Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression - Test2 - elhamkhani - TriplyDB

Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression

Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression

http://www.wikidata.org/entity/Q29615223

about

A precisely regulated gene expression cassette potently modulates metastasis and survival in multiple solid cancers From bytes to bedside: data integration and computational biology for translational cancer research Translational bioinformatics applications in genome medicine Identification of novel mitosis regulators through data mining with human centromere/kinetochore proteins as group queries Mining expressed sequence tags identifies cancer markers of clinical interest GREB1 functions as a growth promoter and is modulated by IL6/STAT3 in breast cancer SOX2 is an oncogene activated by recurrent 3q26.3 amplifications in human lung squamous cell carcinomas The ubiquitin ligase FBXW7 modulates leukemia-initiating cell activity by regulating MYC stability MYBBP1A suppresses breast cancer tumorigenesis by enhancing the p53 dependent anoikis Genome-wide promoter analysis of the SOX4 transcriptional network in prostate cancer cells The euchromatic and heterochromatic landscapes are shaped by antagonizing effects of transcription on H2A.Z deposition Substrate specificity and activity regulation of protein kinase MELK Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer AGTR1 overexpression defines a subset of breast cancer and confers sensitivity to losartan, an AGTR1 antagonist HURP controls spindle dynamics to promote proper interkinetochore tension and efficient kinetochore capture.A crowdsourcing approach for reusing and meta-analyzing gene expression data Three microarray platforms: an analysis of their concordance in profiling gene expression.PAGE: parametric analysis of gene set enrichment The molecular portrait of in vitro growth by meta-analysis of gene-expression profiles Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes Combining Affymetrix microarray results.Storing, linking, and mining microarray databases using SRS Design of a microsphere-based high-throughput gene expression assay to determine estrogenic potential.Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts.High Mobility Group B Proteins, Their Partners, and Other Redox Sensors in Ovarian and Prostate Cancer The mitochondrial unfolded protein response in mammalian physiology Every amino acid matters: essential contributions of histone variants to mammalian development and disease Expression and functionality of histone H2A variants in cancer Maternal embryonic leucine zipper kinase (MELK): a novel regulator in cell cycle control, embryonic development, and cancer Proteomic approaches and identification of novel therapeutic targets for alcoholism Expression of cell cycle-regulated genes and prostate cancer prognosis in a population-based cohort Tumor necrosis factor receptor-associated factor 4 is a dynamic tight junction-related shuttle protein involved in epithelium homeostasis Transcriptome meta-analysis reveals a dysregulation in extra cellular matrix and cell junction associated gene signatures during Dengue virus infection TRAF4 Is a Novel Phosphoinositide-Binding Protein Modulating Tight Junctions and Favoring Cell Migration Global regulation of H2A.Z localization by the INO80 chromatin-remodeling enzyme is essential for genome integrity B-cell-specific Moloney murine leukemia virus integration site 1: potential stratification factor and therapeutic target for epithelial ovarian cancer Reverse enGENEering of Regulatory Networks from Big Data: A Roadmap for Biologists Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes The tyrosine phosphatase PTPRD is a tumor suppressor that is frequently inactivated and mutated in glioblastoma and other human cancers Large-scale integration of microarray data reveals genes and pathways common to multiple cancer types

