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Full-Text Articles in Genetics and Genomics
Odelay: A Large-Scale Method For Multi-Parameter Quantification Of Yeast Growth., Thurston Herricks, Fred D Mast, Song Li, John D Aitchison
Odelay: A Large-Scale Method For Multi-Parameter Quantification Of Yeast Growth., Thurston Herricks, Fred D Mast, Song Li, John D Aitchison
Articles, Abstracts, and Reports
Growth phenotypes of microorganisms are a strong indicator of their underlying genetic fitness and can be segregated into 3 growth regimes: lag-phase, log-phase, and stationary-phase. Each growth phase can reveal different aspects of fitness that are related to various environmental and genetic conditions. High-resolution and quantitative measurements of all 3 phases of growth are generally difficult to obtain. Here we present a detailed method to characterize all 3 growth phases on solid media using an assay called One-cell Doubling Evaluation of Living Arrays of Yeast (ODELAY). ODELAY quantifies growth phenotypes of individual cells growing into colonies on solid media using …
Solving The Influence Maximization Problem Reveals Regulatory Organization Of The Yeast Cell Cycle., David L Gibbs, Ilya Shmulevich
Solving The Influence Maximization Problem Reveals Regulatory Organization Of The Yeast Cell Cycle., David L Gibbs, Ilya Shmulevich
Articles, Abstracts, and Reports
The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. …
Combining Inferred Regulatory And Reconstructed Metabolic Networks Enhances Phenotype Prediction In Yeast., Zhuo Wang, Samuel A Danziger, Benjamin D Heavner, Shuyi Ma, Jennifer J Smith, Song Li, Thurston Herricks, Evangelos Simeonidis, Nitin Baliga, John D Aitchison, Nathan D Price
Combining Inferred Regulatory And Reconstructed Metabolic Networks Enhances Phenotype Prediction In Yeast., Zhuo Wang, Samuel A Danziger, Benjamin D Heavner, Shuyi Ma, Jennifer J Smith, Song Li, Thurston Herricks, Evangelos Simeonidis, Nitin Baliga, John D Aitchison, Nathan D Price
Articles, Abstracts, and Reports
Gene regulatory and metabolic network models have been used successfully in many organisms, but inherent differences between them make networks difficult to integrate. Probabilistic Regulation Of Metabolism (PROM) provides a partial solution, but it does not incorporate network inference and underperforms in eukaryotes. We present an Integrated Deduced And Metabolism (IDREAM) method that combines statistically inferred Environment and Gene Regulatory Influence Network (EGRIN) models with the PROM framework to create enhanced metabolic-regulatory network models. We used IDREAM to predict phenotypes and genetic interactions between transcription factors and genes encoding metabolic activities in the eukaryote, Saccharomyces cerevisiae. IDREAM models contain many …