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, August 26, 2018
SysBio18 Asgn_1B_Class_2_Article_01_2018_08_28
Huang-Wikswo Dimensions: Read Article 01 Huang, S,
and Wikswo, J. Dimensions of systems biology. In: Reviews of Physiology,
Biochemistry and Pharmacology. S. G. Amara, E. Bamberg, T. Gudermann,
S. C. Hebert, R. Jahn, W. J. Lederer, et al., eds. pp 81-104. 2007..
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Kylie Balotin
ReplyDeleteReading Assignment 1b: Dimensions of Systems Biology
0) What I already knew
Through my studies and previous research experiences, I feel like I've encountered the five dimensions listed in this article.
1) The most important think I learned
While I’ve feel like I’ve encountered these dimensions, I don’t think I’ve ever seen it laid out like it was in Table 1. I think this table really helped by giving me a summary of the approaches that can be used to study each dimension and what challenges come with each dimension.
2) My most pressing question from the reading
How do we balance making a model representative of a system without making it too complex to create? How do we consider the best time scale to study a system? A lot of my stem cell differentiation protocols rely on giving the right growth factor/small molecule in the right amount at the right time. These tend to be written in days, but how do we know that this time scale is correct?
3) A suggestion for a class discussion
It might be interesting to go through a research article and see how these dimensions appear in the literature and how researchers deal with the complexity of the systems they are studying.
4) Any thoughts that you might have on the class or paper
I liked how Table 1 described all the challenges for the different dimensions. I think it helps highlight some of the issues facing this field. It seems a little overwhelming trying to create a model that will help explain a system but isn’t too complex to realistically develop.
0) What I already knew
ReplyDeleteI am familiar with the kind of work that typically constitutes "systems biology" in the current research field, primarily at a molecular level - "omics" data and multivariate modeling.
1) The most important thing I learned
I haven't seen systems biology extended to dimensions 3-5 before, as described in the paper, and I learned about the higher-order challenges and shortcomings of thinking of systems only at the molecular and structural scales.
2) My most pressing question from the reading
To what extent can "reductionism" be applied while still considering the work systems biology? How does the idea of systems biology itself conflict with the most basic principle of experimentalism - controlling confounding factors and isolating variables?
3) A suggestion for a class discussion
It would be useful to talk about experimental design that encompasses the five dimensions of systems biology with examples from ongoing research.
4) Any thoughts you might have on the class or paper
I think this paper was a good high-level review of systems biology approaches that makes one think about all the variables and challenges that exist across different biological scales and dimensions.
I was also perplexed by the whole idea of reductionism, and whether this pursuit serves as a comrade to understanding the nature of the system or an antagonist to understanding the complex interactions within each level of the system.
Delete0) What I already know
ReplyDeleteOne philosophical and scientific phenomenon that I have been exposed to in the past is the notion of pattern formation, which was listed in this paper under the fourth dimension of systems biology (abstraction and emergence). In previous biology classes I learned about numerous examples of "self-organization," from biochemical and cellular situations like the cell membrane to ecological phenomena like finches occupying different niches in a large tree. While I had learned about the complexities of pattern formation in biology, I had never considered the more abstract nature of spontaneous order in time and space in relation to biological organization. The fourth dimension in this article really emphasized going beyond the biological evidence for organization in order to examine more abstract properties where you can consider the interactions of different individual components of the system.
1) The most important thing I learned
The most important thing I learned from this paper can be summed up with the quote that attempts to define systems biology: "analysis of the entirety rather than the entireness of analysis." Through this article, I gained a better understanding the nature of systems biology. Traditional disciplines like biophysics stressed the analysis of the individual level of a system, and suggested that the system was merely a superposition of the individual components. However, systems biology underscores the notion that there is more to the system than just the individual components; it is the interaction of each component across multiple dimensions and levels that creates the system. For example, when looking at genomic and phenotypic complexity, the article suggests that it is possibly futile to attempt to map a clear pathway between the genomic dimension and the phenotypic world, as the complex interactions of biology and biochemistry operate at a complexity far greater than a linear map. Thus, I learned through this article that whether I am looking at the molecular level or different spatial and temporal scales, systems biology focuses on the entirety of the system rather than specific, isolated levels.
