BIOL398-04/S15:Class Journal Week 14

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Contents

Lucia I. Ramirez

Interpretations

  • Look at the uploads of at least one other group in the class. State which group you compared yours to. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)? If so, do the weights compare? Are there any weights that indicate activation in one network and repression in another? If so, what do you make of it?
    • It seems that no one was able to attain weighted networks.

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following:

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • This is very valuable because we are now able to see visually what genes are affecting and controlling other genes. Being able to see the mathematical representation of what we know or are still trying to understand biological concepts has been extremely interesting!
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • My answers haven't really changed.

Lucia I. Ramirez 02:59, 28 April 2015 (EDT)

Lauren M. Magee

Interpretations

  • Look at the uploads of at least one other group in the class. State which group you compared yours to. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)? If so, do the weights compare? Are there any weights that indicate activation in one network and repression in another? If so, what do you make of it?

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following:

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • Biology and mathematics have different strengths and area of focus. Biology offers an understanding of life's complex systems, but mathematics is able to do what we would never have the years to complete. Mathematics can model real or hypothetical systems from which we can gain a more holistic view of life. When combining these two disciplines, we are highlighting each fields talents to assist the other, which creates a more complete picture and promotes the ideal that all disciplines are connected and can assist one another to create a more effective product.
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • My answers have no change from that initial reflection, because as a Biomathematics major, I hold interdisciplinary approaches in very high regard. I would identify myself as both a biologist and a mathematician, but I believe that to be easier for me since I have had the opportunity to gain experience in both fields. I don't think there needs to be a specific skill set to label oneself either a biologist or a mathematician, I think it is more of a frame of mind and inquisitive nature to learn more about earths systems and the human experience. After completing the modelling, I can see clearly the intersectionality that is necessary between mathematics and biology in a very different way than I am accustomed to. I focus more on statistics as it relates to biology, so it is interesting to see more computer science and theoretical mathematics become so influential.

Lauren M. Magee 00:54, 28 April 2015 (EDT)

Alyssa Gomes

Interpretations

  • Look at the uploads of at least one other group in the class. State which group you compared yours to. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)? If so, do the weights compare? Are there any weights that indicate activation in one network and repression in another? If so, what do you make of it?

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following:

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • Biology helps explains the why and math explains how. I have always thought that but especially through procedures in this class have they become more interlinked by modeling and Matlab scripts. It is very different from the math I was expecting to do, but by combining both you can combine the how and why very easily in order to gain a deeper understanding of the what. Using this we will continue to learn and adapt more and more to scientific and mathematical advances.
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • In one of my answers from the week 1 journal I noted that math is to see patterns. Through some of the research done in this class, my complex journal club 2 assignment and more, I've learned not all math will show patterns and a conclusive answer. Sometimes, rather, it helps reveal hidden discrepancies that would otherwise not be noted. I still believe in the way math and biology come together in different ways, but now I've seen much more of the complexities that come along with it, especially with trial and error methods. Sometimes it is easy to see something that may be off and just call it a weird conclusion, when in reality it is a math error or scientific method error. I've learned that because the combination of biology and math brings in a new level of foundation, we must understand each piece very carefully in order to really understand the whole assignment, experiment, or whatever it may be.

Alyssa N Gomes 23:28, 29 April 2015 (EDT)

Natalie Williams

Interpretations

I looked at Lauren and Lucia's results from MATLAB. Their specific deletion was HMO1.
In comparing our networks, we have ten of the same genes.

  • HMO1
    • It represses itself in my GRN while it activates itself in L^2
    • It seems to up regulate CIN5 in both models
    • It seems to repress MSN4 in my GRN while it activates MSN4 in L^2
  • YOX1
    • HMO1 up regulates it in both; however, it more significant in my GRN
    • MSN2 upregulates it in L^2's network while it is repressed in mine
  • YHP1
    • It only receive inputs from other genes in L^2's network while it regulates other genes in my GRN
  • YLR278C
    • All of its inputs are down-regulating the gene while it has one up regulation in my GRN
  • MSN4
    • Only contains inputs in my GRN with both activation and repression cues, while in L^2's GRN it down-regulates ROX1
  • MSN2
    • In both networks, it has a key role in regulating many other genes
  • GLN3
    • It regulates one gene in my GRN while it only receives input in L^2's GRN
    • In my GRN it is only up-regulated while in L^2's it has both up and down regulation
  • SFP1
    • It only receives inputs in both GRNs constructed
    • In L^2's GRN, it is up-regulated with great weight whereas in my GRN, the up-regulating weight is negligible
  • CYC8
    • In my GRN, it regulates two other genes with negligible weight
    • It only receives input from other proteins in the network for L^2's
  • CIN5
    • In my network, it seems to significantly down regulate MIG2 and slightly up-regulate other genes
    • In L^2's GRN, it has a stronger up-regulation presence, but it also down regulates SFP1

