Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures.
about
Suppression of breast tumor growth and metastasis by an engineered transcription factorComprehensive Molecular Portraits of Invasive Lobular Breast CancerThe transcription factors Snail and Slug activate the transforming growth factor-beta signaling pathway in breast cancerClinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival modelA pan-cancer analysis of prognostic genes.A data similarity-based strategy for meta-analysis of transcriptional profiles in cancer.A B-Cell Gene Signature Correlates With the Extent of Gluten-Induced Intestinal Injury in Celiac Disease.Transcriptomic classification of genetically engineered mouse models of breast cancer identifies human subtype counterparts.Prognostic B-cell signatures using mRNA-seq in patients with subtype-specific breast and ovarian cancer.Hormone receptor and ERBB2 status in gene expression profiles of human breast tumor samplesGenomic analysis identifies unique signatures predictive of brain, lung, and liver relapse.A novel model to combine clinical and pathway-based transcriptomic information for the prognosis prediction of breast cancerDesign of a multi-signature ensemble classifier predicting neuroblastoma patients' outcomeNovel role of Engrailed 1 as a prosurvival transcription factor in basal-like breast cancer and engineering of interference peptides block its oncogenic function.Predictions of the pathological response to neoadjuvant chemotherapy in patients with primary breast cancer using a data mining technique.Logic Learning Machine creates explicit and stable rules stratifying neuroblastoma patientsAn integrated genomics approach identifies drivers of proliferation in luminal-subtype human breast cancer.Genomic analyses across six cancer types identify basal-like breast cancer as a unique molecular entity.Dermcidin expression is associated with disease progression and survival among breast cancer patients.Evaluation of public cancer datasets and signatures identifies TP53 mutant signatures with robust prognostic and predictive valueIntratumoral heterogeneity in a Trp53-null mouse model of human breast cancer.GeneSigDB: a manually curated database and resource for analysis of gene expression signaturesA mammary stem cell population identified and characterized in late embryogenesis reveals similarities to human breast cancer.Gene expression in extratumoral microenvironment predicts clinical outcome in breast cancer patients.Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen.Response and survival of breast cancer intrinsic subtypes following multi-agent neoadjuvant chemotherapy.Molecular characterization of basal-like and non-basal-like triple-negative breast cancer.Radiation therapy following surgery for localized breast cancer: outcome prediction by classical prognostic factors and approximated genetic subtypes.Prognostic ability of EndoPredict compared to research-based versions of the PAM50 risk of recurrence (ROR) scores in node-positive, estrogen receptor-positive, and HER2-negative breast cancer. A GEICAM/9906 sub-studyNew algorithm for constructing area-based index with geographical heterogeneities and variable selection: An application to gastric cancer screening.Impact of tumor microenvironment and epithelial phenotypes on metabolism in breast cancerPractical implications of gene-expression-based assays for breast oncologists.Molecular Heterogeneity and Response to Neoadjuvant Human Epidermal Growth Factor Receptor 2 Targeting in CALGB 40601, a Randomized Phase III Trial of Paclitaxel Plus Trastuzumab With or Without Lapatinib.Predicting drug responsiveness in human cancers using genetically engineered mice.MR Imaging Radiomics Signatures for Predicting the Risk of Breast Cancer Recurrence as Given by Research Versions of MammaPrint, Oncotype DX, and PAM50 Gene Assays.Endothelial-like properties of claudin-low breast cancer cells promote tumor vascular permeability and metastasis.Intrinsic subtypes of high-grade bladder cancer reflect the hallmarks of breast cancer biology.Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO).Chemotherapy benefit for 'ER-positive' breast cancer and contamination of nonluminal subtypes—waiting for TAILORx and RxPONDER.A PAM50-Based Chemoendocrine Score for Hormone Receptor-Positive Breast Cancer with an Intermediate Risk of Relapse.
