Khodade Prashant, Malhotra Samta, Kumar Nirmal, Iyengar M Sriram, Balakrishnan N, Chandra Nagasuma
Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore 560012, India.
J Biosci. 2007 Aug;32(5):965-77. doi: 10.1007/s12038-007-0096-y.
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.
生物细胞是具有首要生物学重要性的自然自包含单元,是一台极其复杂的机器,可在多个层面进行理解。对整个细胞的更高层次视角需要将各种特征整合为连贯的、具有生物学意义的描述。有一些基于细胞基因组、蛋白质组或代谢组描述对细胞进行建模的努力。然而,目前尚无既定方法来描述细胞形态、捕捉不同细胞之间或健康与疾病状态之间的异同。在此,我们报告一个框架,用于对细胞的各个方面进行建模,并整合在不同抽象层次编码的知识,一端是细胞形态,另一端是原子结构。已解决的不同问题包括本体论、特征描述和模型构建。该框架描述了虚线表示法和树状数据结构,以整合各种数据和参数模型,从而实现大小、形状和位置描述。该框架是整合生物细胞可用的不同层次数据的第一步,有潜力在我们构建细胞结构和功能模型的过程中推动计算模型的发展,并由此衍生出多种应用。