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Costas D. Maranas

Researcher at Pennsylvania State University

Publications -  279
Citations -  18822

Costas D. Maranas is an academic researcher from Pennsylvania State University. The author has contributed to research in topics: Metabolic network & Biology. The author has an hindex of 52, co-authored 256 publications receiving 16371 citations. Previous affiliations of Costas D. Maranas include Oak Ridge National Laboratory & Princeton University.

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OptKnock: A Bilevel Programming Framework for Identifying Gene Knockout Strategies for Microbial Strain Optimization

TL;DR: The computational OptKnock framework is introduced for suggesting gene deletion strategies leading to the overproduction of chemicals or biochemicals in E. coli, and hints at a growth selection/adaptation system for indirectly evolving overproducing mutants.
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Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

TL;DR: This protocol provides an overview of all new features of the COBRA Toolbox and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios.
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Managing demand uncertainty in supply chain planning

TL;DR: A stochastic programming based approach is described to model the planning process as it reacts to demand realizations unfolding over time, which provides an effective tool for evaluating and actively managing the exposure of an enterprises assets to market uncertainties.
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OptStrain: A computational framework for redesign of microbial production systems

TL;DR: OptStrain provides a useful tool to aid microbial strain design and, more importantly, it establishes an integrated framework to accommodate future modeling developments by establishing an integrated computational framework capable of constructing stoichiometrically balanced pathways.
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αBB: A global optimization method for general constrained nonconvex problems

TL;DR: The proposed branch and bound type algorithm attains finiteε-convergence to the global minimum through the successive subdivision of the original region and the subsequent solution of a series of nonlinear convex minimization problems.