The Systems Biology of COVID-19 and the SARS-CoV-2 virus. The class will build a foundation that includes the emergence of complexity, simple biological subsystems, their reductionist and equivalent toy and organ-chip models, and the measurements required to specify model architecture and parameters. Applications to biology, physiology, medicine, chemical and biological defense, pharmacology, drug discovery, and toxicology. UGrad: PHYS 240 01 and BME 290B; Grad: PHYS 326 and BME 395C.
Tuesday, October 8, 2013
SysBio13 Asgn_11_Class_15_Article_19_2013_10_10
Read Article 19 B. Novak and J. J. Tyson. Design principles of
biochemical oscillators. Nature Rev.Mol.Cell Biol. 9 (12):981-991,
2008. Answer the Pop Quiz before reading, and then read the article to
obtain an overview of the concepts. We will drill down next class. Post
a PCRC.
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0. Knew the concepts and background of oscillators and switches that was elucidated in the previous Tyson paper.
ReplyDelete1. Learned the biological application of oscillators and key examples. Understanding the concepts of oscillators makes the understanding of in vivo biochemical interactions and biology easier since it provides a researcher a platform for which to attach studied interactions.
2. Do oscillators or the concept behind biological oscillators explain it all? Or rather is there another “phase space” to which greater networks and interactions can be applied?
3. A presentation highlighting some of the key biological oscillator examples.
4. The concept of biological oscillators is built around the negative feedback loop which ensures that if the concentration of X gets too large then it decreases and if it is too small then it increases....so this is in one loop so how is the X effected if there are multiple loops around X and use X?
Frank "Edad" Block, Jr.
ReplyDeleteSysBio13 Asgn_11_Class_15_Article_19_2013_10_10
0. Knew: The previous Tyson article.
1. Learned: Methods of cellular oscillation.
2. Pressing: How are oscillations synchronized? For instance circadian rhythm is synched to light and dark (except when one is jetlagged). Also there is a phenomenon in which women who live together (e.g. in a barracks) will usually synch their menstrual cycles. How?
3. Presentation: How to synch oscillations.
4. Thoughts: How does memory (i.e., recall of events) really work? Could it be stored (in part) in oscillations, or in the speed of oscillations? Stored in the hysteresis of a reaction? In a discontinuous jump? How does forgetting work?
Regarding your questions about synchronization, I would look up Steven Strogatz who has done research from pulse-coupled oscillations in pacemaker cells, to synchronization in Josephson junctions, to fireflies. He's written a fairly technical book great for self-education on nonlinear dynamics, and a pop-sciencey book on synchronization.
Deletehttp://scholar.google.com/citations?user=FxyRWlcAAAAJ&hl=en
David Wooten
ReplyDeleteSysBio13 Asgn_11_Class_15_Article_19_2013_10_10
0. Knew: Dynamical systems theory and chaos / previous article
1. Learned: Different classes of oscillators. Also, interestingly, that there aren't good experimental measurements of chaos inside cells, because single cell experiments are too noisy, and many cell experiments average out the details too much.
2. Pressing ?: On Figure 2e, they show p as taking non-integer values (i.e. p=0.7 is allowable). In the text p was the order of the oligomer (monomer=1, dimer=2, tetramer=3, etc). In their analysis they mentioned that Kd/Km was sufficiently large, the system could oscillate, but this would require values of p<1 (non integers). Are such regions physically reasonable if we assume the equations (Eq 5 for instance) are abstractions of what happens, and a more detailed model might have purely integer values of p which, in this approximated version, become non-integer, but not as physically meaningful?
Also, what might be an evolutionary advantage to deterministic chaos in a cell? Is it possible that some regulatory machinery exists to control chaos? Do cells show "life at the edge of chaos"?
3. Presentation: Chaos theory in information processing. Control of chaos.
4. Thoughts: I thought this was a great paper! I would have liked to see more analysis of particular biochemical pathways (like the cell-cycle control in the last paper) and am very interested in how to analyze systems with many biochemical reaction motifs coupled together. I really liked the constraint diagrams, particularly the timescale constraints. I am very interested in what happens when you couple oscillating motifs with different timescales together, or even similar timescales, and what roll this plays in information processing within a cell.
0 Knew: Concepts of oscillations as discussed in Tyson article.
ReplyDelete1 Learned: There are certain parameters required to have oscillations, many different oscillation motifs that can be combined to produce different results. Oscillatory mechanisms can evolve.
2 Pressing: It says in the last paragraph that quantitative modeling is needed to determine/ study these oscillations. Why is this so? Does this mean taking physiological data or just "running the equations"? So, just analyzing the components and determining which "class" it is isn't sufficient?
3 Presentation: Oscillation Dependent Diseases
4 Thoughts: This was a great paper to read. It helped me to understand just how important oscillations are in biology. It was interesting to see how adding different components, such as time delay and positive feedback, produced oscillations. It was also interesting to learn reasons why physiology works the way it does!
0. Knew the basics of oscillations from the previous paper, various characteristics that make up such networks.
ReplyDelete1. Learned about the classes of oscillators and what characteristics define them. Different examples of where these are found in nature. What restrictions there are to ensure that a system oscillates.
2. How complex of a system of connected oscillators can we currently model? The workings of a cell are highly connected. What examples are there of oscillation on a larger scale, that is not on the molecular scale? How do we recognize/model deterministic chaos?
3. Understanding chaotic trajectories
4. I enjoyed this paper, it was really helpful in understanding exactly what is needed to control biological oscillations. Their works cited also has annotations, which is extremely helpful.
Large scale oscillation-> Lotka-Voltera equation (but that's a cheap example)
Delete0. Knew - basics of oscillators from previous paper and how to read the graphs thanks to the last few classes
ReplyDelete1. Learned - the necessary components for a system to oscillate and the three classifications of oscillators for systems with 3 components and 3-4 links
2. Questions - are the little black arrows like the ones we drew in class for the spaces between the curves? how/why does the angle of the arrows (the angle of crossing of curve 3) play an important role? (I understand they influence whether there is oscillation or not, but still confused about them on some level.)
3. Presentation - oscillations through evolution and relation to disease (very interesting last paragraph, wish there was more on this)
4. Thoughts - I really am glad we spend so much time on the last paper because I felt like I was really able to understand and gain a lot of information from this one now; also like the real-world examples
0. Knew: General models of signal-response mechanisms
ReplyDelete1. Learned: physiological significance of different ways to employ time-delay. Prevalence of mechanisms submitting to a circadian ‘clock’. Oscillations possible only within bounds, range of non-linearity that allows oscillations. Positive feedback loops have to be held in check within a negative feedback loop. Mechanism of continually over then undershooting, characteristics of different negative feedback loops.
2. Pressing: Short time delay creates an overdamped response? For OoC’s will correlation equations have to be developed from empirical data to run simulations?
3. Presentation: A simple python simulation of an oscillating biological mechanism described in the paper
4. Thoughts: The equations/nullcline graphs were a lot more digestible after having gone through the previous Tyson paper. Interested in topic of entrainment across systems.
0. Knew: Oscillatory mechanisms as discussed previously.
ReplyDelete1. Learned: Hysteresis and negative feedback in the context of mRNA and Protein production. Interaction between positive and negative feedback loops (in the context of biochemical oscillators). Wide variation in the time-scales of biological oscillators (less than a second to days).
2. Pressing: How do time scales of molecular oscillation vary with organism size? Are they size-independent?
3.Presentation: Evolution of oscillatory circuits
4.Thoughts: Marvelously complex systems. Scaling between organs seems crucial to proper function of these systems.
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