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Student Exploration Sheet: Growing Plants
Student Exploration Sheet: Growing Plants

... new substances. The substances that undergo change are called reactants. The new substances are products. Sometimes during a chemical reaction, one type of reactant will be used up before the other reactants. This reactant is the limiting reactant. Using the Limiting Reactants Gizmo™, you can determ ...
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Practice with Chemical Equilibrium (Chapter 14) (Due 2/17)
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... Practice with Chemical Equilibrium (Chapter 14) (Due 2/17) Here are four additional practice exercises concerning chemical equilibrium (Chapter 14). See your instructor if you have questions. Note that for these questions, the symbol "=" is used to indicate a reversible reaction. Your textbook uses ...
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TG_ProteinPartners-ver10 - RI

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... near the active site to change its shape or block it. Many well known poisons such as potassium-cyanide and curare are enzyme inhibitors that interfere with the active site of critical enzymes. The enzyme used in this lab, catalase, has four polypeptide chains, each composed of more than 500 amino a ...
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Chemical reactions unit
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Avogadro`s lab
Avogadro`s lab

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6-1 Endothermic and Exothermic Reactions

... When the solids become liquid, set the flask on a moist piece of wood. Hold until the water freezes and flask sticks to wood. Lift the flask to show its hold on the wood. Exothermic: Put stir bar in Styrofoam cup and set on stir plate. Add 50 mL of water into cup. Turn on stir plate so that water is ...
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... 10. The following figure contains the citric acid cycle. A. Label one reaction as an “aldol reaction,” one reaction as an “electrophilic addition,” and one reaction as a “hydrolysis reaction.” B. Label all reactions in which CO2 is produced. If a cofactor is required, give the cofactor. C. Label al ...
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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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