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Specialisations in the Master Computational Science Understanding
Specialisations in the Master Computational Science Understanding

... Computational Biology (UvA) Parameter Estimation Applied to Medical and Biological Sciences (VU) ...
supplementary material
supplementary material

... 2,3-dimethoxy-5-methyl-6-n-decyl-1,4-benzoquinone (0.1 mM) and 0.25 mM NADH as electron donor, in the presence of 1 mM KCN. The addition of 5 M rotenone allowed us to determine the rotenone-sensitive activity. A total of 50-100 g mitochondrial protein was used for each measurement. Complex II (Suc ...
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Chemical Reaction Th..

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... 6. (5 points) According one text, a 0.92% (w/v) NaCl (0.16 M) solution is “isotonic” with the fluid in red blood cells. Another solution used, “D5W”, is 5.5% (w/v) solution (0.31 M) of glucose in water and is also isotonic with the fluid in red blood cells. Explain how these solutions can have such ...
Factors affecting Enzyme Activity
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enzymes powerpoint - Pasadena High School
enzymes powerpoint - Pasadena High School

... Living systems depend on reactions that occur spontaneously, but at very slow rates. Catalysts are substances that speed up reactions without being permanently altered. No catalyst makes a reaction occur that cannot otherwise occur quick enough for life. Most biological catalysts are proteins (enzym ...
Direct-Coupling Analysis (DCA)
Direct-Coupling Analysis (DCA)

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... typical example to understand how the cell (or the body) controls biological chemical reactions. The enzyme has two (A) sites, one for threonine, and the other for isoleucine. To make a balance of threonine and isoleucine, the enzyme becomes more active when the cell has excess of threonine because ...
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PERIODIC TABLE

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Chemistry Midterm Review Sheet

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Enzymes Notes - The Lesson Locker
Enzymes Notes - The Lesson Locker

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Klaus Schulten: The computational microscope
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... unprecedented treatments and have huge potential economic benefits as they enable highly controlled synthetic biology. Similarly, the examples of best-of-breed simulations today of HIV or drug resistance can lead to new and much more effective treatments but require many simulated “drug trials” in ...
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Ch 11 Chemical Reactions

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M.Sc. (Chemistry)

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Protein regulation: The statistical theory of

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Functional genomics: assigning functions to genome sequences

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Angular momentum
Angular momentum

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Multi-state modeling of biomolecules

Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behaviour of biological molecules or complexes that can adopt a large number of possible functional states.Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: The problem of how to describe and specify a multi-state system (the ""specification problem"") and the problem of how to use a computer to simulate the progress of the system over time (the ""computation problem""). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states, and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators further fall into two categories: Non-spatial simulators such as StochSim, DYNSTOC, RuleMonkey, and NFSim and spatial simulators, including Meredys, SRSim and MCell. Modelers can thus choose from a variety of tools; the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.
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