Identifying single-cell molecular programs by stochastic profiling. - Wikidata - wikimedia - TriplyDB

Identifying single-cell molecular programs by stochastic profiling.

Identifying single-cell molecular programs by stochastic profiling.

http://www.wikidata.org/entity/Q30434682

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SVD identifies transcript length distribution functions from DNA microarray data and reveals evolutionary forces globally affecting GBM metabolism Coupling among growth rate response, metabolic cycle, and cell division cycle in yeast The applications of single-cell genomics Multiscale models of cell signaling.Cell-to-cell variability in cell death: can systems biology help us make sense of it all?Normal morphogenesis of epithelial tissues and progression of epithelial tumors.Single-cell RNA-seq: advances and future challenges Differentiation of human gingival mesenchymal stem cells into neuronal lineages in 3D bioconjugated injectable protein hydrogel construct for the management of neuronal disorder Profiling Subcellular Protein Phosphatase Responses to Coxsackievirus B3 Infection of Cardiomyocytes.Small Molecule Inhibitor of CBFβ-RUNX Binding for RUNX Transcription Factor Driven Cancers TNF-insulin crosstalk at the transcription factor GATA6 is revealed by a model that links signaling and transcriptomic data tensors.Single-cell states versus single-cell atlases - two classes of heterogeneity that differ in meaning and method An analysis of critical factors for quantitative immunoblotting.A time- and matrix-dependent TGFBR3-JUND-KRT5 regulatory circuit in single breast epithelial cells and basal-like premalignancies Simultaneous profiling of 194 distinct receptor transcripts in human cells Parameterizing cell-to-cell regulatory heterogeneities via stochastic transcriptional profiles.Models of signalling networks - what cell biologists can gain from them and give to them Stochastic profiling of transcriptional regulatory heterogeneities in tissues, tumors and cultured cells RUNX1 and its understudied role in breast cancer Intersection of FOXO- and RUNX1-mediated gene expression programs in single breast epithelial cells during morphogenesis and tumor progression.Single cell transcriptional profiling reveals heterogeneity of human induced pluripotent stem cells.End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data.Accurate expression profiling of very small cell populations.Akt and ERK control the proliferative response of mammary epithelial cells to the growth factors IGF-1 and EGF through the cell cycle inhibitor p57Kip2.Teasing apart translational and transcriptional components of stochastic variations in eukaryotic gene expression.Expression of VEGF receptors on endothelial cells in mouse skeletal muscle.Embracing noise to improve cross-batch prediction accuracy.Non-biased and efficient global amplification of a single-cell cDNA library.Identifying functional gene regulatory network phenotypes underlying single cell transcriptional variability.One-step purification of nucleic acid for gene expression analysis via Immiscible Filtration Assisted by Surface Tension (IFAST)On comparing heterogeneity across biomarkers.Multiscale analysis of the murine intestine for modeling human diseases.A conserved cell growth cycle can account for the environmental stress responses of divergent eukaryotes.Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling.Epigenomic Reprogramming of Adult Cardiomyocyte-Derived Cardiac Progenitor Cells Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas.Identifying network motifs that buffer front-to-back signaling in polarized neutrophils.Cell type-specific transcriptome profiling in mammalian brains Functional genomics of the brain: uncovering networks in the CNS using a systems approach.Cancer cells in epithelial-to-mesenchymal transition and tumor-propagating-cancer stem cells: distinct, overlapping or same populations.

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P2860

Identifying single-cell molecular programs by stochastic profiling.

http://www.wikidata.org/entity/Q30434682

description

2010 nî lūn-bûn

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2010 թուականի Մարտին հրատարակուած գիտական յօդուած

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2010 թվականի մարտին 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

@zh-hk

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

Identifying single-cell molecular programs by stochastic profiling.

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Identifying single-cell molecular programs by stochastic profiling.

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type

label

Identifying single-cell molecular programs by stochastic profiling.

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Identifying single-cell molecular programs by stochastic profiling.

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Identifying single-cell molecular programs by stochastic profiling.

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Identifying single-cell molecular programs by stochastic profiling.

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Identifying single-cell molecular programs by stochastic profiling.

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Chun-Chao Wang

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Joan S Brugge

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Karin J Holmberg

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Kristin Cabral

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P2860

PI-3 kinase activity is necessary for ERK1/2-induced disruption of mammary epithelial architecture.

Stress-associated endoplasmic reticulum protein 1 (SERP1)/Ribosome-associated membrane protein 4 (RAMP4) stabilizes membrane proteins during stress and facilitates subsequent glycosylation

A collection of breast cancer cell lines for the study of functionally distinct cancer subtypes

ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome

Functional role and oncogene-regulated expression of the BH3-only factor Bmf in mammary epithelial anoikis and morphogenesis

Noise minimization in eukaryotic gene expression

Modeling T cell antigen discrimination based on feedback control of digital ERK responses

An improved single-cell cDNA amplification method for efficient high-density oligonucleotide microarray analysis

Phosphorylation meets ubiquitination: the control of NF-[kappa]B activity

Laser capture microdissection

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