Nayan De
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Nayan De has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Achinta Sannigrahi
University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USA
1 shared publication - Debmalya Bhunia
Cold Spring Harbor Laboratory, 1 Bungtown Rd, Cold Spring Harbor, NY 11724, USA
1 shared publication - Jhuma Bhadra
School of Applied & Interdisciplinary Sciences, Indian Association for the Cultivation of Science, Kolkata 700032, India
1 shared publication - Md Sorique Aziz Momin
Department of Physics and Astronomy, Rochester Institute of Technology, Rochester, New York, USA
1 shared publication
Latest Publications
- Open Access
Unlocking Cellular Memory and Gene Regulatory Networks: Pioneering the Future of Therapeutic Innovations
Cellular memory is the competence of cells to preserve information from past experiences and respond aptly. This memory is maintained and controlled by gene regulatory networks (GRNs). GRNs are crucial for understanding why some cells are resistant to treatment, particularly for cancer. In our study, we created a new mathematical model to understand how “noise” affects cellular memory in GRNs, focusing on a “double positive feedback loop”. Our theoretical perspective article equipped with mathematical modeling exhibits how noise and feedback loops interact in GRNs. It also proposes a potential theoretical avenue for future therapy. By targeting the mechanisms that maintain drug resistance in cells, we aim to develop therapies that can restore the sensitivity of cancer cells to treatment.
Open AccessUnlocking Cellular Memory and Gene Regulatory Networks: Pioneering the Future of Therapeutic Innovations
Cellular memory is the competence of cells to preserve information from past experiences and respond aptly. This memory is maintained and controlled by gene regulatory networks (GRNs). GRNs are crucial for understanding why some cells are resistant to treatment, particularly for cancer. In our study, we created a new mathematical model to understand how “noise” affects cellular memory in GRNs, focusing on a “double positive feedback loop”. Our theoretical perspective article equipped with mathematical modeling exhibits how noise and feedback loops interact in GRNs. It also proposes a potential theoretical avenue for future therapy. By targeting the mechanisms that maintain drug resistance in cells, we aim to develop therapies that can restore the sensitivity of cancer cells to treatment.