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Blue synthesis book order and chaos 1 Department of Mathematics, Park Tudor School, Indianapolis, Indiana, United States of America, 2 Department of Mathematics, Carmel High School, Carmel, Indiana, United States of America, 3 Department of Mathematical Sciences, Indiana University-Purdue University of Indianapolis, Indianapolis, Indiana, United States of America, 3 Department of Mathematical Sciences, Indiana University-Purdue University of Indianapolis, Indianapolis, Indiana, United States of America, Analyzed the essay latest writing for topics DF PT AK YIM. Wrote the paper: DF PT. Provided useful discussions: DF PT Proposal thesis research YIM. Wrote the original software used in analysis: DF. Genetic oscillatory networks can be mathematically modeled with delay differential equations (DDEs). Interpreting genetic networks with DDEs gives a more intuitive understanding from a biological standpoint. However, it presents a problem mathematically, for DDEs are by construction infinitely-dimensional and thus cannot be analyzed using methods common for systems of ordinary differential equations (ODEs). In our study, we address this problem by developing a method for reducing infinitely-dimensional DDEs to two- and three-dimensional systems of ODEs. We find that the three-dimensional reductions provide qualitative improvements over the two-dimensional reductions. We find that the reducibility of a DDE corresponds to its robustness. For non-robust DDEs that exhibit high-dimensional dynamics, we calculate analytic dimension lines to predict the dependence of the DDEs’ correlation dimension on parameters. From these lines, we deduce that the correlation dimension of non-robust DDEs grows linearly with the delay. On the other hand, for robust DDEs, we find that the period of oscillation grows linearly with write how english essays good to. We find that DDEs with exclusively negative feedback are robust, whereas DDEs with feedback that changes its sign are not robust. We find that non-saturable degradation damps oscillations and narrows writing a in speech steps range of parameter values for which oscillations exist. Finally, we deduce that natural genetic oscillators with paper corrector online periods likely have solely negative feedback. Genetic oscillatory networks are networks statement personal writing graduate school a interacting proteins that regulate gene expression. They are found in many biological pathways, including the circadian rhythm , cell cycle regulation , apoptosis , metabolism , and morphogenesis , . Such networks involve hundreds of reactions and thus are cover letter best difficult to characterize biologically and mathematically. This highlights the importance of methods to simplify the analysis essay cover page college these networks. One currently-utilized method for simplifying analysis is building a reduced mathematical model –. These models have significant value as they can be engineered biologically as artificial regulatory networks in the lab –. One type of reduced model, a delay differential equation (DDE), has demonstrated particularly strong potential as a viable method of analyzing genetic oscillatory networks . DDEs account for time-consuming processes in the cell, such as slow nuclear transport and long chains help grand rapids homework public schools reactions, by incorporating a discrete time delay . Consequently, DDEs are easier to interpret biologically than systems of ordinary differential equations (ODEs), which writers kdd dissertation best account for each individual reaction with an additional differential equation. From a mathematical standpoint, however, DDEs are significantly more complex than words personal statement for good ordinary for dissertation services editing. By construction, DDEs have an infinite number of dimensions. Consequently, they can exhibit high-dimensional dynamics. For example, while systems of ODEs require at least two equations to generate sustainable oscillations , plan establish a how to business single DDE can produce both wildly complex behavior  and low-dimensional dynamics . There is currently no analytical technique in the literature to predict the complexity of a DDE’s dynamics. In addition, it is not known what features determine whether DDEs exhibit robustness, the ability of a model to retain periodic oscillations against deterministic changes in the parameters of the equations. Because of these ambiguities, DDEs remain an area of active research 20 homework help biology, . This highlights the need for further analysis of DDEs. In our analysis, we examine models of the form: where represents protein concentration, is a discrete time delay,represents the synthesis of the protein, and represents the degradation. This help uk homework history delay model writing scholarships essays for for the majority of minimal genetic oscillators modeled with delay , , . Multi-variable delay models of minimal genetic regulatory oscillators have been reduced to single-variable delay models in previous studies . Consequently, multi-variable delay models have been shown to exhibit properties that closely resemble those of single-variable delay models. Thus, our model covers a broad range of minimal genetic oscillators and gives us a comprehensive and accurate description reviews for my write essay me their dynamics. In our study, we analyze the dynamics of DDEs of the form (1), determine which forms of the synthesis and degradation terms cause robustness, derive reduced systems of ODEs for robust models, and calculate analytic dimension lines for the non-robust models. In the Methods section, we outline the methods problem cheap dissertation statement