P2860

Q21145043-8BF8F5F7-CAC9-40AF-BF62-6C8C6F70BD3A Q21145672-DCCE9CCB-AD37-45F3-A757-A8C7DA873331 Q21183956-C0075861-6776-4CE2-80CE-E11120A2C714 Q21284186-3AD04E05-97FB-42AD-AF13-21E9007F2B47 Q21284250-C5B86761-B805-43FB-A463-2A6721FE58A5 Q21560759-BC6C7EBA-D2EA-47B9-AB54-75CE577A0C3D Q21562575-C1B8EDDB-7188-4858-9EE6-9EB6E63FFA28 Q24296476-6B3159BC-F93D-4EE4-9449-77602966A22A Q24314897-652047B3-1736-4102-AC6F-92B9E0416C8F Q24317198-49A2D1BB-9619-4EE3-8235-D0BF732F7C99 Q24336460-848BE4AB-7494-4CBA-9C7A-FB49C8BB94D4 Q24338012-FEA8043A-A6C1-4A13-AE4F-EC3C9B1B3B76 Q24528253-BD5E8B50-1B42-4284-A89D-B3181FE47B33 Q24652842-B65AAE96-7AEC-4B95-805D-8C898C8C51DC Q24683651-BE3B2A40-1BA6-4C9D-A591-3A9898DEFE36 Q24706236-9B50FBAB-C3B3-4ED7-9855-11BEF2FD8C25 Q24810026-027018D0-BBD0-40F6-B204-72EC97912601 Q24810449-937A1752-7FE6-4D0E-A4B7-3705B2E55131 Q24811243-1E1ACE9D-97CB-4ABC-A66B-816262C31000 Q24811346-33887A18-4940-459B-83C4-81A9B0A5C9BD Q24811466-FE46E4BB-3EB1-4FD1-8A8F-058D8862749B Q24813666-9CD14F20-CB6C-4ABD-AD8C-76438F39BFB2 Q24815514-B65689B3-1675-44A4-9723-B2C4CA1CF31C Q25257621-40968B43-6F15-4E7A-A7FD-77C7ED2F5E97 Q26774902-95B73904-A502-4430-925B-48ACF1074EFE Q26864918-F6F88E1E-F741-4AAF-BB1D-9F24E6A16EE0 Q27008522-BCB27064-6CF6-4E6D-B5C8-7DD75817A3BB Q27014044-7B81A7D0-2AF2-40EA-B7C5-DF4B489F9CA4 Q27022633-A6FCF2E7-AA07-424E-9E67-58CDB4791029 Q27023085-E50239DE-D7E7-46C7-A012-EDD194FEBB76 Q27331050-3F41FF50-1227-4A9F-B78B-CCA625652921 Q27438162-4121C714-D01C-4DD4-AA44-2FD8BE06B0BB Q27468674-08BCF0C5-23D3-4AFE-A1AA-A386F8CF7147 Q27680792-059F0964-3936-418D-B56A-E11260D53737 Q27930002-44B91D42-1B20-4423-A721-76C1C4202496 Q28075362-EE74194C-0E95-4861-A6BC-9ABAF702E999 Q28083193-EB72C281-CAC5-47BA-ACB4-BEC4C025A832 Q28085759-0A185E7E-6B6E-489A-A775-6D4DF54C43B5 Q28115840-954DEA71-4B25-4901-809B-A1E26F63DED3 Q28301260-646E10AB-8214-409F-800B-CF81360EB709

P2860

Large-scale meta-analysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression

