Poster Session II
Work on PTMsToPathways (P2P) Bioinformatics R package development
Project Type
Poster
Faculty Mentor’s Full Name
Lucia Williams
Faculty Mentor’s Department
Computer Science
Abstract / Artist's Statement
The University's Grimes Lab researches how Post-Translational Modifications (PTMs) co-express with eachother under experimental conditions, as well as, the protein to protein and pathway to pathway network interactivity based on such expressions. Such research is important for understanding the logic behind cell signaling and plays a decisive role in understanding how gene expression treatments can affect cancer and diseases. In their research, Grimes Lab wrote software using the programming language R to perform such analysis, and collaborated with our lab. We take in an input PTM dataset, such as mass spectrometry data and find relevant PTM groupings using a t-distributed stochastic neighbor embedding. Then we combine that output with methods to analyze the implications of such interactions, like the interactions between cell signaling pathways and protein/gene interactions that are related to specific PTMs. Our lab provided a variety of software improvements. This includes guides on how to both install, use, and debug the software. Furthermore, we also optimized the package, updating with modern vectorization techniques. Additionally, we improved overall code stability, adding unit tests and modifying the package directory in order to comply with R's package guidelines. This is for the purpose of eventually submitting our results to a package repository such as bioconductor so users can access our software easily. This project provides a common solution to a large problem in biological data analysis. Many scientists create datasets that are interesting (but massive) as a byproduct of their research, but arrive at a loss as to what they can use it with. This package a free and easy-to-use solution which can provide further analysis on such data.
Category
Life Sciences
Work on PTMsToPathways (P2P) Bioinformatics R package development
UC South Ballroom
The University's Grimes Lab researches how Post-Translational Modifications (PTMs) co-express with eachother under experimental conditions, as well as, the protein to protein and pathway to pathway network interactivity based on such expressions. Such research is important for understanding the logic behind cell signaling and plays a decisive role in understanding how gene expression treatments can affect cancer and diseases. In their research, Grimes Lab wrote software using the programming language R to perform such analysis, and collaborated with our lab. We take in an input PTM dataset, such as mass spectrometry data and find relevant PTM groupings using a t-distributed stochastic neighbor embedding. Then we combine that output with methods to analyze the implications of such interactions, like the interactions between cell signaling pathways and protein/gene interactions that are related to specific PTMs. Our lab provided a variety of software improvements. This includes guides on how to both install, use, and debug the software. Furthermore, we also optimized the package, updating with modern vectorization techniques. Additionally, we improved overall code stability, adding unit tests and modifying the package directory in order to comply with R's package guidelines. This is for the purpose of eventually submitting our results to a package repository such as bioconductor so users can access our software easily. This project provides a common solution to a large problem in biological data analysis. Many scientists create datasets that are interesting (but massive) as a byproduct of their research, but arrive at a loss as to what they can use it with. This package a free and easy-to-use solution which can provide further analysis on such data.