End of the Semester!

This semester sure went by fast! Here, we have a couple wrap up statements from our two project undergraduates, Patrick Mendoza and Andre Flores. We were really lucky to have such great students working (project discussed here and here) with us this spring. In their words, here is what they learned, what more they hope to learn, and what is next for them.

Patrick Mendoza

One of the big takeaways from this semester will be the fact that biology is not as far removed from computing and statistics as I normally thought.  The biological sciences are an incredibly interdisciplinary branch of science that have many different areas and sub-disciplines.  I have learned that there are many ways to merge interests in math and computer science to complement biology, and particularly, phylogeny.

This past semester has been a great experience.  Working for April Wright and Walker Pett has been especially gratifying as that both are extremely knowledgeable and took time to distill complex concepts through exercises, lectures, and applied research.

I would like to spend more time understanding the root mathematical models and their derivation along with their correlation to applied phylogenetic analysis.  Not being a computer science major hasn’t been a hindrance, but it could help to learn more fundamentals.

This summer I will be attending an internship at the Boyce Thompson Institute in Ithaca as part of their Plant Genome Project.  Solanaceous crops have been genetically modified via CRISPR/Cas9 regarding leaf polarity.  I will be using in situ hybridizations and histology to detect modified genes in plant progeny.  I am looking forward to expanding my skillsets to include microscopic laboratory experiments.

Andre Flores

Although I generally felt proficient for my age in biological knowledge as I first the lab, I quickly realized I had considerably more advanced concepts to learn. The beginning was mostly a breeze as I refreshed my knowledge in phylogenetics, but concepts began to get harder afterward. Because I was taking a Genetics course concurrently, I found it easier to understand my lab work. In particular, it was much easier to grasp the concepts of DNA evolution. Since I had a better understanding of these molecular structures and their types of mutation, I was able to apply it to the models of evolution. The simplest of these was the Jukes Cantor substitution model, which was important to learn as both a basic model of evolution but also due to its importance in understanding statistical analysis.

When I first started to apply my programming skills as an analytical tool for biology, I had almost no clue how to summarize the data I was gathering. This started to change when I started learning about substitution models, as they explained mutation rates through methods in statistical probability. It was especially helpful when we worked through concepts and problems as a group while using the whiteboards, as it was much easier to grasp with relatively simpler material (like the JC model). Later on, I found it interesting to visualize the data using Tracer or the notebooks, especially as a visual learner. The same notebooks were also a great way to apply programming skills and try out new languages. Despite learning a considerable amount, I would still say I have much more to learn in statistical analysis before being confident in my abilities with it.

By far, the most trouble I had in the lab was trying to grasp understanding of the data. Although I learned how different models worked, I still had trouble understanding what to do with the data. The first time I ran scripts on Rev, I remember being basically clueless when I saw all the terms like “marginal” or “prior” followed by random numbers. While these were quickly explained to me, it was a lot to take in at once, so I had to do a lot of extra work refreshing my knowledge in stats before I could progress. Looking back, I think it would have been helpful for us to have spent more time learning about statistical terminology and their roles in affecting a data plot. Essentially, I would have liked to learn more about the stats/computing side of the lab. This would relate to a better understanding of my understanding on how to improve upon these models, but I luckily have the opportunity to continue learning these topics through the summer.

My summer plans are to continue learning under April and Will to hopefully prepare for presenting at SACNAS in October. I hope to learn a lot more about statistical analysis and be able to apply my knowledge to more datasets with better understanding. Being able to apply my new skills to more datasets is important because it is basically the most important point of what I hope to present over – providing data to support the efficiency of using Bayesian methods to study phylogeny. I plan to start immediately after finals week and be able to continue at least into July, from where I’m hoping to spend 4 weeks in Costa Rica at a conservation facility. I would spend half my time working hands-on with endangered species, then spend the other half in the jungle helping record data as a bioinformaticist. Afterward, I’ll likely pick right back up on studying molecular evolution, whether I continue the fall semester at Iowa State or not. Regardless, I would have a summer with a lot of valuable practice in the bioinformatics field.

Overall, I had a great experience learning alongside Pat in the Heath Lab. April and Will did an excellent job teaching us new material and were helpful in making sure we understood key concepts. Early on, I refreshed knowledge on basic biological processes that led to evolution, then transitioned into the computational methods used to analyze those biological processes. Although I still have a lot to learn, under April and Will’s guidance I hope to gather valuable experience continuing summer research as I build my biological skillset.

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