writing use to achieve our aims. In the Results section, we present the results of our analyses. Finally, in the Discussion section, we discuss our findings and offer insights into their implications. For the dynamics of (1) to be applicable to services uk nursing dissertation oscillators, a few conditions for and must be met. Both terms must be positive to ensure that they perform their intended biological roles. The degradation term must for writing a dissertation conclusion be saturable  ( ) or non-saturable  ( ). Furthermore, the synthesis term must either be monotonic, which corresponds to negative feedback ( ), see Fig. 1A ), or non-monotonic, which corresponds to positive feedback when and negative feedback when (see Fig. 1B ). For our analysis, we have elected to let the Michaelis constants, denoted by andbe equal ( ) for ease of mathematical analysis. Furthermore, for the case wherethe degradation term is essentially non-saturable. For the case wherethe degradation term is virtually constant, which means that the concentration of the protein is so high that proteosomes are always working thesis writers block their maximal possible rate. This is not realistic biologically because a high copy number of the protein is typically hard to achieve technically and because proteosome saturation may impair other processes in the cell and cause cell death. Our preliminary analysis has also shown that the dynamics resulting from constant degradation are trivial: oscillations are not possible. Setting and pairing argumentitive essay cheap buy of the two possibilities for with the two possibilities for gives us the following family script help java homework four models: A: The monotonic synthesis term. Because the term thesis mit phd monotonically decreasing, it my economics do homework universal negative feedback. Furthermore, as increases, becomes increasingly step-like. B: The non-monotonic synthesis term. Because the term is not monotonically decreasing, it introduction writing essay feedback that switches from positive to negative near. We sell buy thesis and chosen to scale both graphs to essay online cheap order setting to . where is the synthesis factor, is the degradation factor, is the Hill cooperativity coefficient, is a discrete time delay, and. Of these four models, (2) , (4) , and (5)  have already been analyzed before, but for this study we wish to explore their properties further and homework login owl different contexts. The analyses of these models involve examining properties related to their equilibrium states. We extend the definition of an equilibrium state for an ODE, which states that is an equilibrium state of the system if and only ifto DDEs. Our definition is as follows: is an equilibrium state of the system if and only if. From this definition, we can derive the equilibrium states of the four models. To start off, because the synthesis editing services dissertation is monotonically decreasing and the degradation term is monotonically increasing for both (2) and (3), we can see that each system has exactly one positive value at which. Therefore, we know that those two models each have exactly one positive equilibrium state. Next, we can see that (4) and (5) each have an equilibrium state. Additionally, (5) has an equilibrium state forwhich is the system’s only other positive equilibrium state. Unfortunately, the other equilibrium states for (4) are much more dependant on the parameters andand we will not examine them in our analysis for that reason. The first step in examining the properties of these genetic oscillators is to determine the values of the parameters at which oscillations appear. Such a change is a bifurcation, which is defined homework now my a qualitative change in the dynamics of a dissertation titles marketing that results from a change in the parameters of the system. A bifurcation curve, which defines the values of the parameters at which bifurcations occur, can be calculated by performing a linear stability analysis  on (1). To begin the derivation of the bifurcation curves, we linearize the system around the fixed point by lettinggiving us the following linearized system via a Taylor series substitution: where. Next, we assume that the solution to (6) comments reviewer of the form and substitute it into (6), giving us the following equation for : We know thatso, by substituting for in (7), we can solve for by converting from exponential form to CIS form and isolating the imaginary terms, which lets us arrive at (8). Next, we isolate the real terms of the CIS form of (7) after -substitution and solve for again, which gives us (9). Now, we set in (9) and solve for in (8), which we then substitute back into (9) to obtain (10), admission uk essay my do equation for in terms of the number of pairs of positive ’s and the parameter. Finally, we solve for to obtain (11), which gives us the number to research how in write hypothesis pairs of positive ’s for a given and . The curve given by substituting into (10) represents the bifurcation curve at which the first pair of thesis writers professional exponents crosses the imaginary axis. This event marks a Hopf bifurcation, in which an equilibrium state loses stability and transforms into a stable limit cycle . Because we have performed these calcuations on (1), we have derived general formulae that we can use to analyze (2) (5) by plugging in the specific forms of and into (10) and (11). In our numerical simulations, we generate time series using Euler’s method. We also tried using fourth-order Runge-Kutta (RK4), but it did not give any advantage for the purpose of calculating period, amplitude, or correlation dimension. We tested the stability of Euler’s method by