[DIYbio] Re: Any use for RNA secondary structure prediction? (slash help getting started?)

Interesting thesis topic. I still can't wrap my head around the use of a partition function vs just "pure" free energy calculations. Especially because of non-local base pairing leading to an ridonculously incalculable number of possible states but I guess the goal is to try and predict more canonical secondary structures? And probably I just haven't spent enough time reading on the topic. Previous to this though I never knew that mfold(unafold) used a partition function calculation. 

The question you ask is difficult to answer, why is RNA secondary structure prediction important? RNA secondary structure prediction is important because it provides a tool for Scientists to use, to better understand how biology works. Science can't have exact answers in some(most?) cases. Think about using SHAPE for RNA secondary structure determination it only gives someone info on what bases are "flexible" or "unpaired"(the reason these are in quotes is because those definitions can vary). The only ways to really determine a "macrostate" conformation in RNA secondary structure is through things like NMR or X-ray crystallography and even those are just a local energy minimum based on context. So programs like unafold are used widely by RNA biochemists and biologist to understand how and why RNA works the way it does. The more we understand how things work the better we can predict why things are doing what they are doing and the better we can do cool things with Science. Helping with unafold doesn't necessarily contribute anything directly to our knowledge of the universe but it helps others contribute.

As for what you should do, the field of Molecular Dynamics simulations lends itself to someone with knowledge of physics and computer science. Molecular Dynamics around protein function and dynamics is a field that is being extensively and successfully explored. If you run a windows box I would suggest looking up tutorials on NAMD and proteins, if you use linux I would suggest looking up tutorials on GROMACS and proteins. Simulations can also be run with the 3D structures of RNA but the energy functions aren't quite optimized and so I would generally stick to proteins.

If you have any questions feel free to send them my way.


Josiah Zayner




On Monday, August 10, 2015 at 2:37:16 PM UTC-7, Michael Flynn wrote:

Hi all,

I recently wrote my undergraduate thesis on RNA secondary structure prediction algorithms. In the process I've become intimately familiar with the algorithms and code bases behind Unafold and RNAstructure, which I have been told comprise 90% of the market share of RNA structure prediction software. My thesis is located here, if you are interested.  

However, I was a physics and computer science student, and I have minimal (no) training in biology. This meant that most of the time while I was writing my thesis I was in great want of background knowledge and motivation. I was often asked why my research was important, but I could never give a strong answer. When I asked my advisor for motivations behind our work, he did not answer to my satisfaction. So I thought, what better way to learn than DIYbio?

So are there ways I could help this community? What would be the best path for me to get started, in a way that my background would be the most relevant? 

Mike