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    • Keywords


      Cell modelling; cell morphology; cell ontology; computational models; dotted representation

    • Abstract


      The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a first step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can flow out.

    • Author Affiliations


      Prashant Khodade1 Samta Malhotra2 Nirmal Kumar2 M Sriram Iyengar3 N Balakrishnan1 Nagasuma Chandra1 2

      1. Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India
      2. Bioinformatics Centre, Indian Institute of Science, Bangalore 560012, India
      3. University of Texas Health Science Center, Houston, Texas 77030, USA
    • Dates

  • Journal of Biosciences | News

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      Posted on July 25, 2019

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