Exploring autonomy through computational biomodelling.

The question of whether living organisms possess autonomy of action is tied up with the nature of causal efficacy. Yet the nature of organisms is such that they frequently defy conventional causal language. Did the fig wasp select the fig, or vice versa? Is this an epithelial cell because of its genetic structure, or because it develops within the epithelium? The intimate coupling of biological levels of organisation leads developmental systems theory to deconstruct the biological organism into a life-cycle process which constitutes itself from the resources available within a complete developmental system.

Modeling biochemical transformation processes and information processing with Narrator.

Background: Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models.

Reverse-engineering gene-regulatory networks using evolutionary algorithms and grid computing.

Objective: Living organisms regulate the expression of genes using complex interactions of transcription factors, messenger RNA and active protein products. Due to their complexity, gene-regulatory networks are not fully understood.However, by building computational models it is possible to gain insight into their function and operation.

Representing bioinformatics causality.

This paper reviews a variety of different graphical notations currently in active use for modelling dynamic processes in bioinformatics and biotechnology, and crystallises from these notations a set of properties essential to any proposal for a modelling language seeking to provide an adequate systemic description of biological processes.

The construction of meaning in computational integrative biology.

It is the contention of this paper that current data mining work in bioinformatics tends to emphasize data representation to the neglect of another essential aspect of biological systems, namely dynamics. This results in a divorce of both the enterprise and the teaching of bioinformatics from its central aim of meaning-construction. The paper argues that this neglect of dynamics is rooted in an information-processing view of cognitive psychology, and needs to be complemented by a more narrative perspective which emphasizes the explanation, rather than the mere description, of observed patterns in data.