Gabriel Wright, Ph.D.
Assistant Professor
- Milwaukee WI UNITED STATES
- Diercks Hall DH414
- Computer Science
Gabriel Wright's primary research work is in computational biology.
Education, Licensure and Certification
Ph.D.
Computer Science and Engineering
University of Notre Dame
2021
M.S.
Computer Science and Engineering
University of Notre Dame
2020
B.A.
Mathematics
Concordia College
2016
Biography
Areas of Expertise
Accomplishments
Arthur J. Schmitt Leadership Fellowship
University of Notre Dame, 2016 – 2021
Event and Speaking Appearances
A New Look at Codon Usage and Protein Expression
11th International Conference on Bioinformatics and Computational Biology
Analysis of Popular Computational Codon Usage Models and Their Association With Ribosome Footprinting Implied Translational Slowdowns
Great Lakes Bioinformatics Conference
HarMinMax: Harmonizing Codon Usage to Replicate Local Host Trans- lation
ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
Selected Publications
CHARMING: Harmonizing synonymous codon usage to replicate a desired codon usage pattern
Protein ScienceThere is a growing appreciation that synonymous codon usage, although historically regarded as phenotypically silent, can instead alter a wide range of mechanisms related to functional protein production, a term we use here to describe the net effect of transcription (mRNA synthesis), mRNA half-life, translation (protein synthesis) and the probability of a protein folding correctly to its active, functional structure. In particular, recent discoveries have highlighted the important role that sub-optimal codons can play in modifying co-translational protein folding. These results have drawn increased attention to the patterns of synonymous codon usage within coding sequences, particularly in light of the discovery that these patterns can be conserved across evolution for homologous proteins. Because synonymous codon usage differs between organisms, for heterologous gene expression it can be desirable to make synonymous codon substitutions to match the codon usage pattern from the original organism in the heterologous expression host. Here we present CHARMING (for Codon HARMonizING), a robust and versatile algorithm to design mRNA sequences for heterologous gene expression and other related codon harmonization tasks. CHARMING can be run as a downloadable Python script or via a web portal at http://www.codons.org.
Network analysis of synonymous codon usage
BioinformaticsMost amino acids are encoded by multiple synonymous codons, some of which are used more rarely than others. Analyses of positions of such rare codons in protein sequences revealed that rare codons can impact co-translational protein folding and that positions of some rare codons are evolutionarily conserved.
Analysis of computational codon usage models and their association with translationally slow codons
PloS oneImproved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively.
%MinMax: A versatile tool for calculating and comparing synonymous codon usage and its impact on protein folding
Protein ScienceMost amino acids can be encoded by more than one synonymous codon, but these are rarely used with equal frequency. In many coding sequences the usage patterns of rare versus common synonymous codons is nonrandom and under selection. Moreover, synonymous substitutions that alter these patterns can have a substantial impact on the folding efficiency of the encoded protein. This has ignited broad interest in exploring synonymous codon usage patterns.