2) My most pressing question from reading
One question I had after reading this paper was the notion of "chaotic behavior" in systems biology. I wanted to learn more about what chaotic behavior was referring to in regards to protein spatial structure. I was really interested by this section that discussed random occurrences in temporal patterns, and wanted to learn more about how abstract principles like "chaotic behavior" and fractals apply to human physiology.
3) Suggestion for Class Discussion
I think one interesting topic for a class discussion would be to apply the five different dimensions of systems biology to a macro-biological phenomenon like an ecosystem. For example, when observing the horizontal integration and interaction of various individuals, one could examine the inter-species interactions of a variety of organisms. Similarly, for dimensions like the temporal hierarchy, one could compare quick occurrences like predation, to longer occurrences like migration, to even longer occurrences such as a volcanic eruption or glacier eroding the soil. Through this topic we could look at how an ecosystem can be deconstructed using the five different dimensions of systems biology, and how like a human body, the "homeostasis" of the ecosystem (resilience to change) is an emergent phenomenon operated by numerous individual components.
4) Any thoughts on class/paper
I thought this paper did a really good job describing the different aspects of systems biology. It especially made it clear why this new field is impactful and revolutionary and tries to gain a far more theoretical understanding of the science and phenomena we observe rather than collect overly detailed data that only sees the individual level rather than the entire system. I am really excited to explore these different dimensions throughout the semester.
0) Knew: Biological systems are complex and in order to study them we need to develop tests and models that address the richness of this complexity.
ReplyDelete1) Learned: I honestly had never questioned the meaning of "systems biology", I assumed it referred to the use of computers to crunch large data or variable sets, and I feel like this interpretation is pretty universal. Even today in class Dr. Wikswo mentioned that this was a systems biology course so of course we would be doing some discussion of computation approaches (in so many words). I can definitely appreciate the expanded definition however, as it speaks to the breadth of variables, biological and otherwise, that can be at play in the systems we seek to better understand.
2) Pressing ?: What does this leave the rest of biology with?
3) Discussion: biological structures and system dynamics that repeat at different levels of scale and within other dimensions of complexity
4) Thoughts: I was glad to see the acknowledgement of fractal-like similarity among structures across scale but the notion was quickly discounted and perhaps deserves more love. The perfect fractal structure depicted in images is unachievable in the real world. The fractals that grow in the hyperspace of biological complexity are more like crystals jutting abruptly from a rough stone surface.
1. What I already knew: that the human body contains examples of emergent phenomena at multiple scales
ReplyDelete2. The most important thing I learned: temporal complexity (systems biology doesn’t only relate to the structure of a unit, but also how that structure functions over different time scales)
3. My most pressing question: there is a section that compares specific, detail-based modelling to more generic modelling- what are the practical uses of generic modelling?
4. Suggestion for a class discussion: there is clearly a limit to how far mathematical modelling can explain a system, so how do we know when we’re being too reductionist?
5. Thoughts on the paper: great overview of the different facets of systems biology, definitely raises more questions than answers
This comment has been removed by the author.
ReplyDelete0) What I already knew: Basic biology knowledge. For example, the number of genes in humans is the same order of magnitude as the number of genes in plants and worms, and that all features of organisms are not optimization by adaption but there are historical accidents such as the appendix and the tailbone.
ReplyDelete1) The most important thing I learned: It is best to study systems when they are far from equilibrium, and to understand something, we must simplify it.
2) My most pressing question from the reading: I am confused about the term anti-reductionist and the concept that knowing all the components of a system is not equivalent to understanding the system. I have always equated understanding of something, such as how a computer works, by knowing how each component of the computer works and how they work together. How do we understand a system?
3) A suggestion for class discussion: P.95 notes the difference between predicting actual behavior of a system and potential behavior. But how do we predict potential behavior of a system, how do we know what could occur? And P. 98 discusses if computers can overcome what the human brain cannot grasp. Why is the human component in designing systems necessary? Why are scientists even needed in society if a machine can overcome human flaws?
4) Thoughts
This was my first introduction to the term systems biology. I really enjoyed learning the background and the philosophical component of the term.
0.) What I Knew: I know that Systems Biology is a field that aims to take a new approach to biology. It aims to analyze and predict biology using complex mathematical and computational models. Systems Biology approaches an organism at several different levels ranging from intracellular to organ systems and larger. There is a focus on analyzing and understanding biological networks.
