Using advanced neural networks to understand how single cells behave
MANET: Maximum Entropy Neural Networks for Mechanistic Modeling of Single Cell Behavior
This study is all about figuring out how individual cells behave and communicate by using computer models to analyze their data, and it's designed for scientists who want to better understand cell dynamics and how cells react to their surroundings.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Yale University NIH-funded |
| Lab location | 1 site (New Haven, United States) |
| Project ID | NIH-10925421 on NIH RePORTER |
What this research studies
This research focuses on improving our understanding of single cell behavior by integrating single cell data with mechanistic signaling network models. It employs a computational approach using Maximum Entropy neural networks to analyze and predict cell dynamics and variability. By collaborating with experimentalists, the research aims to validate its computational architecture and study the biochemical processes that influence how cells communicate and respond to their environment. This innovative methodology seeks to bridge the gap between experimental data and theoretical models in cellular biology.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals with conditions that involve cellular signaling and communication, such as cancer or autoimmune diseases.
Not a fit: Patients with conditions unrelated to cellular behavior or those who do not have access to the necessary single cell analysis techniques may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to breakthroughs in understanding cellular behavior, which may improve treatments for various diseases by targeting specific cellular mechanisms.
How similar studies have performed: Other research has shown promise in using computational methods to model biological networks, indicating that this approach could yield significant insights.
Where this research is happening
New Haven, United States
- Yale University — New Haven, United States (Active)
Researchers
- Principal investigator: Dixit, Purushottam — Yale University
- Study coordinator: Dixit, Purushottam
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.