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.
Will Matloff
ReplyDelete6/LeDuc
0. Knew: Basics of control theory. Necessity for simultaneous perturbation and measurement for controlling systems.
1. Learned: The importance of MIMO control. Differences between black, grey, and white box control.
2. Pressing?: Given unlimited capabilities, could a black box model of cells be created? Also, control theory didn't get its start until the use of the governor in the 1800s, despite biology using control theoretic techniques for much longer. Does biology exploit other techniques that are unknown to us today, that a control theoretic model could not account for?
3. Presentation: Combining synthetic biology with microfluidic techniques.
4. Thoughts: Control-based phenomena occur on many different levels in biology, from the molecular level to the organ level. Also, can cells be controlled, given their immense complexity? I remember reading about it being a feat that a group managed to control a three-armed pendulum.
Ayeeshik Kole
ReplyDelete6/LeDuc
0. Knew: I did not know much about control theory. I was familiar with MIMO.
1. Learned: I learned about the three fundamental types of feedback control and how some biological systems naturally exhibit these control principles. Also, to effectively reverse-engineer the cell, we will need multiple actuators and sensors that can work simultaneously with high spatiotemporal resolution.
2. Pressing?: Should control theory and a formal programming language be taught to all future experimental biologists?
3. Presentation: Optogenetic control of the cell
4. Thoughts: I think something that was touched on briefly in this paper, but is pivotal in systems biology is that biology is not Boolean. Therefore, the decision states of a signalling pathway will have to be defined experimentally. Additionally, the fact that a response can affect downstream and upstream components will make discerning a biological network extremely difficult.
Brian Evans
ReplyDelete6/Control-based approaches in biology
0. Knew: Fundamentals of control theory, the dynamic complexity and inherent non-linearity that are characteristic of cellular behavior, and familiar with most of the current approaches utilized in SISO systems (FRET, optical tweezers, caged molecules, fluorescent labeling, etc.)
1. Learned: The difficulties in closed-loop approaches to cellular control and how a closed-loop approach can potentially be realized.
2. Pressing?: What type of technologies will give us dynamic spatio-temporal control of intracellular signalling dynamics? Especially when it comes to intracellular MIMO control? Could we possibly engineer molecular input/output machinery with the appropriate time-scale response to achieve high-frequency modulation of signaling parameters?
3. Presentation: Closed-loop approaches to understanding pathological inter- and/or intracellular signaling dynamics
4. Thoughts: In additions to IM-MS, SILAC-MS (stable isotope labeling of amino acids in cell culture-mass spectrometry) is another novel approach to quantifying gene expression on the timescale of seconds/minutes to days.
Erica Curtis
ReplyDelete6/Control-Based Approaches in Biology
0. Knew: Basics of control theory and some of the instrumentation used. I was also familiar with the closed-loop system that is often discussed in SyBBURE.
1. Learned: I was previously unfamiliar with grey and clear box system approach definitions as well as the three fundamental types of feedback control.
2. Pressing?: In a closed-loop approach with on-line real-time measurements and a self-learning algorithm that actuates the experiment, where do you start? What variables do you begin with? Does it matter?
3. Presentation: Optogenic Cellular Control and Possible Therapeutic Applications
4. Thoughts: What would be the ideal instrumentation for analysis on an on-line system? Is there any way to combine the data collected from multiple instruments to achieve this?
Zach Eagleton
ReplyDelete6/LeDuc
0 Knew: about basic feedback and control
1 Learned: gray vs black vs clear box teminology. Three types of control. Biology is not boolean.
2 Presing ?: What is a resonable goal for MIMO/How many inputs could you resonably have and be able to measure all the data?
3 Presentation:IM-MS
4 Thoughts: Good summary of all the different kinds of inputs you can have. Was really easy to undetstand.
Lucas Hofmeister
ReplyDeleteAsgn_6/Control Theory
0. Knew: we need the ability to dynamically turn more than one knob at once
1. Learned: Biological systems probably do not exhibit biological control
2. Pressing?: Could you explain again why we need at least ten copies of something?
3. Presentation: Hyperspectral Imaging and Bandwidth in Optical Sensing
4. Thoughts: I had never considered a systems biology/control based justification for my mechanotransduction project, but reading this paper it makes it seem like it fits well.
Also, I want to re-brand stem cells as a control units rather than as a source of progenitors. Im starting to feel like they are not particularly important as progenitors especially in adults.
0 - I knew about MIMO (from Ayeeshik)
ReplyDelete1 - I learned there were three basic models of control and what they were.
2 - I wonder if there are other models of control that engineers have not typically used, but that might be used by a biological system (other than one of the three basic models)
3 - Presentation on a familiar type of MIMO control
4 - Thoughts: I keep thinking that to control the cell we need to physically access the insides of it. It would be neat to have a living cell that we could perifuse and perfuse (with our pump)!
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