ReplyDelete1.) The Most Important Thing I Learned: Systems Biology is not an attempt for a universal theory of biology. But it does take a new approach that attempts to explain emergent phenomenon. But, most importantly, it brings in perspectives from other fields besides biology. Also the complexity of organs partially comes from evolutionary artifacts and dissipative systems.
2.) Most Pressing Question: How do the branches of systems biology combine into a larger picture in the coming decades? What could the future path of the field look like?
3.) Suggestion for Class Discussion: Specific examples to demonstrate the types of approaches to systems biology.
4.) I would like to know more about so-called "dissipative systems". Also more on logical (such as boolean) based approaches.
For the article:
ReplyDelete0) What I already knew
“Reductionism” is a view of “divide and conquer” widely accepted by biologists while disregarding the complexity for organisms.
The number of genes and proteins encoded is finite, but the ways they interact can be infinite.
Bioinfomatics collect and analyze all the complex DNA/protein sequences.
Knowing all the parts of the system doesn’t mean real understanding of it.
The whole is more than the parts.
1) The most important think I learned
Five “hyperspace” represents all the fundamental properties of living systems: molecular, structural, temporal, abstraction and emergence, algorithmic complexity.
The map should not be additive but multiplicative, a higher order of multiplication.
2) My most pressing question from the reading
How to explore the idea of “Multiplication” for genetics or molecular mapping? Can this philosophy also be used for physiology in complex organ systems (i.e. the interaction of different cardiovascular organs for angiogenesis).
3) A suggestion for a class discussion
Discuss how to incorporate a more holistic view of organisms rather than reductionism
4) Any thoughts that you might have on the class or paper
The paper should be more specific regarding the idea of “multiplication” and anti-reductionism. For instance, since most biological pathways being charted are still considered as additive, how exactly can we define multiplication in terms of metabolism? As for anti-reductionism, does proteome or transcriptome embodies the idea?
Blog harvested - will go over comments in class.
ReplyDeleteWhat I already knew:
ReplyDeleteI was already familiar with many of the topics in the review from more reductionist approaches to systems biology, omics heavy approaches, theoretical abstractions of the network rules, and modeling network topologies.
The most important think I learned:
The conflicting nature of some of the approaches that get in the way of progress and collaboration with some people advocating for making models as detailed as possible with more biophysical approach and others advocating for making models as minimal as possible while answering the research questions.
My most pressing question from the reading:
How do you go about synergistically using approaches from multiple dimensions to improve your work? In a way that can complement each other and add more useful information to your model to better solve your particular research question? How do you optimally choose which combination of approaches to use?
A suggestion for a class discussion:
How do you know if the problem you are working with is computationally irreducible or how would you go about proving that this is possible or not possible? By that I mean there is no finite computational power able to reduce the system in a way that can model the consequences of its interacting components?
Any thoughts that you might have on the class or paper:
While it does explain the different types of approaches to studying Systems Biology it does not seem to discuss a lot on major problems in the field overall besides the challenges associated with each dimension in the paper.
### Dimensions of systems biology - Huang & Wikswo 2006
ReplyDelete0) What I already knew
Negligible amount.
1) The most important think I learned
Seeing system biology from the 5 dimensions described in the paper.
2) My most pressing question from the reading
What exactly is irreducibility, in different contexts?
3) A suggestion for a class discussion
A thorough example of abstraction using mathematical modelling.
4) Any thoughts that you might have on the class or paper
0) KNEW
ReplyDeleteI already knew a fair amount about what the field of systems biology and what it encompassed. I knew that it was an analysis of the whole as opposed to a reductionist point of view. I knew a fair amount about how complex biology was and how tough it is to connect "different" portions of bio. I also knew about pattern formation and epigenetic landscapes
1) LEARNED
I learned about scale space and how biology is complex from the nanometer scale up to the meter scale. From this, the study of structural complexity requires taking a view of all the scales of the organism (rather than each individual level) to understand the biology properly.
2) QUESTION
My main question is where we go from here? If we describe systems biology as the "holy grail" or best way of measuring biological systems, surely it isn't fool-proof. Certainly we are missing something by using this mindset, so what are we leaving behind?
3) DISCUSSION
I think that we need a discussion on temporal complexity as well as the epigenetic landscape.
4) THOUGHTS
I liked this article in its comprehensiveness. It did a very good job of describing many aspects of systems biology, albeit from a pretty favorably biased view.