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programming, genomics, bioinformatics, data analysis, modeling & simulation

Please note: This stream will be ending at the end of 2023.


Key Points:

  • Determine and understand the relationship between sequence and structure of nucleic acids and proteins.

  • Explore the interactions between proteins and nucleic acids and the consequences of said interactions.

  • Utilize experimental data in online databases to construct, optimize, and analyze structure.

Detailed Description:

DNA is an essential molecule in the cells of living organisms and relies on both its encoded base sequence and overall structure for a multitude of uses ranging from organization to expression. Our research focuses on creating 3-D computational models of DNA from data stored in online databases like the Protein Data Bank.

We will create DNA models inspired by research conducted in national labs exploring interactions used in metabolism and architecture or exploring the presence of circular DNA found in cancer cells. 


Key Points:

  • The binding of proteins to specific DNA sequences controls interactions at sites up and downstream from the interaction site.

  • Developing and analyzing new models can improve understanding of the molecular organization and binding activity for enzymes and drugs.

Detailed Description:

DNA interacts with numerous molecules that range in size and complexity, from small ligands to large proteins. These interactions not only affect local DNA regions, but they also are consequential in how DNA can be used in other positions.


Our research uses computational and modeling methods to explore various DNA configurations and how they are influenced by the DNA properties like sequence composition and external factors like binding.

DNA interactions, shapes, and binding are central to human health and have been implicated in numerous diseases.


Key Points:

  • Bridging the gap between experiment to computational modeling and design.

  • Scientific computing basics with command line and C++.

  • Programming and analysis in Python and R.

Detailed Description:

Regardless of projects that range from comparing protein structures found in the Protein Data Bank, analyzing models differing by DNA sequence, or even creating your own DNA models, this work teaches you how to work in a computational environment.


Here, you will become more familiar with programming languages like Python and C++, learn how to execute code, utilize supercomputers, analyze data, and generate figures.


You will learn how to work on the edge where biology and chemistry meet physics and mathematics all using computational skills that can be used for any application. 

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