Natalie Williams 21:17, 4 May 2015 (EDT)

Reflection

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • In combining mathematics and biology, we are finding ways to define and understand functions and processes that various systems undergo. In applying a mathematical equation to a process, we hopefully describe laws that are universal under many conditions. With universality of equations, we can apply these equations to other processes to better understand what occurs in nature.
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • In gathering the data and determining significance, I am still amazed by all the work that must be done to get to just having the adjacency matrix for the input sheet. The one matrix for our selected GRN is not the only possibility from the data. Multiple versions can be run with varying outputs. These results elicit multiple interpretations and more than one can be correct. Even with the help of mathematics, which is concrete, interpretation of data varies and does not give conclusive results every time.

Kristen M. Horstmann

Interpretations

Look at the uploads of at least one other group in the class. State which group you compared yours to. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)? If so, do the weights compare? Are there any weights that indicate activation in one network and repression in another? If so, what do you make of it?

  • I looked at Tessa's and Alyssa's powerpoint of figures and we actually had many genes in common. Both of our networks included: ACE2, ASG1, CIN5, CYC8, FKH2, GLN3, HMO1, MIG2, MSN2, PDR1, RIF1, SFP1, SNF6, STB5, SWI5, YHP1, YLR278C, YOX1, and ZAP1. Actually, it seems the only gene that Kara's and my network had that Tessa's and Alyssa's did not was GAT3.
  • CIN5->ASG1: in ours, positive weight (activation), in theirs, negative (repression)
  • CIN5->MIG2: both extremely high weights, but their estimated-b was highly positive and ours was very negative
  • YHP1->GLN3: both positive, but in ours, the estimated was higher than theirs.
  • MSN2->CYC8: ours was slightly positive, while both of theirs was extremely negative
  • It makes sense, their network is different than ours, so there's no reason to expect that theirs should be similar or identical to ours. However, some of the weights were the same, which might make sense because since the majority of our genes were so similar, the chances of some of them not being affected by our respective deleted strains means that they behave the same regardless. This especially makes sense since ZAP1 was only connected to ACE2, Kara's and my network should be fairly similar to the genes that their deleted gene was unaffected by.

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following:

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • Biology and math are much more similar than many people would think. The value of combining these two is that it helps us further understand both topics- math helps strip the biology side to step-by-step equations and not a microscopic mystery, while biology helps find and explain how some of these more intense math equations fit with the natural world. I think the biggest value math brings to scientific questions is that by being forced to break it down into small steps help make the science less of a mystery and makes it easier to comprehend what's happening on a smaller level.
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • I'm not sure if my answers have really changed. I guess I would consider myself a biologist/mathematician more so than before, but I would still never use those titles to describe myself as such. I still feel like those titles are far too prestigious to describe me, someone who knows very little relative to the massiveness of both fields. I think my response about "hiding math" with the Stewart reading is somewhat funny after this semester, as none of us could hide from all the math that we did this semester, yet the clearest outputs we produced were in GRNsight, a great program who does exactly that- hide math. It's just interesting because for us, doing all the math was what helped us understand, only to input it to create a picture to make it easier for everyone else to understand. I'm starting to think that's a big aspect of biomath and bioinformatics- making sure to streamline our work to the point that we can hide all the math we did in order to explain it to others.

Kristen M. Horstmann 03:35, 3 May 2015 (EDT)


Tessa A. Morris

Interpretations

Look at the uploads of at least one other group in the class.

  1. State which group you compared yours to.
  2. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)?
    • CIN5
    • CYC8
    • GLN3
    • HMO1
    • MSN2
    • MSN4
    • SFP1
    • YHP1
    • YLR278C
    • YOX1
    • They did not have ZAP1 in their system
  3. If so, do the weights compare?
    • When looking at the weights the only one that had the same controller --> target was HMO1--> HMO1
    • Our weights were approximately double theirs
      • Our weights fixed b: 0.628535081and estimate b: 0.589007964
      • Their weights fixed b: 0.275399893 and estimate b: 0.276865958
  4. Are there any weights that indicate activation in one network and repression in another?
      • There was only one comparable weight and that did not indicate activation in one network and repression in the other, which would likely be indicated by the weights being negative in one network and positive in another.
  5. If so, what do you make of it?
    • These networks did not really overlap and did not provide much insight.

