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.
Sunday, January 18, 2015
SysBio15 Asgn_5B_Class_05_Article_08_2015_01_20
Systems Biology Dimensions and Challenges: Read Article 08 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.
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Kendra Oliver
ReplyDeleteAsgn_5B / Systems Biology Dimensions and Challenges
Engineering challenges of BioNEMS: the integration of microfluidics, micro- and nano-devices, models and external control for systems biology
1. Known: The size of the machines that must be used to make measurement for systems biology are very small.
2. Learned: There are many different approaches that need to be developed in bio-instrumentation and biomedical measurements for systems biology. Biomicro- electromechanical systems are used similar to laboratory-on-a-chip.
3. Pressing: What do these systems actually look like? I still do not how these systems will answer some of the temporal concerns.
4. Presentation: Apply/discuss issues discussed in this article specifically to the complexities addressed in A_7?
5. Thoughts: There are many different way that people are able to answer question in systems biology. How fast are new technologies incorporated? Where are the current limits: biological or technological?
Juan Gnecco
ReplyDeleteAsgn _5B/ BioNEMS
0: Knew: incorporation and interdiciplinary application of biology, engineering, physiology and physics to create better models to interpret systems biology (integration and functional analysis of genomics, proteomics and metabolomics). Need for autocrine and paracrine modeling to define physiolgical function from reductionist data.
1. The importance of the metabolome as a functional perspective.There isnt an exact definition for systems biology. The main problem in biomedical research = intergrating genomci/proteomic data into systems biology.
2. Pressing: We NEED actual experiments not just theoretical biology. How do you measure relaxation times (table 1 and 2)? How can we accomplish this if the (multiple sensor) technology is still not there?
3. Challenges to study systems biology - and to find the spatiotemporal techniques to measure cell dynamics.
4. Thoughts: Seahorse bioscience could provide ways to measure metabolism. Clearly the concept of RTA has existed for longer than I thought. A written lecture by Wikswo. TEER measurements in OoC.
Arman Chowdhury
ReplyDeleteAssignment 5B
0. Knew: BioMEMS serve as a complete biological laboratory-on-a-chip or artificial organs or implantable biosensors.
1. Learned: Fluorescence and microelectrode recordings are the only two cellular measurements that have adequate bandwidth to discern the time course of critical intracellular biochemical events as of now. “Ultimate models for systems biology might require a mole of differential equations (called a Leibnitz) and computations that require a yottaFLOPs (floating point operations per second) computer”.
2. Pressing ?: What does “de novo” specification of biochemical networks mean in the context of the paper (does it refer to understanding the evolution of metabolic reactions, like the Krebs cycle)? Can the micropysiometer (MMP) and multi-analyte nano physiometer (MNP) being developed by VIIBRE sense as well as actuate glucose, lactate, pH and oxygen in cells (and to what length)?
3. Presentation: The supplemental figures were really helpful to understand the material of the article, for example Fig 3 which described the size of biological systems and the micro- and nanodevices being developed to study them.
4. Thoughts: The most significant challenges to micro- and nano-scale analyses of biology seem to be low spatiotemporal resolution (bandwidth and sensitivity) and a vast number of correlations of multiple metabolic and signaling parameters. It is interesting that, on the other hand, while macroscale results might be easier to gather, they represent an ensemble average of many cells that may be in different states. I didn’t know that an individual cell had its own cyclical phase space and that it could exhibit systematic or functional “ergodic” behavior. Along with cellular phase space, I also found the ongoing research on understanding the cellular feedback loop to be really fascinating.
Selene van der Walt
ReplyDeleteAssignment 5B
0. Knew: the potential applications of microfluidics and nanotechnology to build BioMEMS such as OoC, as well as the history of proteomics in studying protein expression profiles. The concepts of reductionism and post-reductionist thought as applied to biology.
1. Learned: The varying time scales, from 10^-13 to 10^9 that exist in biological systems and the problems this poses for studying and classifying these systems. There is also huge variance in the physical size scale of different elements within living systems. There a multitude of technical challenges facing systems biology, from how to acquire data from a system, to how to handle and analyze the data acquired.
2. Pressing ?: How can we accurately model a system with levels of complexity such as a cell expressing ten to fifteen thousand proteins at any time? What is the easiest way to distinguish the purpose of a specific protein once you have identified it (ie if it’s for signaling, metabolism, maintenance etc.)?
3. Presentation: the subdiscipline of metabolomics and current research therein
4. Thoughts: the clearest definition I found for what systems biology really hopes to achieve is: “Given the scientific goal of systems biology to find the underlying biological explanations for the multitudinous observations provided by genomics, proteomics and physiology, the magnitude and the inhomogeneity (the multiscale character) of the problem preclude simple statistical methods.” However I still find the field, and particularly the technology being used to achieve these goals, rather vaguely defined.
James Pino
ReplyDeleteAssignment 5B
0:Knew:
1:Learned: Term metabolome. Types of modeling of metabolism. Basic calculation of a Leibnitz. Complexity of an organism arises from the combinations of interactions rather than number of genes.
2:Pressings: When disabling the natural cellular control mechanism do the cells compensate by other methods? How do you control the now open loops? Are their reservoirs of molecules that can be controlled? How long is the delay between measuring and adjusting signals?
3:Presentation: Current state of computational models and their complexity.
4:Thoughts: I need to learn more about nano-devices and how they are controlled and coupled.
