The AI applied inter-disciplinary fields, namely

(i) Bioinformatics,

(ii) Computational Biology, and

(iii) Biomolecular Modeling and Simulation.

The domain "Bioinformatics" involves the combination of technologies in bioscience and data analytics. Similarly, the field "Computational Biology" is the combination of "Biomolecular Characterization" and "virtual modeling." All the areas mentioned above do not work in isolation but as a combined network to understand the differences in biological processes in normal (Physiological) and abnormal (Pathological) conditions. The significant difference between bioinformatics and computational biology is the construction of virtual models to mimic a real-time system (Computational Biology) and the identification of various computational techniques to understand the dynamics of sensitivity specificity and precision of individual components and the working system in the virtual model (Bioinformatics) involves the application of Artificial Intelligence. Then concerning Biomolecular Modeling and simulation, the 3-D model of small molecules (ligands) can be constructed using various tools based on the Lamarcian Genetic Algorithm. Finally, Molecular Simulations can be static (simulation of molecules in a vacuum environment) and dynamic (simulation of molecules in water, buffer, and related ions involved in the system). Molecular docking is a static simulation where changes are observed only at the binding pose of the ligand and receptor in the vacuum environment. Interactions between biomolecules can be of Protein-DNA, Protein-Protein, Protein-Ligand, Protein-Peptide, etc. Most of the peptides carry therapeutic value, i.e., applied medicine, and presently "Alpha-Fold" works well in predicting and optimizing biomolecular interaction.

At a glance

  • The main difference between bioinformatics and computational biology
  • Computational biology involves the creation of virtual models to mimic a real-time system
  • Bioinformatics involves the identification of various computational techniques
  • Comprehending the dynamics of sensitivity specificity and precision of individual components

Keywords: Bioinformatics, Computational Biology, Biomolecular Modeling, Simulation, Physiology, Pathology, Ligands, and Alpha-Fold

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