Toward integration of biological and physiological functions at multiple levels

A Unifying Framework for Understanding Biological Structures and Functions Across Levels of Biological Organization

The relationship between structure and function is a major constituent of the rules of life. Structures and functions occur across all levels of biological organization. Current efforts to integrate conceptual frameworks and approaches to address new and old questions promise to allow a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization. Here, we provide unifying and generalizable definitions of both structure and function that can be applied across all levels of biological organization. However, we find differences in the nature of structures at the organismal level and below as compared to above the level of the organism. We term these intrinsic and emergent structures, respectively. Intrinsic structures are directly under selection, contributing to the overall performance (fitness) of the individual organism. Emergent structures involve interactions among aggregations of organisms and are not directly under selection. Given this distinction, we argue that while the functions of many intrinsic structures remain unknown, functions of emergent structures are the result of the aggregate of processes of individual organisms. We then provide a detailed and unified framework of the structure-function relationship for intrinsic structures to explore how their unknown functions can be defined. We provide examples of how these scalable definitions applied to intrinsic structures provide a framework to address questions on structure-function relationships that can be approached simultaneously from all subdisciplines of biology. We propose that this will produce a more holistic and robust understanding of how different biological functions are achieved across levels of biological organization.

Databases for multilevel biophysiology research available at Physiome.jp

Physiome.jp (http://physiome.jp) is a portal site inaugurated in 2007 to support model-based research in physiome and systems biology. At Physiome.jp, several tools and databases are available to support construction of physiological, multi-hierarchical, large-scale models. There are three databases in Physiome.jp, housing mathematical models, morphological data, and time-series data. In late 2013, the site was fully renovated, and in May 2015, new functions were implemented to provide information infrastructure to support collaborative activities for developing models and performing simulations within the database framework. This article describes updates to the databases implemented since 2013, including cooperation among the three databases, interactive model browsing, user management, version management of models, management of parameter sets, and interoperability with applications.

A versatile platform for multilevel modeling of physiological systems: template/instance framework for large-scale modeling and simulation

Building multilevel models of physiological systems is a significant and effective method for integrating a huge amount of bio-physiological data and knowledge obtained by earlier experiments and simulations. Since such models tend to be large in size and complicated in structure, appropriate software frameworks for supporting modeling activities are required. A software platform, PhysioDesigner, has been developed, which supports the process of creating multilevel models. Models developed on PhysioDesigner are established in an XML format called PHML. Every physiological entity in a model is represented as a module, and hence a model constitutes an aggregation of modules. When the number of entities of which the model is comprised is large, it is difficult to manage the entities manually, and some semiautomatic assistive functions are necessary. In this article, which focuses particularly on recently developed features of the platform for building large-scale models utilizing a template/instance framework and morphological information, the PhysioDesigner platform is introduced.

Software for systems biology: from tools to integrated platforms

Understanding complex biological systems requires extensive support from software tools. Such tools are needed at each step of a systems biology computational workflow, which typically consists of data handling, network inference, deep curation, dynamical simulation and model analysis. In addition, there are now efforts to develop integrated software platforms, so that tools that are used at different stages of the workflow and by different researchers can easily be used together. This Review describes the types of software tools that are required at different stages of systems biology research and the current options that are available for systems biology researchers. We also discuss the challenges and prospects for modelling the effects of genetic changes on physiology and the concept of an integrated platform.