Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.
BMC Bioinformatics. 2019 Aug 27;20(1):442. doi: 10.1186/s12859-019-2997-9.
Contemporary biological observations have revealed a large variety of mechanisms acting during the expansion of a tumor. However, there are still many qualitative and quantitative aspects of the phenomenon that remain largely unknown. In this context, mathematical and computational modeling appears as an invaluable tool providing the means for conducting in silico experiments, which are cheaper and less tedious than real laboratory experiments.
This paper aims at developing an extensible and computationally efficient framework for in silico modeling of tumor growth in a 3-dimensional, inhomogeneous and time-varying chemical environment. The resulting model consists of a set of mathematically derived and algorithmically defined operators, each one addressing the effects of a particular biological mechanism on the state of the system. These operators may be extended or re-adjusted, in case a different set of starting assumptions or a different simulation scenario needs to be considered.
In silico modeling provides an alternative means for testing hypotheses and simulating scenarios for which exact biological knowledge remains elusive. However, finer tuning of pertinent methods presupposes qualitative and quantitative enrichment of available biological evidence. Validation in a strict sense would further require comprehensive, case-specific simulations and detailed comparisons with biomedical observations.
当代生物学观察揭示了肿瘤扩张过程中存在大量作用机制。然而,该现象仍有许多定性和定量方面的内容尚不清楚。在这种情况下,数学和计算建模作为一种宝贵的工具出现,为进行计算机实验提供了手段,与真实的实验室实验相比,计算机实验更便宜、不那么繁琐。
本文旨在开发一个可扩展且计算高效的框架,用于在 3 维、不均匀和时变化学环境中进行肿瘤生长的计算机模拟。所得到的模型由一组数学推导和算法定义的算子组成,每个算子都针对特定生物学机制对系统状态的影响。如果需要考虑不同的初始假设集或不同的模拟场景,可以扩展或重新调整这些算子。
计算机模拟为测试假设和模拟确切的生物学知识难以捉摸的情况提供了另一种手段。然而,相关方法的精细调整需要定性和定量地丰富现有生物学证据。严格意义上的验证还需要进行全面、特定于案例的模拟,并与生物医学观察进行详细比较。