Knowledge-driven genomic interactions: an application in ovarian cancer. - Test2 - elhamkhani - TriplyDB

Knowledge-driven genomic interactions: an application in ovarian cancer.

Knowledge-driven genomic interactions: an application in ovarian cancer.

http://www.wikidata.org/entity/Q34165543

about

Using knowledge-driven genomic interactions for multi-omics data analysis: metadimensional models for predicting clinical outcomes in ovarian carcinoma.Identification of epigenetic interactions between miRNA and DNA methylation associated with gene expression as potential prognostic markers in bladder cancer Identifying subtype-specific associations between gene expression and DNA methylation profiles in breast cancer More Is Better: Recent Progress in Multi-Omics Data Integration Methods Biology-Driven Gene-Gene Interaction Analysis of Age-Related Cataract in the eMERGE Network.Lnc-CC3 increases metastasis in cervical cancer by increasing Slug expression Detecting gene-gene interactions using a permutation-based random forest method Characterization of ovarian cancer cell lines as in vivo models for preclinical studies.Collective feature selection to identify crucial epistatic variants.

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P2860

Knowledge-driven genomic interactions: an application in ovarian cancer.

http://www.wikidata.org/entity/Q34165543

description

2014 nî lūn-bûn

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2014 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած

@hyw

2014 թվականի սեպտեմբերին հրատարակված գիտական հոդված

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2014年の論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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2014年論文

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2014年论文

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name

Knowledge-driven genomic interactions: an application in ovarian cancer.

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Knowledge-driven genomic interactions: an application in ovarian cancer.

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Knowledge-driven genomic interactions: an application in ovarian cancer.

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Knowledge-driven genomic interactions: an application in ovarian cancer.

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Knowledge-driven genomic interactions: an application in ovarian cancer.

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Knowledge-driven genomic interactions: an application in ovarian cancer.

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Knowledge-driven genomic interactions: an application in ovarian cancer.

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Alex T Frase

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Dokyoon Kim

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Ruowang Li

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Scott M Dudek

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P2860

Oncogenes and Cancer

Gene ontology: tool for the unification of biology

Analysis of protein-protein interactions in cross-talk pathways reveals CRKL protein as a novel prognostic marker in hepatocellular carcinoma

Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles.

The Pfam protein families database

Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases

Towards precise classification of cancers based on robust gene functional expression profiles

Targeting HIF-1 for cancer therapy

Integrated genomic analyses of ovarian carcinoma

Gene expression profiling predicts clinical outcome of breast cancer

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