Cameron Togrye
ReplyDeleteAsgn_5B / Engineering Challenges of BioNEMS
0.Knew: The use of DNA microarrays can be used to determine the expression profiles for thousands of genes at once.
1. Learned: Fluctuations of single ion channels in ventricular myocytes has been linked to variation in overall heart rate. I wasn't aware that such a seemingly small event could have such noticeable an impact.
2. Pressing: What can truly be learned by single cell observation? As has been previously pointed out, no cell in a multicellular organism is truly isolated, and thus wouldn't we be making incorrect inferences based off a unrepresentative subject?
3. Examples of ergodicity (and non-ergodicity) in biology or otherwise
4. How closely does RTA parallel the design and objectives of the single cell controller mentioned in the paper?
Tim Lee
ReplyDeleteAsgn_5B
0. Knew: General idea of the scale required to interpret systems biology.
1. Learned: Details about the scale and resolution needed. Algorithms and computational models known to evaluate the data.
2. Pressing: Doesn't it seem like our understanding of systems biology in its most complex levels will ultimately be limited by how we're able to interpret the large volume of data?
3. Presentation: The large variation of scales in interpreting systems biology and the challenges of measuring to those scales
4. Thoughts: It's depressing to think how there will be another immense obstacle to interpret the immense amount of data that will be produced from finally finding a way to obtain high spatiotemporal resolution. Maybe it won't be as tough of an obstacle as I predict
Cami Johnson
ReplyDeleteAssignment 5B: Article 8
0. Knew: Biology seems to have reached its limit in what can be gained from the reductionist approach, and the study of systems biology aims to begin understanding how all the parts integrate to create the function of the whole.
1. Learned: How important processes at the cellular level can be to the function of the organ or organism. I didn't realize that an error at just one cell could drastically affect the overall function.
2. Pressing ?: How often do cellular activities differ substantially? Essentially, are cell populations often not ergodic? With microdevices, there are many advantages, but is the small volume a disadvantage when it comes to taking measurements?
3. Presentation: Different instruments which are being developed to suit this type of recording
4. Thoughts: It seems one of the largest obstacles to microdevices is having the appropriate actuators and measurement instruments for this scale. Every time I read about this, it seems more and more complex, but maybe the key is to create just enough complexity so that useful information can be obtained, without it being so complicated that it doesn't make sense.
Kate Jones
ReplyDeleteAssignment 5B Article 08
0. Knew: Systems biology is an interdisciplinary science with contributions from physiologists, physicists, biomedical engineers, chemical engineers, chemists, mathematicians, and more. I also knew that devices including laboratory-on-a-chip could revolutionize drug discovery and environmental monitoring.
1. Learned: I did not know that inadequate bandwidth was a major concern in mapping the time of cellular events and that only two technologies have adequate bandwidth. Table 3 helped me condense the information about the benefits of micro devices and see why they are necessary and important.
2. Pressing ?: The article uses a lot of futuristic language, such as "it will soon be possible" and discussion about the future of these devices. As of now, where in the steps listed for the analysis of cellular signalling dynamics and control are current technologies?
3. Presentation: Breaking down Figure 3 and discussing the technologies that fall under each category could help develop an appreciation for the scope of systems biology beyond the class.
4. Thoughts: Until reading section 2.4, I was wondering why we needed to be looking at each cellular event as opposed to the entire system, but the example of heart rate fluctuations in response to a single ion channel helped me realize how important the small scale events could be to the system.
Mark Vander Roest
ReplyDeleteAssignment 5B
0. Knew: What BioMEMS stands for, some of the high throughput techniques mentioned, scale of biological complexity.
1. Learned: Problems with integrating all the data that we can acquire, especially relating to control. ie. we can collect a ton of info, but the next logical step is exerting some type of control, which is really really difficult.
2. Pressing ?: What levels of control will be possible/realistic for BioMEMS to achieve? Will real time genome editing be possible or even useful?
3. Presentation: Scales of biology, measurement challenges and ways to make use of the data acquired from the many measurements we can make.
4. Thoughts: It seems like a lot of the idea of measurement and control could be used and applied to reductionist biology. Is there a good way to apply it all to a specifically systems bio approach?
Shuaipeng "Jimmy" Zhang
ReplyDeleteAssignment 5B
0. Knew: BioMEMS devices, and the use of them to study interactions in biology.
1. Learned: The different micro- and nano-instruments that can be used to study the actions and mechanisms on a cellular level. The immense variance in both the time and size scales in biology.
2. Pressing ?: How accurately can we measure the changes in concentration and time once the micro/nano devices are built? Making sure that the measurements taken from the device are accurate is a huge obstacle, perhaps as big as building the device itself.
3. Presentation: Complexity of systems biology, current models used, and the development of nano and micro scale technologies to aid in research.
4. Thoughts: The article continues to reinforce the complexity and challenges faced in systems biology. It seems that the more we try to solve a challenge, the more challenges we find.
Blog harvested
ReplyDeleteChuck Herring
ReplyDeleteAsgn_5B
0. Knew: General idea of systems biology.
1. Learned: Some of the more specific technologies and computational approaches listed were to new to me.
2. Pressing: How has the outlook or technology of systems biology changed since this paper was published?
3. Presentation: Engineering challenges associated with systems biology.
4. Thoughts: What will systems biology look like in decade?