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, October 16, 2019
SysBio19 Asgn_6_Due_Sunday_20-0ct-2019__LeDuc_article_in_Control_Folder_2019_10_22
Read carefully LeDuc article_in_Control_Folder Control of biology. Answer the questions: 1) What did you already know? 2) What did you learn? 3) What is your most pressing question that you would like Nicole to explain in class? 4) How does this relate to your project?
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1) What did you already know?
ReplyDeleteI knew some of the methods discussed in the paper to both model and gather data, but I didn't know all of them.
2) What did you learn?
Some of the methods discussed like the integrative control was something I had never considered or even heard of. I also didn't know the extent to which circuitry methods were being applied to biology. I also didn't know what black, grey, and clear box methods were before this paper.
3) What is your most pressing question that you would like Nicole to explain in class?
Can you go a little more into the grey box model?
4) How does this relate to your project?
It could help inform some of the weighting and probabilities for the boolean network to try and get the boolean network's behavior similar to some of the models discussed.
1) What did you already know?
ReplyDeleteI knew generally how we approach garnering data to elucidate mechanisms for the biological processes.
2) What did you learn?
I did not know all the approaches to controlling a system to understand it more, so some of the reverse engineering of systems was new to me. Thought it was cool how they tied it in to the emergent phenomenon we have talked so much in class where "characteristics of the components and their interactions with other singular components are well understood but the collective behavior is unknown"
3) What is your most pressing question that you would like Nicole to explain in class?
Further on the black,green and clear box approaches? Not sure that I understand them.
4) How does this relate to your project?
I can see how this paper can be useful to a variety of projects. They describe how to control a system to enable us to measure what we are specifically interested in. I imagine that can be valuable in many scenarios like finding a MOA for some process or describing probabilistic models to understand a system
1) What did you already know?
ReplyDeletesome of the molecular techniques to apply and measure inputs and outputs
2) What did you learn?
various approaches to characterizing a system (black box, grey box, clear box) as well as some inputs that I hadn't previously thought of (i.e. optical input)
3) What is your most pressing question that you would like Nicole to explain in class?
clarification on the three types of control (proportional, derivative, integral)
4) How does this relate to your project?
brings up the importance of identifying relevant inputs and (sometimes more difficult) outputs, for iPSC grey box approach to characterizing system probably most realistic
1) What did you already know?
ReplyDeleteThe incompleteness of the picture that black box approaches draw.
Many of the actuating methods (clamp experiment, caged molecules, engineered proteins)
2) What did you learn?
Internal gradients of stimuli are incredibly relevant (like in embryonic cells)
3) What is your most pressing question that you would like Nicole to explain in class?
Input-output techniques outlined don't mention intial condiiton very often, how can we account for this given these control theories? (e.g. stretch on neuron is not only a factor of strength of stimuli, but also instantaneous permeability of the cell membrane and genetic landscape)
4) How does this relate to your project?
Raises the concern in how much control is possible in converting a stromal to IPS cell. Although in stem state, there can be residual tendencies from the original cell type. This article outlines ways to at least know that such that its a consideration in the results on the experiment.
1) What did you already know?
ReplyDeleteI knew about some of the input actuators like chemical and genetics inputs.
2) What did you learn?
I learned about more of the control mechanisms, and about systems like BioMIMO. I also learned about system identification approaches.
3) What is your most pressing question that you would like Nicole to explain in class?
How do you go between the derivative and integral control equations? Can you define equations and use calculus of them or are these qualitative descriptions?
4) How does this relate to your project?
Control is an important part of how stromal cells go to iPSCs. It might be interesting to model one specific transcription factor and how that genetic control works.
1) What did you already know?
ReplyDeleteI was familiar with the voltage clamp experiments performed to elucidate the mechanism of the action potential. I knew that there were three basic types of feedback control (proportional, derivative, and integral). I also knew that biological systems could be perturbed (or actuated) by chemical, mechanical, and electrical stimuli.
2) What did you learn?
I learned about black-box, gray-box, and clear-box terminology. I also learned about several techniques to seize control of a cellular system/process, like Campenot chambers and RGD-coated ferromagnetic beads.
3) What is your most pressing question that you would like Nicole to explain in class?
What is the succinct explanation for why MIMO control is more desirable that SISO? Also, when researchers apply MIMO control, how do they tease apart the effects of several different inputs?
4) How does this relate to your project?
Since we are modeling a gene regulatory network with Boolean logic, control is inherent in the project. This paper could help experimentally validate the theoretical network once it is completed.
1) What did you already know?
ReplyDeletephysical, electrical, and chemical stimuli can be used to trigger biological events, and these disruptions to normal function give insight into the mechanism of action of biological events.
2) What did you learn?
I did not know about types of feedback control, nor had I heard of black, gray, and clear boxes. I thought it was interesting to see those applied to reverse engineering biological functions.
3) What is your most pressing question that you would like Nicole to explain in class?
I would like to know how we can determine beyond reasonable doubt the pathway/mechanism by which we are controlling the cell. How do we know that our stimulus is acting along the suspected mechanism?
4) How does this relate to your project?
Cellular control relates to directed differentiation closely, especially in being able to predict and direct cellular development.
1) Knew: I have read this paper before, so I'm familiar with black, gray, and clear-box approaches to measuring biological systems, as well as the fundamental types of control.
ReplyDelete2) Learned: I really appreciated the section about controlling genetic networks of interconnected molecular components, especially after our presentation about the Cre-LoxP system and how tissue-specific gene expression can be silenced or altered. It would be interesting to see these tools used to control higher-level networks of genes rather than simple knockouts or mutations.
3) Question: Is directed cell differentiation a multiple-input, single-output (MISO) application, where the single output that you care about is the identity of the cells? Or should it be MIMO in order to be closed-loop control?
4) Project: I think control goes hand-in-hand with computational modeling of a system, as you're trying to both figure out what parameters or 'levers' are needed to affect a system in a desired way, as well as most simply and effectively do so without overcomplicating.
1) What did you already know?
ReplyDeleteThe ideas of black box, grey box, and clear box models, the complexity of controlling MIMO systems, the types of control objectives, and the potential points of observability in biological systems.
2) What did you learn?
I have seen this article a few times now but it was good to reread it. The example of the chemotaxi network is interesting to think about since we are talking about Boolean networks.
3) What is your most pressing question that you would like Nicole to explain in class?
How does observability relate to controlability? How does control of a deterministic system compare to controlling a stochastic system?
4) How does this relate to your project?
I care about controlling GRNs for stem cell differentiation.
1) I knew that certain events (stimuli) can trigger changes in cells. Understanding these mechanisms can be used to determine the inner workings of a cell
ReplyDelete2) gray, black, clear boxes, BioMIMO
3) I would like to see how different modeling techniques (the ones from this paper and Boolean networks perhaps) compare and work together.
4) See if changes in disease states can be predicted using this technique