Protein search for multiple targets on DNA

Protein-DNA interactions are crucial for all biological processes. One of the most important fundamental aspects of these interactions is the process of protein searching and recognizing specific binding sites on DNA. A large number of experimental and theoretical investigations have been devoted to uncovering the molecular description of these phenomena, but many aspects of the mechanisms of protein search for the targets on DNA remain not well understood. One of the most intriguing problems is the role of multiple targets in protein search dynamics. Using a recently developed theoretical framework we analyze this question in detail. Our method is based on a discrete-state stochastic approach that takes into account most relevant physical-chemical processes and leads to fully analytical description of all dynamic properties. Specifically, systems with two and three targets have been explicitly investigated. It is found that multiple targets in most cases accelerate the search in comparison with a single target situation. However, the acceleration is not always proportional to the number of targets. Surprisingly, there are even situations when it takes longer to find one of the multiple targets in comparison with the single target. It depends on the spatial position of the targets, distances between them, average scanning lengths of protein molecules on DNA, and the total DNA lengths. Physical-chemical explanations of observed results are presented. Our predictions are compared with experimental observations as well as with results from a continuum theory for the protein search. Extensive Monte Carlo computer simulations fully support our theoretical calculations

Canadian targets

Monetary policy - Canada ; Canada ; Money supply - Canada

Production Targets

We present a dynamic quantity setting game, where players may continuously adjust their quantity targets, but incur convex adjustment costs when they do so. These costs allow players to use quantity targets as a partial commitment device. We show that the equilibrium path of such a game is hump-shaped and that the final equilibrium outcome is more competitive than its static analog. We then test the theory using monthly production targets of the Big Three U.S. auto manufacturers during 1965-1995 and show that the hump-shaped dynamic pattern is present in the data. Initially, production targets steadily increase until they peak about 2-3 months before production. Then, they gradually decline to eventual production levels. This qualitative pattern is fairly robust across a range of similar exercises. We conclude that strategic considerations play a role in the planning phase in the auto industry, and that static models may therefore under-estimate the industry's competitiveness.

Concepts of spawning targets

This report discusses the concepts of spawning targets. Spawning target setting is based on the fact that the number of smolts produced by any given river is constrained by habitat availability. This means smolt numbers depend on spawner numbers up to a point, but thereafter smolt production reaches a ceiling. It has been shown, in some rivers at least, that the relationship between egg deposition and smolt production may approximately be described by a mathematical equation. The equation will vary between rivers and there is uncertainty over its exact form. The concept of Maximum Gain (MG) is explained and its application in fisheries management discussed. The author also critically examines the concept of Density Independent Mortality (DIM)

Evolution with Drifting Targets

We consider the question of the stability of evolutionary algorithms to gradual changes, or drift, in the target concept. We define an algorithm to be resistant to drift if, for some inverse polynomial drift rate in the target function, it converges to accuracy 1 -- \epsilon , with polynomial resources, and then stays within that accuracy indefinitely, except with probability \epsilon , at any one time. We show that every evolution algorithm, in the sense of Valiant (2007; 2009), can be converted using the Correlational Query technique of Feldman (2008), into such a drift resistant algorithm. For certain evolutionary algorithms, such as for Boolean conjunctions, we give bounds on the rates of drift that they can resist. We develop some new evolution algorithms that are resistant to significant drift. In particular, we give an algorithm for evolving linear separators over the spherically symmetric distribution that is resistant to a drift rate of O(\epsilon /n), and another algorithm over the more general product normal distributions that resists a smaller drift rate. The above translation result can be also interpreted as one on the robustness of the notion of evolvability itself under changes of definition. As a second result in that direction we show that every evolution algorithm can be converted to a quasi-monotonic one that can evolve from any starting point without the performance ever dipping significantly below that of the starting point. This permits the somewhat unnatural feature of arbitrary performance degradations to be removed from several known robustness translations

RECENT ADVANCES IN METAL-CATALYZED C-H FUNCTIONALIZATION OF PYRIMIDINONES, QUINAZOLINONES AND FUSED QUINAZOLINONES

International audienceThis review emphasises the recent developments in metal-catalyzed functionalization using direct C-H bond activation of pyrimidinones (uracils), quinazolinones and quinazolinone-based fused poly-N-heterocycles as well as metal-catalyzed C-H functionalization of high valuable 2-arylquinazolinones