Using machine learning to understand how biomolecules interact in human signaling networks
Official title: Machine learning of biomolecular interactions and the human signaling networks they comprise
Funded at Columbia University Health Sciences · NIH-10932883 · Data updated 2026-11-12
This study is using smart computer techniques to understand how proteins and their partners work together in our bodies, which could help us learn more about and improve treatments for genetic diseases related to these important communication systems.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia University Health Sciences NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | September 22, 2023 |
| Project end | August 31, 2028 |
| Funding year | 2024 |
| Award (this year) | $411,250 |
| NIH project number | 5R35GM150546-02 |
| Project ID | NIH-10932883 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with genetic disorders that affect cellular signaling pathways.
✕Less likely to help
Patients with conditions unrelated to genetic signaling pathways may not receive any benefit from this research.
What this research studies
This research focuses on utilizing machine learning techniques to create detailed models of how biomolecules, particularly proteins and their ligands, interact within human signaling networks. By applying these models at a large scale, the research aims to uncover fundamental insights into the systems biology of human signaling. The approach involves advanced computational methods to predict interactions based on both the sequence and structure of proteins, with a special emphasis on modified ligands that play crucial roles in cellular communication. Patients may benefit from the findings as they could lead to improved understanding and treatment of genetic diseases linked to signaling pathways.
Why it matters
Potential benefit: If successful, this research could enhance our understanding of cellular signaling, potentially leading to new treatments for genetic diseases.
How similar studies have gone: Other research has shown promising results using machine learning to model biomolecular interactions, indicating that this approach has potential for success.
Where this research is happening
-
Columbia University Health Sciences
New York, United States Active
Researchers
- Principal investigator: Alquraishi, Mohammed Nazar — Columbia University Health Sciences
- Study coordinator: Alquraishi, Mohammed Nazar
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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.