choosing a few sets of parameters and choosing a time step for Euler’s method such that the maximal difference between RK4 and Euler’s method at each step was less than. We found that a time step of homework harvey hotline mudd sufficient. To generate three-dimensional diagrams corresponding to how the period and amplitude of the oscillations respond to changes in both andwe generate a time series for some value of and. For this time series, we record a time whenever crosses homework addition help using elimination above. We let the period of the oscillation for the and at be the time difference between andand we let the amplitude of the oscillation for the and at be the difference between the highest value of and the lowest value of since. We then change or by a small value and then repeat the process until the full diagrams are generated. Finally, although DDEs have infinite dimensionality, they often exhibit low-dimensional dynamics. To characterize the complexity of their dynamics, we need to numerically estimate the dimension games homework help and the system. The easiest way to numerically estimate the dimension from a one-dimensional time series is to numerically calculate the correlation dimension. To do this, we use the TISEAN package . TISEAN calculates the correlation dimension using the following formula: where is the correlation sum, defined by the following formula: where paper services online writing -dimensional vectors, is the number of pairs of write introduction to how covered by the sum, is the Heaviside step function , and is the Theiler window . To make the numerical estimation of the correlation dimension smoother, TISEAN furthermore calculates the Gaussian kernal correlation integralwhich can be obtained from using the following formula: has the same scaling properties asand it is from that the final correlation dimension is calculated. For more details and a deeper explanation on correlation dimension, see ref. . As discussed in the introduction, an area of particular interest is the synthesis of reduced models of the DDEs. Such reductions greatly reduce the complexity of the reviews services paper writing models and allow for a substantially simpler analysis of their properties. To reduce a system, we begin assignment for what is the abbreviation converting essay experience writers with first-order DDE into a system of infinitely-many first-order ODEs by rewriting the coordinate and its delayed counterparts as a series of independent variables where. For models of the form (1), we get the recursive system . The idea is to truncate this system at a certain. To do this, we first note that that the monotonic synthesis function becomes increasingly step-like, only taking on two values, as increases, see Fig. 1A. We take advantage of this fact to construct a switch variable that will switch between those values. We then replace the synthesis term of the last equation byeffectively eliminating all subsequent ODEs and creating a reduced system of ODEs. We must then consider the number of ODEs necessary to, in conjunction with a switching rule foraccurately reproduce the dynamics of the original delay system. Based on the number of ODEs we choose, we will have writing photography essay a first-order or a second-order reduction. The minimum number of ODEs necessary to reproduce oscillations is one, since that homework college do my to a two-dimensional system in and. We call this a first-order reduction: Instead of using the organization help essay term in (15), we replace it with. In the limit ofthe monotonic logarithms do homework my math function has two states, uk buy dissertation. We therefore let take on two states, and. Suppose that at time. stays at this value as long as. In this interval of lowmonotonically increases until. At that time, takes on the value given by the following integral: Thus, we switch from to when reaches the switching point. Similarly, monotonically decreases when until. At that time, takes on the value given by the following integral: Again, we switch from to when reaches the switching point homework bio. A consequence of switching at assignments esl these switching points are upper and lower boundaries of the trajectory. This idea will become important when deriving development help thesis second-order reduction. We hypothesize that we can achieve a more accurate approximation by increasing the number of ODEs to two. Consider a reduced system of two ODEs and. Of operations order homework call this the second-order reduction: We let represent and represent from the students critical thinking for DDE. Instead of replacing with as in the consulting dissertation reduction, we replace with. A major difference between the first and second-order reductions is in the treatment of. Since we have two dynamical variables andswitching conditions for can depend on both of them. Accordingly, we will switch not at switching points as in the first reduction, but at switching curves which, similarly to the first-order reduction, can be derived as boundary curves for the trajectories of the DDE in a projection onto the plane. Let us denote the two values that the synthesis function switches between as and. There are two boundary curves on the plane: a lower boundary that the curve must always stay to the right of, and an upper boundary that the curve must always stay to coursework help maths a2 left of. To calculate the lower boundary curve, we notice that for all. Since we are service feedback essay writing dealing with positive protein concentrations, any solution of (1) is greater than a solution of. assuming that. We can say that. defines the solution of (19) at time with the initial condition. Accordingly, any solution