Pages that link to "Q30657296"
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The following pages link to Separation of samples into their constituents using gene expression data (Q30657296):
Displaying 50 items.
- Macrodissection versus microdissection of rectal carcinoma: minor influence of stroma cells to tumor cell gene expression profiles (Q24810564) (← links)
- In silico microdissection of microarray data from heterogeneous cell populations (Q24811429) (← links)
- RNA-Seq Differentiates Tumour and Host mRNA Expression Changes Induced by Treatment of Human Tumour Xenografts with the VEGFR Tyrosine Kinase Inhibitor Cediranib (Q27315803) (← links)
- DeMix: deconvolution for mixed cancer transcriptomes using raw measured data (Q30634335) (← links)
- Inferring tumour purity and stromal and immune cell admixture from expression data (Q30674996) (← links)
- An assessment of computational methods for estimating purity and clonality using genomic data derived from heterogeneous tumor tissue samples (Q30762666) (← links)
- Finite mixture model analysis of microarray expression data on samples of uncertain biological type with application to reproductive efficiency (Q30986404) (← links)
- B-Cell and Monocyte Contribution to Systemic Lupus Erythematosus Identified by Cell-Type-Specific Differential Expression Analysis in RNA-Seq Data (Q31012687) (← links)
- Complex Sources of Variation in Tissue Expression Data: Analysis of the GTEx Lung Transcriptome (Q31126351) (← links)
- A self-directed method for cell-type identification and separation of gene expression microarrays. (Q31129201) (← links)
- Robust computational reconstitution - a new method for the comparative analysis of gene expression in tissues and isolated cell fractions (Q33252920) (← links)
- Sample matching by inferred agonal stress in gene expression analyses of the brain (Q33300170) (← links)
- Biomarker discovery in heterogeneous tissue samples -taking the in-silico deconfounding approach (Q33523636) (← links)
- Statistical expression deconvolution from mixed tissue samples (Q33785569) (← links)
- Systematic Bias in Genomic Classification Due to Contaminating Non-neoplastic Tissue in Breast Tumor Samples (Q33947222) (← links)
- Probabilistic analysis of gene expression measurements from heterogeneous tissues (Q34180824) (← links)
- Cell population-specific expression analysis of human cerebellum (Q34474749) (← links)
- Gene expression deconvolution in clinical samples (Q34513150) (← links)
- PERT: a method for expression deconvolution of human blood samples from varied microenvironmental and developmental conditions (Q34531191) (← links)
- A mixture model for expression deconvolution from RNA-seq in heterogeneous tissues (Q34756607) (← links)
- Deconvolution of gene expression from cell populations across the C. elegans lineage (Q34783303) (← links)
- MMAD: microarray microdissection with analysis of differences is a computational tool for deconvoluting cell type-specific contributions from tissue samples (Q35004287) (← links)
- A method for cell type marker discovery by high-throughput gene expression analysis of mixed cell populations (Q35007302) (← links)
- Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials (Q35583307) (← links)
- ISOpureR: an R implementation of a computational purification algorithm of mixed tumour profiles. (Q35601192) (← links)
- MixChIP: a probabilistic method for cell type specific protein-DNA binding analysis (Q35878429) (← links)
- A Balanced Tissue Composition Reveals New Metabolic and Gene Expression Markers in Prostate Cancer (Q35996026) (← links)
- Improving sensitivity of linear regression-based cell type-specific differential expression deconvolution with per-gene vs. global significance threshold. (Q36170311) (← links)
- Deconvoluting complex tissues for expression quantitative trait locus-based analyses (Q36929492) (← links)
- A prototype tobacco-associated oral squamous cell carcinoma classifier using RNA from brush cytology (Q37086306) (← links)
- Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression (Q37356734) (← links)
- Computational deconvolution: extracting cell type-specific information from heterogeneous samples (Q37417280) (← links)
- Epigenomic Deconvolution of Breast Tumors Reveals Metabolic Coupling between Constituent Cell Types (Q37422742) (← links)
- High-throughput genomic profiling of tumor-infiltrating leukocytes. (Q38884388) (← links)
- Semi-supervised Nonnegative Matrix Factorization for gene expression deconvolution: A case study (Q39471747) (← links)
- Computational purification of individual tumor gene expression profiles leads to significant improvements in prognostic prediction (Q42057291) (← links)
- ISOLATE: a computational strategy for identifying the primary origin of cancers using high-throughput sequencing (Q42662335) (← links)
- A sequential Monte Carlo approach to gene expression deconvolution. (Q42695752) (← links)
- Population-specific expression analysis (PSEA) reveals molecular changes in diseased brain (Q43681272) (← links)
- Simultaneous enumeration of cancer and immune cell types from bulk tumor gene expression data (Q47106619) (← links)
- Transcriptomic analysis of the tumor microenvironment to guide prognosis and immunotherapies. (Q47959293) (← links)
- Statistical mechanics approach to the sample deconvolution problem. (Q51216797) (← links)
- Single-cell RNA sequencing identifies celltype-specific cis-eQTLs and co-expression QTLs. (Q52611747) (← links)
- Quantifying tumor-infiltrating immune cells from transcriptomics data. (Q52726457) (← links)
- Gene expression in thyroid autonomous adenomas provides insight into their physiopathology. (Q54653332) (← links)
- A new method for constructing tumor specific gene co-expression networks based on samples with tumor purity heterogeneity. (Q55483368) (← links)
- Quantitative Analyses of the Tumor Microenvironment Composition and Orientation in the Era of Precision Medicine (Q57492123) (← links)
- Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases (Q58568263) (← links)
- Deblender: a semi-/unsupervised multi-operational computational method for complete deconvolution of expression data from heterogeneous samples (Q58592901) (← links)
- Insights from deconvolution of cell subtype proportions enhance the interpretation of functional genomic data (Q64090324) (← links)