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Motivation for writing this book came from the strong desire of the authors to explore the potential of building a Cellular Automata (CA) model that can be employed to address the problems of interest for industry and human society. The outline of the design of Cellular Automata enhanced with Machine Learning (CAML) model for two application domains is presented in Chap. 4. Chapter 5 applies Cellular Automata (enhanced with) Machine Learning (CAML) to computational biology, specifically in protein mutation analysis. It explores its use in studying viral proteins, such as those in SARS-CoV-2, to predict mutations, antibody resistance, and potential biomarkers for medical research. The chapter covers Proteomics study for - (i) three CoV-2 virus proteins, (ii) analysis of p53 protein (encoded by TP53 gene and implicated for majority of cancer types), and (ii) identification of Medicinal Plants displaying Anti-Cancer property.

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CAML Model for Computational Biology

  • 章节

  • 发表日期：

    2025年

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  • Parimal Pal Chaudhuri,
  • Adip Dutta,
  • Somshubhro Pal Choudhury,
  • Dipanwita Roy Chowdhury,
  • Raju Hazari

摘要

Motivation for writing this book came from the strong desire of the authors to explore the potential of building a Cellular Automata (CA) model that can be employed to address the problems of interest for industry and human society. The outline of the design of Cellular Automata enhanced with Machine Learning (CAML) model for two application domains is presented in Chap. 4. Chapter 5 applies Cellular Automata (enhanced with) Machine Learning (CAML) to computational biology, specifically in protein mutation analysis. It explores its use in studying viral proteins, such as those in SARS-CoV-2, to predict mutations, antibody resistance, and potential biomarkers for medical research. The chapter covers Proteomics study for - (i) three CoV-2 virus proteins, (ii) analysis of p53 protein (encoded by TP53 gene and implicated for majority of cancer types), and (ii) identification of Medicinal Plants displaying Anti-Cancer property.