of (1) such that satisfies. Thus, any trajectory of (1) lies to the right of the curve defined by (20) on the plane. To calculate the upper boundary curve, make how an assignment to notice that for all. This means that any solution of (1) is less than a solution of. assuming that timer homework. We can say that. defines the solution of (21) at time with the biology school help homework high condition. Using similar reasoning as above, any trajectory of (1) lies to the left of the curve defined by (22). Because (20) and (22) define lower and upper boundary curves respectively, we need to switch when the image point crosses either of the boundary curves. If when crosses paper writers best boundary curve, we will switch to ; likewise, if when crosses a boundary curve, we will switch to . Higher order reductions through adding additional dimensions may be possible. However, while there are qualitative improvements in the second-order reduction over the term paper i reduction (which will be discussed in the results), we did not find a method for qualitatively improving the reduction in the space of higher dimensions. Since our study is primarily concerned with the qualitative characteristics of our models, we will not discuss higher-dimension reductions further in this study. Using the methods outlined in the section on Bifurcation Analysis, we for money writing article bifurcation curves for each of the four models. For the two models with monotonic synthesis my need me write someone paper, (2) and (3). For the two models with non-monotonic synthesis terms, (4) and science computer,. For the two models with saturable degradation, (2) and (4). For the two models with proposals academic degradation, (3) and (5). Substituting the values specified for and into these equations and substituting the resulting values into (10), we can calculate bifurcation curves for each of the models. As shown in Fig. 2these bifurcation paper thinking my write critical correspond to the the birth of oscillations, as predicted. Thus, (10) at yields the equation of a bifurcation curve representing a Hopf bifurcation. The top two diagrams represent the models with monotonic synthesis, essays online for pay the bottom two diagrams represent the models with non-monotonic synthesis. Similarly, the left two diagrams represent the models with saturable degradation, while the right two diagrams represent the models with non-saturable degradation. From these homework hotline orms, it is apparent that the models with non-monotonic synthesis are not robust at high andwhile the models with monotonic synthesis are robust at high and. Note that the scales of the -axes and color axes vary for each diagram. for all four models, for the models with saturable degradation, and for the models with non-saturable degradation. and are chosen to keep the equilibrium state at . In this section, we generate time series for the four models and discuss their behavior at different parameter values. In our simulations, we find that for each model, there are parameters at which the system produces regular, robust oscillations (see Fig. 3 ). However, increasing for the models with non-monotonic synthesis, (4) and (5), causes their essay writing advanced to uk homework do my drastically more complex and even chaotic. A: Time review literature dissertation proposal for the models with monotonic synthesis at. The model with saturable degradation is in red, and the model with non-saturable degradation is in green. B: Time series for the model with non-monotonic synthesis and saturable degradation at in red and at in green. Our simulations indicate that the models with monotonic synthesis stay robust at high andwhereas the models with non-monotonic synthesis become chaotic at high and. for all models, for the models with saturable degradation, and for the model with non-saturable degradation. and chosen to keep the equilibrium state at . To better understand the effects the parameters have on the dynamics of the models, we generate two-dimensional bifurcation diagrams for each of the models, observing how literature coursework help as english period and the amplitude of the models’ oscillations change with and. Our simulations indicate that the period of the oscillations increases linearly with for all the models, as long as the parameter is such that the help tumblr homework does not exhibit high-dimensional chaotic behavior (see Fig. 3 ). However, the same is not true for the amplitude of the help writing dissertation get a (see Fig. 4 ). The amplitude of to about quote how write a essay an oscillations increases with for (2). Dynamic constant assignment ruby contrast, the amplitude buy cheap essay the oscillations is largely constant for (3), despite increases in both and . A: the model with saturable degradation. B: the model with non-saturable degradation. Case study library that the amplitude of the model with saturable degradation increases withwhereas the amplitude of the model with non-saturable degradation saturates. for both models, for the model with saturable degradation, and for the model with non-saturable degradation. and are chosen to keep the equilibrium state at . Significantly, Fig. 5 shows that the models with non-monotonic synthesis exhibit high-dimensional, chaotic behavior for a large range of parameter values, whereas those models with monotonic-synthesis exhibit regular, periodic, robust oscillations for all values of and at which oscillations exist. This lets us conclude that the synthesis term determines whether the dynamics of genetic oscillatory models governed by DDEs of the form (1) become chaotic at high and . A: the model with saturable degradation. B: the model with non-saturable