Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns - Wikidata - awgldk - TriplyDB

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

http://www.wikidata.org/entity/Q35539757

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Protein 3D structure computed from evolutionary sequence variation A small world of neuronal synchrony Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models Efficient network reconstruction from dynamical cascades identifies small-world topology of neuronal avalanches Maximum entropy reconstructions of dynamic signaling networks from quantitative proteomics data Perturbation biology: inferring signaling networks in cellular systems On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach Trends in modeling Biomedical Complex Systems Thermodynamics and signatures of criticality in a network of neurons.Bayesian network prior: network analysis of biological data using external knowledge.Experimental assessment of static and dynamic algorithms for gene regulation inference from time series expression data.From principal component to direct coupling analysis of coevolution in proteins: low-eigenvalue modes are needed for structure prediction Learning maximum entropy models from finite-size data sets: A fast data-driven algorithm allows sampling from the posterior distribution.Improving landscape inference by integrating heterogeneous data in the inverse Ising problem.Reconstructing networks of pathways via significance analysis of their intersections.Sample entropy analysis of cervical neoplasia gene-expression signatures Inferring species interactions in tropical forests.Identification of crosstalk between phosphoprotein signaling pathways in RAW 264.7 macrophage cells.A semi-supervised learning approach to predict synthetic genetic interactions by combining functional and topological properties of functional gene network.Using entropy maximization to understand the determinants of structural dynamics beyond native contact topology Maximally informative pairwise interactions in networks Social interactions dominate speed control in poising natural flocks near criticality.Maximal entropy inference of oncogenicity from phosphorylation signaling.Convergence of logic of cellular regulation in different premalignant cells by an information theoretic approach.The fitness landscape of HIV-1 gag: advanced modeling approaches and validation of model predictions by in vitro testing.Measuring ambiguity in HLA typing methods.Joint modeling of multiple social networks to elucidate primate social dynamics: I. maximum entropy principle and network-based interactions.Protein signaling networks from single cell fluctuations and information theory profiling.Searching for collective behavior in a large network of sensory neurons Correlations and functional connections in a population of grid cells.On a fundamental structure of gene networks in living cells Statistical mechanics for natural flocks of birds.A Multi-Method Approach for Proteomic Network Inference in 11 Human Cancers.Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations.Genetic Background Specific Hypoxia Resistance in Rat is Correlated with Balanced Activation of a Cross-Chromosomal Genetic Network Centering on Physiological Homeostasis.Reverse engineering and analysis of large genome-scale gene networks.Statistical mechanics of letters in words.Network link prediction by global silencing of indirect correlations High-order social interactions in groups of mice.Pairwise interactions and the battle against combinatorics in multidrug therapies.

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P2860

Using the principle of entropy maximization to infer genetic interaction networks from gene expression patterns

http://www.wikidata.org/entity/Q35539757

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2006 nî lūn-bûn

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2006 թուականի Նոյեմբերին հրատարակուած գիտական յօդուած

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Using the principle of entropy ...... from gene expression patterns

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Using the principle of entropy ...... from gene expression patterns

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Proceedings of the National Academy of Sciences of the United States of America

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Using the principle of entropy ...... from gene expression patterns

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Jayanth R Banavar

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Nina V Fedoroff

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Timothy R Lezon

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P2860

Information Theory and Statistical Mechanics

Cluster analysis and display of genome-wide expression patterns

Weak pairwise correlations imply strongly correlated network states in a neural population

Multi-level response of the yeast genome to glucose

Information Theory and Statistical Mechanics. II

Exploring the metabolic and genetic control of gene expression on a genomic scale

Chromatin-mediated regulation of nucleolar structure and RNA Pol I localization by TOR.

Genetic and biochemical interactions between the Arp2/3 complex, Cmd1p, casein kinase II, and Tub4p in yeast.

Nicotinamide and PNC1 govern lifespan extension by calorie restriction in Saccharomyces cerevisiae.

MMI1 (YKL056c, TMA19), the yeast orthologue of the translationally controlled tumor protein (TCTP) has apoptotic functions and interacts with both microtubules and mitochondria.

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19033-19038

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10.1073/PNAS.0609152103

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103

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