Prioritizing genes associated with prostate cancer development - Wikidata - awgldk - TriplyDB

Prioritizing genes associated with prostate cancer development

Prioritizing genes associated with prostate cancer development

http://www.wikidata.org/entity/Q30497425

about

Exposure to bisphenol A correlates with early-onset prostate cancer and promotes centrosome amplification and anchorage-independent growth in vitro Evaluation of protein biomarkers of prostate cancer aggressiveness Targeting the CCL2-CCR2 signaling axis in cancer metastasis The cholesterol metabolite 27-hydroxycholesterol stimulates cell proliferation via ERβ in prostate cancer cells.Stromal expression of decorin, Semaphorin6D, SPARC, Sprouty1 and Tsukushi in developing prostate and decreased levels of decorin in prostate cancer.Building a statistical model for predicting cancer genes.Identification of proteomic biomarkers predicting prostate cancer aggressiveness and lethality despite biopsy-sampling error.The prognostic utility of the transcription factor SRF in docetaxel-resistant prostate cancer: in-vitro discovery and in-vivo validation.Molecular profiling of prostatic acinar morphogenesis identifies PDCD4 and KLF6 as tissue architecture-specific prognostic markers in prostate cancer.The present and future of prostate cancer urine biomarkers.Androgen-responsive serum response factor target genes regulate prostate cancer cell migration.Beyond comparing means: the usefulness of analyzing interindividual variation in gene expression for identifying genes associated with cancer development.miR-888 is an expressed prostatic secretions-derived microRNA that promotes prostate cell growth and migration.The role of transcription factors in prostate cancer and potential for future RNA interference therapy.Deregulated expression of connective tissue growth factor (CTGF/CCN2) is linked to poor outcome in human cancer.Identification of transcription factors associated with castration-resistance: is the serum responsive factor a potential therapeutic target?Role of SMAD4 in the mechanism of valproic acid's inhibitory effect on prostate cancer cell invasiveness.CCL2 Chemokine as a Potential Biomarker for Prostate Cancer: A Pilot Study.Clinical evaluation of macrophages in cancer: role in treatment, modulation and challenges.Effects of connective tissue growth factor on prostate cancer bone metastasis and osteoblast differentiation.

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Prioritizing genes associated with prostate cancer development

http://www.wikidata.org/entity/Q30497425

description

2010 nî lūn-bûn

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2010 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

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2010 թվականի նոյեմբերին հրատարակված գիտական հոդված

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2010年の論文

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2010年論文

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2010年論文

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2010年論文

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2010年論文

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2010年論文

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2010年论文

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name

Prioritizing genes associated with prostate cancer development

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Prioritizing genes associated with prostate cancer development

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type

label

Prioritizing genes associated with prostate cancer development

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Prioritizing genes associated with prostate cancer development

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prefLabel

Prioritizing genes associated with prostate cancer development

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Prioritizing genes associated with prostate cancer development

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Prioritizing genes associated with prostate cancer development

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Christopher J Logothetis

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Curtis A Pettaway

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Hongya Zhao

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Ivan P Gorlov

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Jin Young Byun

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Kanishka Sircar

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

Nora M Navone

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Olga Y Gorlova

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

Patricia Troncoso

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

Sankar N Maity

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

P2860

The file drawer problem and tolerance for null results

NCBI GEO: mining tens of millions of expression profiles--database and tools update

Highly accurate two-gene classifier for differentiating gastrointestinal stromal tumors and leiomyosarcomas

DAVID: Database for Annotation, Visualization, and Integrated Discovery

Gene Expression Omnibus: NCBI gene expression and hybridization array data repository

Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

Tissue microarray analysis of signal transducers and activators of transcription 3 (Stat3) and phospho-Stat3 (Tyr705) in node-negative breast cancer shows nuclear localization is associated with a better prognosis

SNPs3D: candidate gene and SNP selection for association studies.

Limits of predictive models using microarray data for breast cancer clinical treatment outcome.

Predicting the prognosis of breast cancer by integrating clinical and microarray data with Bayesian networks.

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1471-2407-10-599

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10.1186/1471-2407-10-599

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2010-11-02T00:00:00Z

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