Understanding the functions of lesser-known ion channels using advanced technology
Annotating dark ion-channel functions using evolutionary features, machine learning and knowledge graph mining (Kennady Boyd)
This study is looking into special proteins called dark ion channels that are important for how our cells work, and it's designed for anyone interested in understanding how these channels might be linked to diseases like cancer and heart problems.
Quick facts
| Grant type | U01 cooperative agreement |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Georgia NIH-funded |
| Lab location | 1 site (Athens, United States) |
| Project ID | NIH-10809950 on NIH RePORTER |
What this research studies
This research aims to explore and annotate dark ion channels, which are understudied proteins that play crucial roles in cellular functions. By utilizing a combination of evolutionary data, machine learning, and knowledge graph mining, the project seeks to predict and clarify the functions of these channels at both molecular and cellular levels. The researchers will develop new tools for visualizing and analyzing these channels, leveraging advanced computational methods and structural models derived from cryo-electron microscopy. This innovative approach could lead to a better understanding of how these channels contribute to various diseases, including cancers and cardiovascular disorders.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals affected by conditions related to ion channel dysfunction, such as certain cancers or cardiovascular diseases.
Not a fit: Patients with conditions unrelated to ion channel functions or those not affected by malignancies or cardiovascular disorders may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could enhance our understanding of ion channels, potentially leading to new therapeutic strategies for diseases like cancer and cardiovascular disorders.
How similar studies have performed: Other research has shown promise in utilizing machine learning and evolutionary data to understand protein functions, indicating that this approach could yield valuable insights.
Where this research is happening
Athens, United States
- University of Georgia — Athens, United States (Active)
Researchers
- Principal investigator: Kannan, Natarajan — University of Georgia
- Study coordinator: Kannan, Natarajan
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.