Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering. - Wikidata - awgldk - TriplyDB

Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering.

Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering.

http://www.wikidata.org/entity/Q24793591

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An algorithm for chemical genomic profiling that minimizes batch effects: bucket evaluations Sequencing and comparison of yeast species to identify genes and regulatory elements MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model Identification of nutrient partitioning genes participating in rice grain filling by singular value decomposition (SVD) of genome expression data DNA microarray data and contextual analysis of correlation graphs Tumor classification and marker gene prediction by feature selection and fuzzy c-means clustering using microarray data GeneXplorer: an interactive web application for microarray data visualization and analysis MiCoViTo: a tool for gene-centric comparison and visualization of yeast transcriptome states Quantitative inference of dynamic regulatory pathways via microarray data Conservation and evolution of cis-regulatory systems in ascomycete fungi Integrated analysis of gene expression by Association Rules Discovery Methionine sulfoxide reductase regulation of yeast lifespan reveals reactive oxygen species-dependent and -independent components of aging.A genome-wide analysis of promoter-mediated phenotypic noise in Escherichia coli Defining the plasticity of transcription factor binding sites by Deconstructing DNA consensus sequences: the PhoP-binding sites among gamma/enterobacteria.Dissecting the PhoP regulatory network of Escherichia coli and Salmonella enterica.Incorporating genome-scale tools for studying energy homeostasis.FLAME, a novel fuzzy clustering method for the analysis of DNA microarray data.Configurable pattern-based evolutionary biclustering of gene expression data.Memory acquisition and retrieval impact different epigenetic processes that regulate gene expression.A comprehensive comparison of different clustering methods for reliability analysis of microarray data Subsystem identification through dimensionality reduction of large-scale gene expression data FUMET: a fuzzy network module extraction technique for gene expression data.Clustering Scatter Plots Using Data Depth Measures Recursive cluster elimination (RCE) for classification and feature selection from gene expression data.Diverse activities of viral cis-acting RNA regulatory elements revealed using multicolor, long-term, single-cell imaging yMGV: a cross-species expression data mining tool.Genetic algorithms applied to multi-class clustering for gene expression data Clustering gene expression data based on predicted differential effects of GV interaction.Biclustering of gene expression data by Non-smooth Non-negative Matrix Factorization.Determination of strongly overlapping signaling activity from microarray data.A classification based framework for quantitative description of large-scale microarray data.Nonlinear differential equation model for quantification of transcriptional regulation applied to microarray data of Saccharomyces cerevisiae.Nearest Neighbor Networks: clustering expression data based on gene neighborhoods.Discovering multi-level structures in bio-molecular data through the Bernstein inequality.A ground truth based comparative study on clustering of gene expression data.LS-NMF: a modified non-negative matrix factorization algorithm utilizing uncertainty estimates.Integrated assessment and prediction of transcription factor binding.Using local gene expression similarities to discover regulatory binding site modules.On the detection of functionally coherent groups of protein domains with an extension to protein annotation.Transcription factor target prediction using multiple short expression time series from Arabidopsis thaliana.

P2860

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P2860

Exploring the conditional coregulation of yeast gene expression through fuzzy k-means clustering.

http://www.wikidata.org/entity/Q24793591

description

2002 nî lūn-bûn

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2002 թուականի Հոկտեմբերին հրատարակուած գիտական յօդուած

@hyw

2002 թվականի հոտեմբերին հրատարակված գիտական հոդված

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2002年の論文

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2002年論文

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2002年論文

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2002年論文

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2002年論文

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2002年論文

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2002年论文

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name

Exploring the conditional core ...... rough fuzzy k-means clustering

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Exploring the conditional core ...... ough fuzzy k-means clustering.

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Exploring the conditional core ...... ough fuzzy k-means clustering.

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Exploring the conditional core ...... rough fuzzy k-means clustering

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Exploring the conditional core ...... ough fuzzy k-means clustering.

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Exploring the conditional core ...... rough fuzzy k-means clustering

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Exploring the conditional core ...... ough fuzzy k-means clustering.

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P2860

Metabolism of sulfur amino acids in Saccharomyces cerevisiae

Cluster analysis and display of genome-wide expression patterns

Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization

A prediction-based resampling method for estimating the number of clusters in a dataset.

Fitting a mixture model by expectation maximization to discover motifs in biopolymers

Genomic expression programs in the response of yeast cells to environmental changes

A transmembrane protein with a cdc2+/CDC28-related kinase activity is required for signaling from the ER to the nucleus.

A role for the transcription factors Mbp1 and Swi4 in progression from G1 to S phase.

Coregulation of purine and histidine biosynthesis by the transcriptional activators BAS1 and BAS2.

Signalling from endoplasmic reticulum to nucleus: transcription factor with a basic-leucine zipper motif is required for the unfolded protein-response pathway.

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