Biological Network Inference: A Review of Methods and Assessment of Tools and Techniques

The topic of reconstruction of genetic networks is of great interest to the scientific community today – particularly those in the biological sciences. Essentially the need for network reconstruction is motivated by the need to find relationships between regulation mechanisms for genes, the need for discoveries in medicine, drug and pharmaceutical industry, the need for improved agricultural crops. All this requires a concerted effort from multi-disciplinary sciences, e.g. physics, mathematics, biology and chemistry – which have led to disciplines such as Systems Biology and Bioinformatics. Mathematical and statistical modeling has particularly been very instrumental for engineering and software development has been very useful in biological networks inference. Sometimes the link between theory, modeling and data acquisition is unclear. The goal in this article is to discuss tools and techniques for biological network inference and the areas of application. The pros and cons of network reconstruction methods are also provided. The number of scientific articles on network inference is overwhelming. Additionally, there is a dilemma in methodology choice, which is attributed to the scarcity of novel ways to compare the performance of the existing methods on experimental data. Applications of data visualization tools, modeling and simulation, data analysis and storage are given.