An extensible markup language format insilicoML (ISML) version 0.1 describing multi-level biophysical models has been developed and is available in the public domain. ISML is fully compatible with CellML 1.0, a model description standard developed by the IUPS Physiome Project, for enhancing knowledge integration and model sharing. This article illustrates the new specifications of ISML 1.0 that largely extend the capability of ISML 0.1. ISML 1.0 can describe various types of mathematical models including ordinary/partial differential/difference equations representing the dynamics of physiological functions and the geometry of living organisms underlying the functions. ISML 1.0 describes a model using a set of functional elements (modules) each of which can specify mathematical expressions of the functions of the module. Structural and logical relationships between any two modules are specified by edges, which allow modular, hierarchical, and/or network representations of the model. The role of edge-relationships is enriched by keywords in order for use in constructing a physiological ontology. The ontology is further improved by the traceability of history of the model development and by linking between different ISML models stored in the model database using meta-information. ISML 1.0 is designed to operate with a model database and integrated environments for model development and simulations for knowledge integration and discovery.

Fig.1. The insilico model can cooperate with other model-development environments such as model database, morphological/timeseries data database and other computer languages used for simulations. Since the insilico model is written by insilicoML based on XML, it can be easily converted to other format such as C++, CellML, BUNKI format, LaTeX and so on. An insilico model is composed of one or several module(s) , main actors representing functional components, linking to each other by edges representing structural and functional relationships among modules. A module can involve morphological and/or timeseries data (numerical data) to characterize the geometry and/or dynamics of the module.