The properties of high-dimensional data spaces: implications for exploring gene and protein expression data. - Wikidata - wikimedia - TriplyDB

The properties of high-dimensional data spaces: implications for exploring gene and protein expression data.

The properties of high-dimensional data spaces: implications for exploring gene and protein expression data.

http://www.wikidata.org/entity/Q31140694

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Metabolic reconstruction for metagenomic data and its application to the human microbiome An in silico analysis of dynamic changes in microRNA expression profiles in stepwise development of nasopharyngeal carcinoma Big Data Analytics for Prostate Radiotherapy Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.High-Dimensional Statistical Learning: Roots, Justifications, and Potential Machineries Application of metabolomics in drug resistant breast cancer research A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma Constrained inference of protein interaction networks for invadopodium formation in cancer The noncoding RNA expression profile and the effect of lncRNA AK126698 on cisplatin resistance in non-small-cell lung cancer cell Gene network revealed involvements of Birc2, Birc3 and Tnfrsf1a in anti-apoptosis of injured peripheral nerves Meta-analysis of age-related gene expression profiles identifies common signatures of aging.Correcting for intra-experiment variation in Illumina BeadChip data is necessary to generate robust gene-expression profiles Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis.StRAP: an integrated resource for profiling high-throughput cancer genomic data from stress response studies.Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.Parallel classification and feature selection in microarray data using SPRINT.Using a data mining approach to discover behavior correlates of chronic disease: a case study of depression.Knowledge-guided multi-scale independent component analysis for biomarker identification.Methods of integrating data to uncover genotype-phenotype interactions.From big data analysis to personalized medicine for all: challenges and opportunities Early diagnostic protein biomarkers for breast cancer: how far have we come?Bayesian clinical classification from high-dimensional data: Signatures versus variability.Expression profile analysis of head and neck squamous cell carcinomas using data from The Cancer Genome Atlas.Integrated Data Set of microRNAs and mRNAs Involved in Severe Intrauterine Adhesion.Approaches to working in high-dimensional data spaces: gene expression microarrays.Mining, visualizing and comparing multidimensional biomolecular data using the Genomics Data Miner (GMine) Web-Server.Identification of a gene signature in cell cycle pathway for breast cancer prognosis using gene expression profiling data.A seriation approach for visualization-driven discovery of co-expression patterns in Serial Analysis of Gene Expression (SAGE) data.caBIG VISDA: modeling, visualization, and discovery for cluster analysis of genomic data.Bioinformatics analysis of mass spectrometry-based proteomics data sets.The role of preclinical animal models in breast cancer drug development.Reconstruction of gene regulatory modules in cancer cell cycle by multi-source data integration.Modeling the aneuploidy control of cancer.Expression Profiling of Transcriptome and Its Associated Disease Risk in Yang Deficiency Constitution of Healthy Subjects.The role of microRNA-93 regulating angiopoietin2 in the formation of malignant pleural effusion.Global genotype-phenotype correlations in Pseudomonas aeruginosa.Derivation of cancer diagnostic and prognostic signatures from gene expression data.New dimensionality reduction methods for the representation of high dimensional 'omics' data.Content-based microarray search using differential expression profiles.Support Vector Machine Analysis of Functional Magnetic Resonance Imaging of Interoception Does Not Reliably Predict Individual Outcomes of Cognitive Behavioral Therapy in Panic Disorder with Agoraphobia.

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The properties of high-dimensional data spaces: implications for exploring gene and protein expression data.

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Nature Reviews Cancer

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Antai Wang

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Edmund A Gehan

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Habtom W Ressom

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Jianhua Xuan

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Minetta C Liu

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Yue Wang

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The yeast coexpression network has a small-world, scale-free architecture and can be explained by a simple model

Cluster analysis and display of genome-wide expression patterns

The effects of normalization on the correlation structure of microarray data

Microarray missing data imputation based on a set theoretic framework and biological knowledge

Emergence of Scaling in Random Networks

A comparison of normalization methods for high density oligonucleotide array data based on variance and bias

Gene expression profiling predicts clinical outcome of breast cancer

Serial analysis of gene expression

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

Collective dynamics of 'small-world' networks

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