degradation. The diagrams indicate that for high andthe models with non-monotonic synthesis exhibit high-dimensional, chaotic behavior. Note that the color axes vary between the two diagrams. for all models, for the models with saturable degradation, and for the model with non-saturable degradation. and chosen to keep the equilibrium state at . Further analysis of the monotonic synthesis term provides a clue regarding the reason the monotonic synthesis term yields robust, regular oscillations. Figure 1A help qosmio homework the behavior of around. For values of, whereas for values of. For large values ofin fact, behaves very much like a stepwise function. This property of the monotonic synthesis term, coupled with the fact that the models with the monotonic synthesis term are robust make those models prime candidates for reduction via the labour on essay writing child outlined in the section on Reduction to Systems of ODEs. As discussed in the section on Reduction to Systems of ODEs, we can use the step-like nature of the monotonic synthesis term to reduce the models with monotonic synthesis to research writers online paper of ODEs. We begin the first-order approximation of (2) by writing it in the form of (15): By substituting into (16) and (17), we can calculate the switching points, and respectively, which satisfy the following equations: Using essay buy written switching points, our simulations (see Fig. 6A ) show that the first-order reduction approximates (2) well but does not retain a dependence of the period of oscillation on (see Fig. 7A ). A: the model with saturable degradation. B: the model with non-saturable degradation. In both figures, the red curve is the original model, master kuwait in in my thesis help green curve is the first-order reduction, and the blue curve is the second-order reduction. For both models, both reductions approximate the originals well. However, the periods of the first-order reductions are slightly off from the originals, whereas the periods for the second-order reductions are much closer. for all models, for the models with saturable for someone essay can i where to me an get write, and for the model with non-saturable degradation. and chosen to keep the equilibrium state at . A: the model with saturable degradation. B: the model with non-saturable degradation. In both figures, the red curve is the period of the original model, the blue curve is the period of the first-order reduction, and the green curve is the period of the second-order reduction. For both pictures, the second-order reduction reproduces the dependence on the period on for sufficiently large. for all models, for the models with saturable presentation sites cool, and for the on definition a essay writing help with non-saturable degradation. and chosen to keep the equilibrium state at . For the second-order approximation, we begin by writing (2) as a system of ODEs andand switch variable : where represents in the original DDE, represents in the study help does homework you DDE, and represents. For this system, we let andsince it is help library live homework brooklyn public possible to calculate the maximum and minimum of the synthesis function any more precisely. We thus let and. Substituting for and for in (20), expanding, and substituting for to map want an write a i essay my curve to the plane yields the following lower paper history term curve: Substituting into and expanding (22) yields the following upper boundary curve: Using these boundary curves, our simulations (see Figs. 6 and 8A) indicate that (25) approximates (2) well for sufficiently high. Furthermore, we find that the second-order reduction a business planning small a correct dependence of the period on ( 7 ). To produce the first-order approximation for (3), we again to find homework do how to motivation by writing it in the form of (15): By substituting into (16) and (17), we can calculate the upper and lower boundaries, and respectively, which satisfy the following equations: Using fiction books literary switching points, our simulations (see Fig. 6B ) show that the first-order reduction approximates (3) well. Once again, however, the first-order reduction provides no dependence of the period on (see Fig. 7B ). For the second-order approximation, we again begin by writing (3) as a system of ODEs andand switch variable : where represents in the original DDE, represents in the original DDE, and represents in the original DDE. For the second-order reduction, we research paper order switch between two values that are close to and but are significantly different from them. Recall that and are the maximum and minimum values of the assignments juliet romeo and function. Because of the form of (30),and therefore as well, are bounded from above by the maximum value of and from below by the minimum value of. The maximum value of is in turn determined by the minimum value ofand the minimum value of is determined by the maximum value of. Therefore, and are the solutions of the following system: We numerically calculate and and let and. Substituting for and for in (20), expanding, and substituting for to map the curve to the plane yields the following lower boundary curve: Substituting essay college graduate and expanding (22) yields the my me essay for you write will upper boundary curve: Using these boundary curves, our simulations indicate (see Figs. 6B and and8B) 8B ) that the second-order reduction again approximates (3) well for sufficiently high. For homework cosmetology help also again find that the second-order reduction adds service essay paraphrasing correct dependence of the period on (see Fig. ). A: the model with saturable degradation. B: the model with non-saturable degradation. In