-BF28-E99E9E0986F3Q33645935-9F36C24D-3487-4863-8FE3-7A2CB9397167Q33738285-121CCEA3-63B8-4838-8647-602C6FA718C9Q33794903-A227C1D9-55EF-482E-862B-B55F6120AE81Q33796443-CEE0AFF1-0175-49C8-8231-C0C55F2040CFQ34242041-939DC159-831A-49F4-8CF9-32775B615859Q34551559-4BE94011-45CB-422A-AAF5-65FE3811D389Q34581776-93E9C100-67CB-498F-BAE3-3B0389FE3C44Q34682006-D1560DB8-AC92-4DB9-8744-011E7733F1B8Q34807998-DFA9212B-1761-4D32-A3D3-81DD68AB002DQ35446364-E2E35205-B333-4673-99E3-7243A1407B9AQ35558993-E5026B9A-F04F-44A5-9C9F-9E03EFE9961AQ35949760-624A5F50-3277-413C-BAF7-6AD775E31BFCQ36050778-F7A98510-5CDF-4FEB-BAE8-631E1E0F23B9Q36245180-645F145D-67F2-48B9-9EE5-B7E56BBDC884Q36643153-56E525A2-71D7-4A7A-AD10-99DFFADEC672Q36955150-3CC22F81-C746-41AA-B1F6-4B9C448393B7Q37853555-75D334CE-9ED8-48F2-873E-B9E3D8554B81Q37982447-C9838B6D-94EF-4C45-B9D5-A4FC222A34FDQ38411881-95C3200A-CAF7-40C3-B867-53FA70BB609AQ38526448-3BA6336A-35F7-4841-BC64-0EA2DCE0AAE0Q41339016-8FEA72E5-B88B-4A2F-ADF1-570EB287972FQ42099513-EC7FE233-AEB4-45EC-A84F-056CBB141D94Q45823087-5B58779C-1098-4AE3-854F-1E188735DE12Q46049653-5F1EAC6C-35C3-4B53-A5BA-D30083349175Q51791978-9A934BB4-9DEC-467C-9FC3-BA4D208BB1D6Q52560707-884C47C3-B7CE-4F0E-93DC-7E401378545AQ54960322-AA170BFB-3484-4D15-A35C-83B553A68ACB
P2860
PACK: Profile Analysis using Clustering and Kurtosis to find molecular classifiers in cancer.
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-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
2006年學術文章
@zh-hant
name
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@en
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@nl
type
label
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@en
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@nl
prefLabel
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@en
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@nl
P2860
P50
P356
P1433
P1476
PACK: Profile Analysis using C ...... lecular classifiers in cancer.
@en
P2093
Andrew E Teschendorff
P2860
P304
P356
10.1093/BIOINFORMATICS/BTL174
P407
P577
2006-05-08T00:00:00Z