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following:

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • The biological and mathematical approaches to scientific questions are two very different ways of thinking, which is why it is important to combine them. Apply mathematical concepts to biological processes provides a more quantitative way of analyzing biological data. Often it is easier to see and understand results when using mathematical methods to interpret the data (i.e. graphs).
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • My answers have changed in that now I feel more comfortable identifying as a mathematician or a biologist, but I still think that neither or those terms truly apply to me. I like the general term "scientist" because, like this class, my interests are interdisciplinary, drawing from mathematics, biology, and chemistry. I think that the way that the STEM fields are going to advance is by moving away from just focusing on one field, or at least there will be more of a demand for people who can think like both a mathematician and a biologist (as well as other STEM fields of study).

Tessa A. Morris 17:26, 4 May 2015 (EDT)

User: Kara M Dismuke

Interpretations

Look at the uploads of at least one other group in the class. State which group you compared yours to. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)? If so, do the weights compare? Are there any weights that indicate activation in one network and repression in another? If so, what do you make of it?

  • I decided to compare our uploads to those of Alyssa and Tessa.
  • I noticed we had a overlap of 19 genes:

SWI5, ACE2, PDR1, HMO1, MIG2, YHP1, ASG1, SFP1, CYC8, YLR278C, RIF1, ZAP1, FKH2, GLN3, CIN5, MSN2, STB5, SNF6, YOX1.

  • Weight Comparison
    • CIN5→ ASG1:
      • our fixed b weight: approx. .0707
      • their fixed b weight: approx. -.2956
      • our estimated b weight: approx. .0704
      • their estimated b weight: approx.. -.2849
    • CIN5→ CYC8:
      • our fixed b weight: approx. -.2744
      • their fixed b weight: approx. .2810
      • our estimated b weight: approx. -.2665
      • their estimated b weight: approx.. .2824
    • CIN5→ MIG2:
      • our fixed b weight: approx. 1.777
      • their fixed b weight: approx. 1.283
      • our estimated b weight: approx. -3.920
      • their estimated b weight: approx. 1.617
    • CIN5→ PDR1:
      • our fixed b weight: approx. .7795
      • their fixed b weight: approx. .4802
      • our estimated b weight: approx. .8833
      • their estimated b weight: approx. .4546
    • FKH→ ASG1:
      • our fixed b weight: approx. .05961
      • their fixed b weight: approx. .1193
      • our estimated b weight: approx. .07646
      • their estimated b weight: approx. .1306
    • FKH2→ SFP1:
      • our fixed b weight: approx. .02012
      • their fixed b weight: approx. .2173
      • our estimated b weight: approx. .2589
      • their estimated b weight: approx. .2853
    • FKH2→ SNF6:
      • our fixed b weight: approx. .1886
      • their fixed b weight: approx. .3140
      • their estimated b weight: approx. .3512
    • FKH2→ SWI5:
      • our fixed b weight: approx. -.7660
      • their fixed b weight: approx. -.9305
      • our estimated b weight: approx. -.7674
      • their estimated b weight: approx. -.9618
    • FKH2→ YHP1:
      • our fixed b weight: approx. -1.3071
      • their fixed b weight: approx. -.7845
      • our estimated b weight: approx. -.9215
      • their estimated b weight: approx. -.8250
  • I realized that it would be easier to just put both groups' weight values for the same gene relationships in an Excel table.
  • Weights that Indicate Activation in One Network and Repression in Another
    • CIN5-->ASG1
      • ours: activation
      • theirs: repression
    • CIN5-->CYC8
      • ours: repression
      • theirs: activation
    • HMO1-->HMO1 (only estimated-b weights)
      • ours: repression
      • theirs: activation
    • HMO1-->MSN2 (only estimated-b weights)
      • ours: repression
      • theirs: activation
    • MIG2-->RIF1 (only estimated-b weights)
      • ours: activation
      • theirs: repression
    • MSN2-->CIN5 (only estimated-b weights)
      • ours: repression
      • theirs: activation
    • MSN2-->CYC8
      • ours: activation
      • theirs: repression
    • MSN-->YHP1 (only estimated-b weights)
      • ours: repression
      • theirs: activation
  • Other Notes Regarding Weight Comparison
    • CIN5-->PDR1
      • ours weight values were just about double theirs
    • FKH1-->ASG1
      • ours weight values were about 1/2 theirs, but all values were close to 0 (relatively speaking)
    • HMO1-->CIN5
      • our weight values were just about double theirs
    • HMO1-->CYC8
      • ours weight values were about 1/2 theirs, but all values were close to 0 (relatively speaking)
    • HMO1-->MSN2
      • our weight values were very close to 0, whereas theirs were much closer to 1
    • MSN2-->SFP1
      • our weigh values were about triple theirs
    • ZAP1-->ACE2
      • our weight values were about double theirs
  • Explanation/Analysis
    • It is no surprise to see different weight values when comparing our network to theirs, because even though they involve many of the same genes, they are, in fact, two different networks. Doing the above comparison, I observed that many relationships between genes existed in both networks and had very similar weight values. For the genes who had different activation/ repression roles in the two networks, we may be able to attribute this to the difference in the effects of deleting a particular gene in each network (we deleted dZAP1 and they deleted dGLN3). This possible explanation may also account for the cases in which weight values were doubled tripled, etc. between the two networks. Then again, these are all relative because they are on a scale and so doubling values close to 0, still results in values close to 0.

