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International Conference on Applied Mathematics for Computational Biology and Bioinformatics - (ICAMCB-27)

15th - 16th April 2027 , Vienna - Austria

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Call For Papers

The (ICAMCB-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Applied Mathematics, Mathematical Modeling are explored to promote cross-domain knowledge exchange and collaborative innovation.

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

  • Mathematical models in genomics research
  • Bioinformatics algorithms for sequence analysis
  • Statistical methods in computational biology
  • Modeling biological networks and pathways
  • Mathematical modeling of disease spread
  • Computational methods in systems biology
  • Machine learning in bioinformatics applications
  • Mathematical modeling of protein interactions
  • Data integration in computational biology
  • Mathematical modeling of metabolic networks
  • Bioinformatics tools for data analysis
  • Mathematical modeling of ecological systems
  • Statistical genetics and population modeling
  • Mathematical modeling of cellular processes
  • Computational approaches to drug discovery
  • Mathematical modeling of evolutionary dynamics
  • Network analysis in biological systems
  • Mathematical modeling of immune responses
  • Computational methods for personalized medicine
  • Mathematical modeling of microbiome interactions

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.