http://www.wikidata.org/entity/Q29615223

description

2004 nî lūn-bûn

@nan

2004 թուականի Յունիսին հրատարակուած գիտական յօդուած

@hyw

2004 թվականի հունիսին հրատարակված գիտական հոդված

@hy

2004年の論文

@ja

2004年論文

@yue

2004年論文

@zh-hant

2004年論文

@zh-hk

2004年論文

@zh-mo

2004年論文

@zh-tw

2004年论文

@wuu

name

Large-scale meta-analysis of c ...... transformation and progression

@ast

Large-scale meta-analysis of c ...... transformation and progression

@en

type

label

Large-scale meta-analysis of c ...... transformation and progression

@ast

Large-scale meta-analysis of c ...... transformation and progression

@en

prefLabel

Large-scale meta-analysis of c ...... transformation and progression

@ast

Large-scale meta-analysis of c ...... transformation and progression

@en

P1433

Q29615223-BED5B230-1261-4061-988B-FB925E81046E

P1476

Q29615223-23EC6A78-6FAD-4CF1-8D86-9CBBB23E2D20

P2093

Q29615223-15242E97-9E0D-4624-9B17-8E748D9AFE3E

Q29615223-2835E752-1D76-4D54-AA94-FF0F21E0D805

Q29615223-61FFFC19-3503-45B2-A1CC-FE83064889FF

Q29615223-717E7B48-0D71-4B3A-A701-C87A7F370A12

Q29615223-71B63A41-121E-40CA-A45F-7AC08CCD80A8

Q29615223-8BD2D79E-6042-4541-8189-2BA87CC7477D

Q29615223-9D870A25-E980-4E4B-8128-624087E8FF15

Q29615223-E51C6D7B-E4E8-4F6B-8543-B78539752852

Q29615223-E79F9F7D-F255-455A-B141-29969082CEF0

P2860

Q29615223-006FD1C9-3B77-4EDC-8695-73A227B34E44

Q29615223-05E3627D-5DF2-4A7D-B655-6DCFB9B1FEF9

Q29615223-0EE8DCA5-683A-4236-911D-6F4431BD5854

Q29615223-20C26509-90E6-49FB-A5FF-C037BBDD2690

Q29615223-271E483A-E9E6-4120-9016-E36FD46D6D27

Q29615223-2A210DDD-8D66-458D-B6E3-997E5AA0BBF2

Q29615223-2AF741E4-ACB8-41BD-9370-5D3FC7D8CDAA

Q29615223-2B9D8133-DAB8-4E0F-98A4-6F5522C08540

Q29615223-2E04A8EA-0FA2-475D-A412-308E727A9B55

Q29615223-31294975-39F6-4C17-BB09-219E699B73D9

P304

Q29615223-F6770E1D-9EB9-45F0-80E0-1732F4497284

P31

Q29615223-412050BA-876A-4BCC-82FC-89D57FE694C9

Q29615223-41F4F1CA-2187-4ED6-88E6-161227AC531F

P3181

Q29615223-4B19E19D-D611-4166-9143-890957C8CAC2

P356

Q29615223-B0E10351-3FE4-4129-B820-2F06D05725A3

P407

Q29615223-B83C021E-1294-4999-A0E9-9B3ED152589F

P433

Q29615223-23B1E7F0-6401-45C4-9882-6E7A4A1B7F79

P478

Q29615223-D4731CFD-7562-4740-B658-4583C785A488

P577

Q29615223-D596C0B6-2281-4CB4-9714-342A4C44647E

P5875

Q29615223-A4E4212F-4A2A-4BCB-9772-71C0BF4F8C0C

P698

Q29615223-7EADBA8D-BB8F-4EF6-84DA-18D6B446C9E4

P921

Q29615223-D3A76E42-E627-405B-BC88-7ED99F0FA683

P932

Q29615223-A6D78263-EA28-449A-B2BC-6252B927D127

P3181

P356

PNAS.0401994101

P1433

Proceedings of the National Academy of Sciences of the United States of America

P1476

Large-scale meta-analysis of c ...... transformation and progression

@en

P2093

Barrette T

http://www.w3.org/2001/XMLSchema#string

Chinnaiyan AM

http://www.w3.org/2001/XMLSchema#string

Deshpande N

http://www.w3.org/2001/XMLSchema#string

Ghosh D

http://www.w3.org/2001/XMLSchema#string

Pandey A

http://www.w3.org/2001/XMLSchema#string

Rhodes DR

http://www.w3.org/2001/XMLSchema#string

Shanker K

http://www.w3.org/2001/XMLSchema#string

Varambally R

http://www.w3.org/2001/XMLSchema#string

Yu J

http://www.w3.org/2001/XMLSchema#string

P2860

Control of apoptosis and mitotic spindle checkpoint by survivin

Gene ontology: tool for the unification of biology

Cluster analysis and display of genome-wide expression patterns

Gene expression patterns in ovarian carcinomas

EZH2 is a marker of aggressive breast cancer and promotes neoplastic transformation of breast epithelial cells

Statistical significance for genomewide studies

Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer.

The use of molecular profiling to predict survival after chemotherapy for diffuse large-B-cell lymphoma.

Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications

Gene expression profiling predicts clinical outcome of breast cancer

P304

9309-14

http://www.w3.org/2001/XMLSchema#string

P31

scholarly article

P3181

151069

http://www.w3.org/2001/XMLSchema#string

P356

10.1073/PNAS.0401994101

http://www.w3.org/2001/XMLSchema#string

P407

P433

25

http://www.w3.org/2001/XMLSchema#string

P478

101

http://www.w3.org/2001/XMLSchema#string

P577

2004-06-22T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

P5875

8521774

http://www.w3.org/2001/XMLSchema#string

P698

15184677

http://www.w3.org/2001/XMLSchema#string

P921

P932

438973

http://www.w3.org/2001/XMLSchema#string