On-location / Digital Conference

International Conference on Data Science for Protein Structure Prediction (ICDSPSP-27)

06th - 07th Mar 2027,Stockholm, Sweden

In Association With:

Call for Paper


Important Dates


Early Bird Registration

04th Feb 2027

Paper Submission Deadline

9th February 2027

Registration Deadline

19th February 2027

Conference Date

06th - 07th Mar 2027

Conference Updates:

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  • Early-Bird Registration Reminder:
    Early-bird registration for the Science Cite Conference in Stockholm ends soon! Register Now!
  • Certificate of Presentation – Recognizing Your Contribution:
    Receive a Certificate of Presentation to recognize your participation in Stockholm conference.
  • Peer Review Process:
    The peer review process will begin soon for Stockholm conference.
  • Networking with Global Experts:
    Join global experts at our conference in Stockholm.
  • Opportunity for Scopus-Indexed Journal Publication:
    Your research could be published in a Scopus-Indexed Journal. Submit Your Abstract
  • SDG-Inspired Conference Focus:
    Present your work aligned with Sustainable Development Goals.

Call For Papers

The ICDSPSP bridges the gap between academia and industry by promoting research with practical applications. It provides a platform for professionals and researchers to share insights that drive real-world impact.

The conference focuses on Data Science for Protein Structure Prediction, encouraging applied research, case studies, and industry-driven innovations.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • Data science techniques for protein prediction
  • Machine learning in protein structure analysis
  • Challenges in protein structure prediction
  • Integrative approaches to protein modeling
  • AI applications in protein folding studies
  • Ethics in protein research applications
  • Future trends in protein structure prediction
  • Collaborative projects in protein science
  • Real-time analysis of protein data
  • AI techniques for protein interaction prediction
  • Data integration in protein structure studies
  • Case studies in protein prediction
  • AI for understanding protein dynamics
  • Innovations in protein structure technology
  • Applications of AI in protein research
  • Data privacy in protein studies
  • AI-driven insights in protein analysis
  • Best practices in protein structure prediction
  • AI for structural bioinformatics applications
  • Visualization techniques for protein structures

Assessment

Submissions will be evaluated based on applicability, innovation, and research contribution. Accepted papers will be presented and considered for publication in relevant journals and proceedings.

Registration

Complete your registration to participate in discussions that bridge academia and industry, and gain exposure to practical insights.

Publication

Selected papers will be considered for publication platforms that support academic and industry collaboration.

Indexed / Supported By

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Academic Institutions Whose Scholars Have Contributed

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