Improving Adjacency List Storage Methods for Polypeptide Similarity Analysis

Author

Arianna SwensenFollow

Date of Award

Fall 12-2-2022

Document Type

Undergraduate Thesis

Department

Computer and Information Science

First Advisor

Yixin Chen

Second Advisor

Charlie Walter

Third Advisor

Sushil Mishra

Relational Format

Dissertation/Thesis

Abstract

Protein design is a complex biomolecular and computational problem. Working on increasingly large protein folding problems requires an improvement in current analysis methods available. This work first discusses various methods of protein design, including de novo protein design, which is the primary focus of this thesis. Then, a new approach utilizing a B+ tree to effectively store and query a graph of keys and vertices is proposed in order to store the number of times two polypeptides are considered to be similar. This approach is found to have a reduction in time complexity from current mapping methods and thus provides a new approach by which to compute similar metrics.

Recommended Citation

Swensen, Arianna, "Improving Adjacency List Storage Methods for Polypeptide Similarity Analysis" (2022). Honors Theses. 2807.
https://egrove.olemiss.edu/hon_thesis/2807

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This work is licensed under a Creative Commons Attribution 4.0 International License.