Pages that link to "Q44615395"
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The following pages link to Computational discovery of gene modules and regulatory networks (Q44615395):
Displaying 50 items.
- Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles (Q21145898) (← links)
- The transcriptional network activated by Cln3 cyclin at the G1-to-S transition of the yeast cell cycle (Q21184036) (← links)
- Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks (Q21284254) (← links)
- An extended transcriptional regulatory network of Escherichia coli and analysis of its hierarchical structure and network motifs (Q24557485) (← links)
- Wisdom of crowds for robust gene network inference (Q24604615) (← links)
- The functional landscape of mouse gene expression (Q24794985) (← links)
- Identifying combinatorial regulation of transcription factors and binding motifs (Q24797613) (← links)
- Defining transcriptional networks through integrative modeling of mRNA expression and transcription factor binding data (Q24798371) (← links)
- Extraction of transcription regulatory signals from genome-wide DNA-protein interaction data (Q24801351) (← links)
- Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach (Q24804022) (← links)
- Tools enabling the elucidation of molecular pathways active in human disease: application to Hepatitis C virus infection (Q24815400) (← links)
- Bioinformatics in microbial biotechnology--a mini review (Q24816749) (← links)
- Dual activation of pathways regulated by steroid receptors and peptide growth factors in primary prostate cancer revealed by Factor Analysis of microarray data (Q24817218) (← links)
- Gene annotation and network inference by phylogenetic profiling (Q25255422) (← links)
- A microarray data-based semi-kinetic method for predicting quantitative dynamics of genetic networks (Q25256640) (← links)
- Integrated analysis of gene expression by Association Rules Discovery (Q25257037) (← links)
- Methods for biological data integration: perspectives and challenges (Q26778582) (← links)
- Constructing gene co-expression networks and predicting functions of unknown genes by random matrix theory (Q27496517) (← links)
- Network biology: understanding the cell's functional organization (Q27861027) (← links)
- Sfp1 is a stress- and nutrient-sensitive regulator of ribosomal protein gene expression (Q27931583) (← links)
- Chemogenomic profiling on a genome-wide scale using reverse-engineered gene networks (Q28239582) (← links)
- Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials (Q28385494) (← links)
- PPARalpha siRNA-treated expression profiles uncover the causal sufficiency network for compound-induced liver hypertrophy (Q28469153) (← links)
- Network-based analysis of affected biological processes in type 2 diabetes models (Q28469240) (← links)
- A predictive model of the oxygen and heme regulatory network in yeast (Q28473966) (← links)
- Developing tools for defining and establishing pathways of toxicity (Q28530404) (← links)
- Network deconvolution as a general method to distinguish direct dependencies in networks (Q30352074) (← links)
- Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection. (Q30431448) (← links)
- A literature-based similarity metric for biological processes. (Q30478029) (← links)
- The Inferelator: an algorithm for learning parsimonious regulatory networks from systems-biology data sets de novo (Q30478837) (← links)
- Topological effects of data incompleteness of gene regulatory networks (Q30559069) (← links)
- Identifying subspace gene clusters from microarray data using low-rank representation (Q30606803) (← links)
- Assessing computational methods for transcription factor target gene identification based on ChIP-seq data (Q30701668) (← links)
- Hierarchical clustering of high-throughput expression data based on general dependences (Q30714277) (← links)
- Modular network construction using eQTL data: an analysis of computational costs and benefits (Q30774984) (← links)
- An unsupervised approach to predict functional relations between genes based on expression data. (Q30814879) (← links)
- Integrating high-throughput and computational data elucidates bacterial networks (Q30928624) (← links)
- MINER: exploratory analysis of gene interaction networks by machine learning from expression data. (Q30950386) (← links)
- Uncovering transcriptional interactions via an adaptive fuzzy logic approach (Q30955339) (← links)
- A data integration methodology for systems biology: experimental verification (Q31020012) (← links)
- A data integration methodology for systems biology (Q31020019) (← links)
- A hypothesis-based approach for identifying the binding specificity of regulatory proteins from chromatin immunoprecipitation data. (Q31023801) (← links)
- Evaluation of different biological data and computational classification methods for use in protein interaction prediction (Q31031427) (← links)
- The model organism as a system: integrating 'omics' data sets (Q31032864) (← links)
- Inferring transcriptional modules from ChIP-chip, motif and microarray data (Q31039595) (← links)
- Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis data (Q31047813) (← links)
- Integration of omics data: how well does it work for bacteria? (Q31066785) (← links)
- Nonlinear differential equation model for quantification of transcriptional regulation applied to microarray data of Saccharomyces cerevisiae (Q31085607) (← links)
- Reconstructing gene-regulatory networks from time series, knock-out data, and prior knowledge (Q31108113) (← links)
- Validating module network learning algorithms using simulated data (Q31112212) (← links)