Improved breast cancer prognosis through the combination of clinical and genetic markers. - Wikidata - awgldk - TriplyDB

Improved breast cancer prognosis through the combination of clinical and genetic markers.

Improved breast cancer prognosis through the combination of clinical and genetic markers.

http://www.wikidata.org/entity/Q36201698

about

Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data Inferring phenotypic properties from single-cell characteristics Derivation of molecular signatures for breast cancer recurrence prediction using a two-way validation approach Breast cancer survivability prediction using labeled, unlabeled, and pseudo-labeled patient data Breast cancer prognosis risk estimation using integrated gene expression and clinical data Genetic programming based ensemble system for microarray data classification.Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets.Merging microarray data from separate breast cancer studies provides a robust prognostic test.Signature Evaluation Tool (SET): a Java-based tool to evaluate and visualize the sample discrimination abilities of gene expression signatures Expression profiling with RNA from formalin-fixed, paraffin-embedded material A voting approach to identify a small number of highly predictive genes using multiple classifiers.Clinical bioinformatics for complex disorders: a schizophrenia case study.Survival prediction from clinico-genomic models--a comparative study.Testing the additional predictive value of high-dimensional molecular data.Pathway-BasedFeature Selection Algorithm for Cancer Microarray Data.Local-learning-based feature selection for high-dimensional data analysis.Urine-based assays for the detection of bladder cancer.Advanced computational algorithms for microbial community analysis using massive 16S rRNA sequence data Derivation of cancer diagnostic and prognostic signatures from gene expression data.Statistical Test of Expression Pattern (STEPath): a new strategy to integrate gene expression data with genomic information in individual and meta-analysis studies.Computational prognostic indicators for breast cancer.Classification of dendritic cell phenotypes from gene expression data Human communication dynamics in digital footsteps: a study of the agreement between self-reported ties and email networks.Exploring molecular links between lymph node invasion and cancer prognosis in human breast cancer.Cancer progression modeling using static sample data Network-based Prediction of Cancer under Genetic Storm Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods.Machine learning applications in cancer prognosis and prediction The role of lymphovascular invasion as a prognostic factor in patients with lymph node-positive operable invasive breast cancer.Breast tumor metastasis: analysis via proteomic profiling.Optimizing molecular signatures for predicting prostate cancer recurrence.Molecular diagnostic trends in urological cancer: biomarkers for non-invasive diagnosis.Prediction of breast cancer metastasis by gene expression profiles: a comparison of metagenes and single genes.Bladder cancer detection and monitoring: assessment of urine- and blood-based marker tests Combining clinical and genomic covariates via Cov-TGDR Bladder cancer-associated gene expression signatures identified by profiling of exfoliated urothelia Urinary proteomic profiling for diagnostic bladder cancer biomarkers.Assessment of kidney organ quality and prediction of outcome at time of transplantation.Urinary biomarkers of bladder cancer: an update and future perspectives.MULTIPLEX URINARY TESTS FOR BLADDER CANCER DIAGNOSIS.

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P2860

Improved breast cancer prognosis through the combination of clinical and genetic markers.

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2006年论文

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2006年论文

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2006年论文

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name

Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Improved breast cancer prognosis through the combination of clinical and genetic markers.

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Jian Li

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Li Liu

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Steve Goodison

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William Farmerie

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Yijun Sun

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P2860

Identification of a novel family of cell-surface proteins expressed in human vascular endothelium

Functional characterization of human nucleosome assembly protein-2 (NAP1L4) suggests a role as a histone chaperone

Testis-specific protein, Y-encoded (TSPY) expression in testicular tissues

The RhoGAP protein DLC-1 functions as a metastasis suppressor in breast cancer cells

Gene expression signature of estrogen receptor alpha status in breast cancer

Gene expression profiling predicts clinical outcome of breast cancer

A gene-expression signature as a predictor of survival in breast cancer

Molecular classification of cancer: class discovery and class prediction by gene expression monitoring

Preferentially expressed antigen of melanoma (PRAME) in the development of diagnostic and therapeutic methods for hematological malignancies

Characterization of an antigen that is recognized on a melanoma showing partial HLA loss by CTL expressing an NK inhibitory receptor

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