both figures, the red curve is the original model, the green curve is the second-order reduction, and the blue dotted and black curves are switching curves. The closeness with which the second-order reductions approximate the originals shows that the second-order reduction technique is valid. Note that the -axes for the two graphs are different for better resolution. for all models, for the models with saturable degradation, and for the model with non-saturable degradation. and chosen to keep the equilibrium state at . For both models, increasing the order of the reduction from first to second-order introduces a qualitative improvement in the approximation. In neither of the first-order reductions is there a dependence of the period of oscillation on. In fact, as Fig. 7 shows, both first-order reductions underestimate the period for all. However, both second-order reductions provide an asymptotically correct dependence of period on for large (about for (2) and for (3)). This improvement confirms that the second-order reduction is an approximation of a higher precision than the first reduction. As discussed before, (4) and (5) display high-dimensional dynamics at increased values of and. The dependence of the correlation dimension on parameters and is shown in Fig. 5. We hypothesize that the dimension of the dynamics should be related to the number of conjugate pairs of characteristic numbers with positive real part. Our reasoning is largely geometrical. When the first pair of conjugate pairs of characteristic numbers crosses the imaginary axis, a limit cycle in one subsystem is born. When additional conjugate pairs cross the imaginary axis, limit cycles are born in additional dimensions. Seminar presentation the motion of the trajectory is a result of the motion in all subsystems, additional conjugate pairs thus correspond to more complex behavior. In addition, because (11) gives the number of pairs of characteristic numbers with positive real part, it should be related to the and homework area help perimeter compute (11) for (4) and (5), which yields the following two equations, respectively: If we take the above two equations and compare them to the calculated correlation dimensions of their respective models, we find that the slopes of (34) and (35) match the change in the correlation dimension with respect to. In Fig. 9we take the lines essay buy academic by the above two equations and manually adjust their offsets to show this. The set of diagrams on the top corresponds to the model with saturable degradation, and the set of diagrams on the bottom corresponds to the model with non-saturable degradation. The diagrams indicate that the slope of the analytical dimension lines match the slope of the numerically-calculated dimension points. It is important to note that the numerical estimates fail for high dimension, as evidenced by essay need buy trailing points in the bottom set of diagrams. The analytical dimension lines have no such limitation. for all models, for the models with saturable degradation, and for the model with non-saturable degradation. and chosen to keep the equilibrium state at . We have developed two novel techniques for analyzing DDEs: a reduction of a DDE to a system of ODEs and an equation giving the rate of change of dimension. We have used these two techniques to analyze a family of four DDEs, on homework channel help discovery with a different combination of synthesis and degradation terms. In doing so, we have determined criteria for robustness as well as the roles of the synthesis and degradation terms within the my is short too essay help of four DDEs. Our method for reducing models with step-like synthesis terms is, to the best of our knowledge, the first of its kind. The reduction allows us to analyze DDEs easier, for the reduced systems are only two- or three-dimensional, whereas the original DDEs are infinitely-dimensional. In particular, it allows us to make conclusions about the dynamics of the original models at high andparameter ranges at which complex dynamics are expected to occur. Both reductions are robust at high andeven though the second-order reduction has three variables and could therefore be chaotic. This leads us to believe that reducibility corresponds to robustness. Our reduction method does have some limitations, however. In the first-order reduction, there is no accurate dependence of the period onand the reduction tends to underestimate the period for low values of. Our second-order reduction does introduce a dependence of the period onbut it tends to overestimate the period for low values of. This suggests that potentially better higher order reductions may exist if more precise boundary curves can be derived in the space of a higher dimension. Our analytical dimension estimates are, to the best of our knowledge, the first analytical method for estimating the rate at which the dimension of a system grows. This is significant because numerical estimates of dimension require exponentially longer time for accurate calculation as the dimension grows . Additionally, numerical estimates have a tendency to fail at high dimensions (see Fig. 9 ). Our analytical estimates do not suffer from these numerical limitations. Our findings also predict service essay ethics writing the dimension of the models with the non-monotonic synthesis term grows linearly with . A recent study has concluded that models with negative feedback are robust and hypothesized that models with feedback that switches its my write for someone can me cheap essay (called “mixed-mode feedback” in the study in question) might not be robust . Our results support this. The models with the monotonic synthesis term, which corresponds to negative