Organization principles of biological networks: An explorative study

详细信息    查看全文

• 作者：Havva Kohestani^a ; ^{ha_koohestani90@ms.tabrizu.ac.ir" class="auth_mail" title="E-mail the corresponding author} ; Alessandro Giuliani^b ; ^{alessandro.giuliani@iss.it" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Graph theory ; Systems biology ; Topology ; Biocomplexity ; Principal component analysis
• 刊名：Biosystems
• 出版年：2016
• 出版时间：March 2016
• 年：2016
• 卷：141
• 期：Complete
• 页码：31-39
• 全文大小：1161 K

文摘

The definition of general topological principles allowing for graph characterization is an important pre-requisite for investigating structure–function relationships in biological networks. Here we approached the problem by means of an explorative, data-driven strategy, building upon a size-balanced data set made of around 200 distinct biological networks from seven functional classes and simulated networks coming from three mathematical graph models.

A clear link between topological structure and biological function did emerge in terms of class membership prediction (average 67% of correct predictions, p < 0.0001) with a varying degree of ‘peculiarity’ across classes going from a very low (25%) recognition efficiency for neural and brain networks to the extremely high (80%) peculiarity of amino acid–amino acid interaction (AAI) networks.

We recognized four main dimensions (principal components) as main organization principles of biological networks. These components allowed for an efficient description of network architectures and for the identification of ‘not-physiological’ (in this case cancer metabolic networks acting as test set) wiring patterns.

We highlighted as well the need of developing new theoretical generative models for biological networks overcoming the limitations of present mathematical graph idealizations.