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Structural Mechanobiology Lab

Welcome to the Structural Mechanobiology Lab's GitHub organization. Our lab, led by Dr. Shubhasis Haldar, is dedicated to unraveling the complexities of force-regulated biological phenomena, which are fundamental to various pathophysiological conditions.

Research Focus

We employ a multidisciplinary approach, integrating traditional cell biology, state-of-the-art nanoscopy, machine learning, and advanced computational biology to explore:

  • Mechanical Roles of Chaperone-Assisted Protein Folding: Investigating how chaperones influence protein folding under mechanical stress.

  • Mechanosensitive Proteins in Focal Adhesion-Mediated Cellular Processes: Studying the role of mechanosensitive proteins in cellular adhesion and migration.

  • Developmental Mechanobiology and Cancer Intersection: Exploring how mechanical forces influence tissue development and their implications in cancer.

  • Regulation of Protein Mechanics by Small Molecule Drugs and Microenvironment: Examining how drugs and the cellular environment affect protein mechanical properties.

For detailed information on our research themes, please visit our Research Page.

Publications

Our work has been featured in several peer-reviewed journals. For a comprehensive list of our publications, please refer to our Publications Page.

Team

Our lab comprises a diverse group of scientists and researchers. Learn more about our team on our Scientists Page.

Open Positions

We are currently accepting applications for a PhD position for the January 2025 session. Interested candidates with valid CSIR/UGC-NET JRF in Biology or Chemistry should notify us via email and apply through the S.N. Bose National Centre for Basic Sciences website.

Contact

For inquiries or collaboration opportunities, please visit our Contact Page.

Acknowledgments

Our research is generously funded by the following organizations:

For more information about our lab and ongoing projects, please visit our official website.

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  1. ACSCEND ACSCEND Public

    Comprehensive Enumeration of Cancer Stem-like Cell Heterogeneity Using Deep Neural Network

    Jupyter Notebook 1

  2. OncoMark OncoMark Public

    A deep learning tool designed to predict Cancer Hallmark activities from tumor biopsy samples.

    Jupyter Notebook

Repositories

Showing 5 of 5 repositories
  • acscend2 Public
    SML-CompBio/acscend2’s past year of commit activity
    Jupyter Notebook 0 0 0 0 Updated Jan 22, 2025
  • ACSCEND Public

    Comprehensive Enumeration of Cancer Stem-like Cell Heterogeneity Using Deep Neural Network

    SML-CompBio/ACSCEND’s past year of commit activity
    Jupyter Notebook 1 0 0 0 Updated Jan 22, 2025
  • OncoMark Public

    A deep learning tool designed to predict Cancer Hallmark activities from tumor biopsy samples.

    SML-CompBio/OncoMark’s past year of commit activity
    Jupyter Notebook 0 Apache-2.0 0 0 0 Updated Jan 20, 2025
  • .github Public
    SML-CompBio/.github’s past year of commit activity
    0 0 0 0 Updated Jan 10, 2025
  • KINDLIN-PANCAN Public

    The repository contains the source code used in the paper: "Pancancer Analyses Suggest Kindlin-associated Global Mechanochemical Perturbation"

    SML-CompBio/KINDLIN-PANCAN’s past year of commit activity
    Jupyter Notebook 0 MIT 0 0 0 Updated Apr 12, 2024

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