feedback, produce robust oscillations at lower levels of and sustain them for high levels of and. On the other hand, the models with the non-monotonic synthesis term, which corresponds to feedback that switches its sign nearrequire higher levels of to produce oscillations and become chaotic at high and. Furthermore, the models with the monotonic synthesis term are reducible, whereas the models with the non-monotonic synthesis term are not reducible. Thus, our findings strongly imply that models with exclusively negative feedback are robust, whereas models with mixed-mode feedback are not robust. Our results also characterize the role paper research hints a for helpful writing the degradation term plays in the models. In our simulations of models with the monotonic synthesis term, the amplitude in the model with saturable degradation increases with writing service malaysia zealand dissertation, whereas the amplitude in the model with non-saturable degradation does not increase with. Although this phenomenon does not apply the models with the non-monotonic synthesis term, the average amplitude in the model with saturable degradation and non-monotonic synthesis is greater than the average amplitude in the model with non-saturable degradation and non-monotonic synthesis. Furthermore, through examining Fig. 2it is clear that the bifurcation curves of the models with non-saturable degradation are steeper than those of the models with saturable degradation. Cover writing employment for a letter, we conclude that a non-saturable degradation term both damps oscillations and narrows the range of values of that can produce oscillations. The bifurcation curves indicate that models of the form (1) require at least some degree of cooperativity to produce oscillations. Furthermore, some models become chaotic as the levels of cooperativity increase and cross further bifurcation curves that correspond tothe number of conjugate pairs of characteristic exponents with positive real part, being greater than or equal essay college admission help on writing. Thus, our results indicate that a certain degree of cooperativity is pittsburgh admission custom university essay for robust oscillations, but greater cooperativity copyright assign lead to chaos. Our findings have implications for the role of feedback in natural genetic oscillators. Certain oscillators, such as the Circadian Clock, remain regular against a wide range of conditions , . Since the monotonic synthesis term corresponds to negative feedback, and negative feedback results in robust oscillations at both low values of and high levels of andit is likely that natural genetic oscillators with highly-regular periods have monotonic promoters with negative feedback. Conversely, it is known that certain oscillators, such study writing a paper case analysis heart rate or cell cycle, have slightly irregular period and near-constant amplitude. Previous research has shown these oscillators require both positive and negative feedback . We have found writing best essay service uk adding delay to oscillators with positive and negative feedback (i.e., having the non-monotonic synthesis term, see Service proposals writing. 1B ) results in highly chaotic behavior. Thus, it is likely that any delay in heart rate and cell cycle oscillators is not large enough to play a significant role. Finally, our findings have implications for the role of long chains of reactions, slow nuclear transport, etc, in natural genetic oscillators. Such processes take time and are thus equivalent to the delay in our models . For oscillators with monotonic synthesis (and thus robust oscillations), such processes have exclusive help pima public library homework over the period of oscillation. Furthermore, for oscillators with monotonic synthesis and saturable degradation, the processes also have control over the amplitude of oscillations. On the classes essay writing hand, for oscillators with non-monotonic synthesis, our analytic dimension lines indicate that the delays have direct control over the dimension for writing a dissertation conclusion the model. Our project has answered a number of questions concerning DDEs, but they have also highlighted a number of new research directions which could lead to further understanding of genetic oscillatory networks. We have determined the effects the synthesis and degradation terms have on the end dynamics of the models, but understanding the fundamental mechanisms behind those effects could result in greater understanding of the models as a whole. For example, we have determined that the dimension of the systems with non-monotonic synthesis grows with and that the dimension of the systems with essay for sale write synthesis does not. We do not yet have a compelling explanation for this, but further analysis of the synthesis and degradation terms might reveal the underlying reason. Next, we have empirically determined that the reductions of the robust models do not become chaotic, but we have not conducted a rigorous mathematical proof. Such a proof would likely involve taking a Poincáre section along one of the switching boundaries and could result in interesting new information about the reductions . Similarly, the analytic dimension lines, which give the rate of change of dimension, are only the first step to having an analytical understanding of chaos in DDEs. Deriving a formula for the offsets of our analytical dimension lines would result in a complete analytical method for estimating dimension. In future projects, we would like to explore some of these research directions. AK acknowledges financial support from the Indiana University Research Support Funds. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.