P2860
Q21135222-C3B97397-A192-480F-9BF4-06D3B476F7CFQ28268284-3C8A659D-5154-4925-8504-8D9DD08F70B3Q28743642-08E5052E-AFDE-41E8-8EF0-316E7899A585Q29248640-6A5814EE-2A36-46A8-9E14-6E49FF4D1EC1Q30301043-706B01A4-C0FB-4602-B602-BBDA7E7A6C95Q30587056-AF1EE722-A674-4D96-B044-FBC4991D021AQ33626963-97A0905C-4A8F-4DF3-87F9-491187348AADQ33742688-55DC1B43-F955-47A0-9445-D3CA40C5B9A3Q33916814-117BE140-C197-46CB-A9F9-DED4E66E1E0EQ34055901-5BCBAAD1-2937-49D9-BD7C-43EAE8DC7D7CQ34192343-FDA1A275-752F-494F-A9D9-C49FDF674B47Q34212421-26E4E257-4824-4626-8BF8-B6DE1CEE3ED5Q34247959-658E5160-C40B-45DA-8A25-D78F32FB7842Q34285190-23A1C959-C350-4B25-9886-AE1D754D2577Q34300562-370AFC2C-E76D-43D4-B00F-9D552113876DQ34787791-EEB8C8E2-00E0-4BB2-91CF-5C415C6E2D30Q34989075-4C448727-5BD2-447B-9B83-BBBC8C704089Q35079683-9E42FF35-2D99-4020-912F-6C25EBAF9E68Q35100954-3ED67520-519E-4883-9DD8-B8CB619B9632Q35503492-D8ED4F73-7A4C-4779-ABF5-AA771415AB25Q35572241-50EE4238-0B05-4087-9594-49747BC2B42FQ35630836-7A66A272-C27A-430B-8BCE-DD5A94C144C0Q35750639-26709777-5FD6-4B9D-A01C-8D135AB6D09AQ36245556-10398195-5BD9-4C74-9993-2D1A4EE928CFQ36337751-5247F91A-E274-48BF-AB61-8C46CFA70C2AQ36383626-424FFC25-6EFE-4B19-9A81-97E7526DE1C4Q36630430-EB9D0B08-D012-4963-899D-B647098277CBQ36661360-7ED27651-F421-4800-990C-9904AECBC3E9Q36678505-0E86C5CC-19CB-40F8-8568-E734081C2544Q36928452-4260D433-9E5D-4D8A-9C86-4E2973227620Q36935015-BAE9B260-CC8D-4C2F-9E0C-4C07FC308DC0Q36989546-58C52A1E-5343-4BBC-A9B0-4175851ECC43Q37166436-65D04A60-0639-44A2-928E-BA32C44C4D04Q37187379-4A05F1F0-58ED-4A6B-9999-476086173F2AQ37348196-041ED79C-0F7C-4E52-AA84-74DF7536931CQ37480166-2AA3663A-76CD-47E5-BF8E-FE6D954712E6Q37612632-39239467-099B-4A2E-AB24-00437316FBC7Q38720319-9C2A94AA-AE80-40DD-9989-3F1AE400B5B3Q39106157-0E299C2E-D973-40DD-ADBB-BCAD1D9A2930Q39141610-5A7CBF75-496A-4BE6-9836-4A7F7240A6CF
P2860
Building prognostic models for breast cancer patients using clinical variables and hundreds of gene expression signatures.
description
2011 nî lūn-bûn
@nan
2011 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Building prognostic models for ...... of gene expression signatures.
@ast
Building prognostic models for ...... of gene expression signatures.
@en
type
label
Building prognostic models for ...... of gene expression signatures.
@ast
Building prognostic models for ...... of gene expression signatures.
@en
prefLabel
Building prognostic models for ...... of gene expression signatures.
@ast
Building prognostic models for ...... of gene expression signatures.
@en
P2093
P2860
P356
P1433
P1476
Building prognostic models for ...... of gene expression signatures
@en
P2093
Joel S Parker
Lisa A Carey
Melissa A Troester
Yufeng Liu
P2860
P2888
P356
10.1186/1755-8794-4-3
P577
2011-01-09T00:00:00Z
P5875
P6179
1013453261