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.
Thursday, January 19, 2012
Asgn_5_Class_5_Article_8_2012_01_20
Read Article 8: J. P. Wikswo, A. Prokop, F. Baudenbacher, D. Cliffel, B. Csukas, and Momchil. Velkovsky. Engineering challenges of BioNEMS: the integration of microfluidics, and micro- and nanodevices, models, and external control for systems biology. IEE Proc.-Nanobiotechnol. 153 (4):81-101, 2006. Post a PCRC on the Blog.
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Will Matloff
ReplyDelete5/Wikswo BioNEMS
0. Knew: Concept of multi-scale biology and the challenges with modeling.
1. Learned: In order to model a cell, small scale measurements need to be made. Nano-electromechanical systems (NEMS) instrumentation shows promise in making these measurements. When a biological system is simultaneously perturbed and measured, algorithms can be used to infer information about the system.
2. Pressing?: How high up the levels of biology can you go before you lose important information? Is there a ideal level of abstraction for biological models? Also, when perturbing a cell, how much of a difficulty are semi-permanent changes?
3. Presentation: Machine learning.
4. Thoughts: Moving biological experiments to a very small scale has many advantages. How much does cell heterogeneity play a role at these scales?
Brian Evans
ReplyDelete5/Engineering Challenges of BioNEMS
0. Knew: That the majority of current techniques to assess cellular behavior/metabolism are averaged over a large number of cells over a time period that is usually much longer than the time constants within the system. This disadvantage is becoming apparent as new measurement techniques are elucidating the spatiotemporal resolution of cellular processes.
1. Learned: To think of measuring a single cell's 'ergodicity': Typical measurements are just a single measurement taken at a discrete time point, but looking at the phase space of cellular dynamics allows for insight into the regulation/perturbation of cellular pathways and allows for pattern recognition and identification of cross-talk between signalling pathways.
I also learned that I am quite ignorant of advanced computer modeling and algorithm formulation.
2. Pressing?: What are the most promising developments for single cell manipulation and measurement? How do we non-invasively monitor intracellular dynamics without perturbing the cell?
3. Presentation: Microfluidic modulation of single cells
4. Thoughts: Why can't we develop real-time monitoring NEMS that are then used to monitor cells within an in-vivo environment (i.e. implant the biosensor, send the patient on their way and record the data over time). Would this not be more physiologically relevant than in silico and in vitro methods, and, therefore, wouldn't the research focus need to be on the development of appropriate biosensors before development of the holy grail of an organ on a chip? Why make the organ on a chip if we can't even non-invasively measure whats going on inside it with the adequate spatiotemporal resolution?
Ayeeshik Kole
ReplyDelete5/Wikswo BioNEMS
0. Knew: Systems biology needs new tools with improved bandwidth and time-resolution in order to understand complex biological systems. Single-cell studies are necessary to avoid the dilution of complexity that results from ensemble averaging of large cell populations
1. Learned: Biology is the last of the sciences to encounter the post-reductionist challenge of making sense of data at the smallest fundamental scale in the context of higher scales of integration.
2. Pressing?: Will the lack of technology to record multiple parameters simultaneously be the bottleneck to automated single-cell control? Are there commercial instruments being built to overcome this challenge or they all currently in-house initiatives?
3. Presentation: GEDI for exploration of cellular phase space
4. Thoughts: I thought the introduction to the article was very useful for me, especially the walk-through of the calculation of the 105 parameter number.
Erica Curtis
ReplyDeleteAsgn5/Engineering Challenges of BioNEMs
0. Knew – From SyBBURE, I am familiar with the definitions of systems biology and have a basic understanding of the levels of complexity in these measurements and the trade-offs with various experimental designs/platforms.
1. Learned – I was familiar with all the general concepts but really gained a lot of knowledge in the nuances across the board.
2. Pressing ? What are some of the best ways of avoiding ergodicity? Cell cycle synchronization seems to be a very difficult task and microfluidic devices still contain a large number of cells (less than in-flask experiment for sure). Are there any situations where ergodicity is desired?
3. Presentation: Pros and Cons of Various Nano- and Micro- Instrumentation.
4. Thoughts – Even being able to recreate a disease state on chip may be as complicated and require as many variables and interpreting the read-out.
Lucas Hofmeister
ReplyDelete5/ nanoBiomems
0. Knew: The wide range of time and spatial scales is a big problem for instrumentation/measurement
1.Learned:signaling noise can drive cellular decisions. what is an example of this?
2. Pressing?: what about using one cell type to sense another. instead of developing our own sensing mechanisms, maybe one cell has an easier to look at response to a hard to look at dynamic in another cell. or build a cell that you can stick into the center of a bunch of cells which is designed to sense a few of the phenomenon and has an easy readout
3: Presentation: Synthetic biology
4. Thoughts: Could we approach this by simplifying the system that we are studying and gradually increasing the complexity, i.e. building a cell from the ground up? synthetic assemblies of these components one piece at a time and measuring the resulting dynamics at each step. Maybe start with a membrane and add a nucleus, then start adding the machinery necessary to build all the components, then watch it all happen.
Zach Eagleton
ReplyDelete5A/Engineering Challenges of BioNEMS
0 knew: Fundamental challenge in systems biology
1 learned: In more detail what BioNEMS is and that many oscillatory functions may not yet be understood.
2 Pressing ?: Mentioned something about using living cells as analog computers in the article.
3 Presentation: isolated membrane patch clamp
4 Thoughts: Learned a lot from this article
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