Title: Ion Channels and Oxidative Stress as a Potential Link for understanding Cardiovascular Diseases: A data science approach.

Description : The roles of ion channels and other extracellular matrix proteins have been studied in various domains of disease diagnosis and treatment. The accumulation of large amounts of data and interest in conjunction of ion channels and oxidative stress in the context of Cardiovascular Disease (CVD) necessitates a smart text mining and data analysis pipeline.

In this project we identify all the ion channels and transporters participating in maintaining the intracellular Ca homeostasis in the cardiac myocytes as well as mitochondria and systematically present the classification of ion channels. Next we identify the chemicals or molecules involved in the oxidative stress and design the classification of Oxidative stress based on their involvement (e.g. Initiation of Oxidative Stress (IOS), Regulation of Oxidative stress (ROS), Outcomes of Oxidative Stress (OOS). Similarly we identify eight categories of Cardiovascular Disease. Our goal is to understand underlying molecular mechanisms involving ion-channel associated in CVDs and how they are regulated by oxidative stress. One possible way is to look at ion channel proteins involved in oxidative stress and explore how they are associated in CVDs.

Project walk-through

• Define the datasets in the projects. The dataset includes a family of ion-channels (uniprot ID and functions), CVD’s in MeSH and ICD11 codes, terminology and descriptors of oxidative stress (self generated). Drug Bank (API for drugs and drug target exploration)
• Get familiar with ion-channel classification.
• Learn to extract Drug information from DrugBank API and understand Cardiovascular drug and drug-targets classification.
• Get familiar with a curated list of Oxidative Stress categories and associated molecules.
• Get Familiar with MeSH tree and ICD codes and CVD classification.
• Compare the list of ion-channel proteins and look at how many of them are CVD drug targets.
• Develop the ranking (caseOLAP) of ion-channel proteins over Oxidative stress categories. Develop the ranking (caseOLAP) of ion-channel proteins over CVD categories.
• Explore how many of the proteins significant in some oxidative stress categories are prominent in some specific CVDs. How about drug target ion-channel proteins involvement in oxidative stress categories and CVDs.
• Explore molecular mechanisms through reactome for involved proteins and delineate how they are associated with oxidative stress and CVDs.
• Organize codes and prepare project documentation (or work in the manuscript) sites at PingLab Intern GitHub account.
• Final presentation at lab meeting.

Education goals: The students will learn how to work with innovative text mining tools (e.g., caseOLAP, Neo4J) for biomedical documents and machine learning approach (dimensionality reduction, clustering, graph neural network) for model development and implementation to answer important biomedical questions.

Scientific goals: The students will explore knowledge graphs for oxidative stress, ion-channel, drug and CVD associations with a focus on oxidative stress categories (e.g., Initiation, Regulation and Outcome) and underlying molecular mechanisms involved in ion-channels.

Workflow