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.
Wednesday, February 1, 2012
Asgn_8_Class_11_Article_10_2012_02_06
Article 10: J. J. Tyson, K. C. Chen, and B. Novak. Sniffers, buzzers, toggles and blinkers: dynamics of regulatory and signaling pathways in the cell. Curr.Opin.Cell Biol. 15 (2):221-231, 2003.. We will discuss this article in depth, which will take at least a full class. This should be a first reading to get an overview. Post a PCRC. We will have a second, more careful reading in a second class with a second PCRC.
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Will Matloff
ReplyDelete8/Tyson
0. Knew: Linear signal-response curves and the basics of Michaelis-Menten kinetics.
1. Learned: Genetics networks of even a small number of components can create very useful non-linear dynamics that are essential for the functioning of cells.
2. Pressing: Is this list of modules exhaustive? Is much known about the evolution of these modules?
3. Presentation: Complex networks and nonlinear dynamics.
4. Thoughts: The model of the cell cycle control system using these signal-response elements is really neat.
Brian Evans
ReplyDelete8/Sniffers, buzzers, toggles & blinkers
0. Knew: Linear signal-response curves and the basics of Michaelis-Menten kinetics.
1. Learned: The nuances between different types of biochemical oscillators (i.e. negative-feedback, activator inhibitor and substrate depletion oscillators)
2. Pressing: How would one go about modeling a chaotic deterministic process? (like cell differentiation?)
3. Presentation: Chaos Theory in biology
4. Thoughts: This paper did a great job deconstructing complex processes into simple models. It was also interesting to see mathematical representations of processes that involve memory (i.e. the response is influenced by its state earlier in time as in perfect adaptation)
Ayeeshik Kole
ReplyDelete8/Sniffers, buzzers, toggles & blinkers
0. Knew: Biological cell signaling pathways can be modeled in mathematical terms and can be thought of with the same principles used to build electronic circuits.
1. Learned: Sigmoidal switches represent "buzzers," transient responses can be thought of ass "sniffers," hysteric switches as "toggles," and oscillators as "blinkers." Complicated behaviors can be deconstructed modules of these signal-response curves.
2. Pressing: What are the consequences of a chemotactant systems lacking perfect adaptation? Have people studied the removal of 'species X'?
3. Presentation: Logistic map model
4. Thoughts: I thought this paper did a good job in the text of explaining how biological processes can be reduced to a few types of simple mathematical models. I didn't get the same comprehension from the figures though.
Erica Curtis
ReplyDelete8/Sniffers, Buzzers, Toggles & Blinkers
0. Knew: Cell signaling can be modeled mathematically with a set of known signal-response curves. These cell signaling pathways can be depicted as electrical circuit using analogous electrical components.
1. Learned: I learned which basic signaling pathway patterns are associated with which basic mathematical models and why.
2. Pressing: What is the difference between a super- and sub-critical bifurcation.
3. Presentation: Modeling Complex Signaling Pathways with both Sigmoidal and Oscillatory Behavior
4. Thoughts: How was the scale on the graphs determined? I had some trouble understanding the figures and am looking forward to reading the paper again and hopefully catching on to some of the things I may have missed.
Zach Eagleton
ReplyDelete8/Sniffers, Buzzers,Toggles, & Blinkers
0 Knew: Cell signal pathways could be modeled mathematically
1 Learned: The basic types of signal pathway mathematical models. Examples of biological processes that exhibit these models.
2 Pressing ?: had trouble understanding the Hopf bifurcation principle.
3 Presentation: Spatial Signaling Pathways
4 Thoughts: I found the paper very interesting but also had trouble interpreting some of the graphs, especially in figure 2.
Lucas Hofmeister
ReplyDeleteasgn 8/ Sniffers
0. Knew: some basics of MM and feedback
1. Learned: Steady state spatial oscillations can be described by many of the same means as time-dependent oscillations. and are common in nature ("Touring Patterns")
2. Pressing?:Im a little hazy on how this relates to non-ss cases.
3. Presentation: THe blinker from Elozitz and Leibler
4. Thoughts: This paper suggest that we need more exact engineering-style representations of the wiring diagrams of biological phenomenon. What if our engineering approach is wrong?....i.e. we need a new calculus for this stuff
Follow up:
ReplyDeletehttp://wikipathways.org/index.php/WikiPathways
Also, in the case of hysteresis and the bistable systems:
mutual inhibition - how big are these discontinuities? can we measure them?
All of these plots are normalized, but the changes associated with these phenomenon are still around 10-20% of the total signal, is that realistic?
how about systems which might have switches which are at much lower levels so that they appear to follow a different regulatory mechanism?
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