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following: What is the value of combining biological and mathematical approaches to scientific questions?

  • In my opinion, combining biological and mathematical approaches to scientific questions has great value. I believe this because real-life does not exist in a vacuum whereby biology is isolated from math is isolated from psychology is isolated from political science (so on and so forth). Thus, I believe interdisciplinary approaches promise more hope when dealing with application-based matters (as opposed to theory-based matters). I also believe that combining two (or more) approaches can result in a deeper/nuanced understanding of each of the approaches individually.

Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?

  • Upon looking back on my responses to the Janovy and Stewart readings from the Week 1 Class Journal, I cannot say any of my opinions have changed much. I still hold to my idea of what a biologist is and what a mathematician is, and thus, maintain that I am neither, but I think that after this class, I am more on my way toward becoming both. One thing that I think I didn't consider, though, in my definitions is the role of research in both mathematics and biology as a means of applying things that are known to hopefully discover new things.

--Kara M Dismuke 00:08, 5 May 2015 (EDT)

Jeffrey Crosson

Look at the uploads of at least one other group in the class.

State which group you compared yours to.

  • Kara and Kristen

Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)?

  • RIF1
  • YOX1
  • GLN3
  • HMO1
  • ZAP1
  • MSN2
  • STB5
  • MIG2
  • SWI5
  • SNF6
  • CIN5
  • CYC8
  • YLR278C
  • ACE2
  • SFP1
  • FKH2
  • YHP1

If so, do the weights compare?

  • No, they are all pretty different.

Are there any weights that indicate activation in one network and repression in another?

  • Yes.

If so, what do you make of it?

  • That I'm looking at two entirely different networks.


Reflect back on your learning for this project and for the entire semester and answer the following

What is the value of combining biological and mathematical approaches to scientific questions? They each provide useful and different insight. in the case of this class, mathematics was used to quantify the dynamics of biological events.

Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share?

  • Not really, but I've realized that there's even more information in biology than I formerly imagined.

Have your answers changed to those original reflection questions?

  • No.

Why or why not?

  • I've gained some knowledge since then, but it I still don't think I'm a mathematician or biologist.

Jeffrey Crosson 05:03, 5 May 2015 (EDT)

William A. C. Gendron

Interpretations

  • Look at the uploads of at least one other group in the class. State which group you compared yours to. Is there any overlap between your group and theirs with regard to which genes are in the networks (there should be at least for CIN5, GLN3, HMO1, and ZAP1)? If so, do the weights compare? Are there any weights that indicate activation in one network and repression in another? If so, what do you make of it?
    • I compared my data set to Jeffery's, because we used slightly different data sets due to a miscommunication over which slides we should select. We did have many in common though:
      • ACE2
      • ASG1
      • CIN5
      • CYC8
      • FKH2
      • GCR2
      • GLN3
      • HMO1
      • MIG2
      • MSN2
      • MSN4
      • RIF1
      • SFP1
      • SNF2
      • SNF6
      • STB5
      • SWI5
      • YHP1
      • YLR278C
      • YOX1
      • ZAP1
    • The weights that were shared were all very close and nothing visibly stood out when they were graphed. The weights did not prescribe opposite effects among the transcription factors, but that being said, they did differ with only the difference of 6 transcription factors in total. With larger differences, I find it easy to see that larger changes may occur.

Reflection

Reflect back on your learning for this project and for the entire semester and answer the following:

  1. What is the value of combining biological and mathematical approaches to scientific questions?
    • Being able to quantify interactions is a means to get a complete understanding of a system. Without mathematics, the interactions are merely qualitative not quantitative. Without biology, there isn't a physical system to analyze.
  2. Looking back on your reflections on the Janovy and Steward readings from the Week 1 Class Journal, do you have any further insights to share? Have your answers changed to those original reflection questions? Why or why not?
    • Through this course, I have found that I am much more a biologist than a mathematician. I still am a bit of both, but I am only a mathematician insofar as it adds to the quality of my biological research.
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