The mechanisms behind life are inherently complex. In the last years, increasing research activity has shown that our understaning of life, and human diseases, is not complete if only one source of information (proteomics
) is used.
is an approach which accounts for different sources of information to build an integrate model of life and disease. In this context, methodologies based con complex systems science
and network science
Multilayer networks approach to molecular biology
A fairly standard approach to the analysis of human diseases is based on the enrichment of topological and functional connectivity representing protein-protein interaction networks.
Figure: PPI network and disease. The concept of disease modules exemplified using a sample PPIN. One or more topological modules (highlighted red) contain proteins involved in similar biological
processes forming functional modules (highlighted blue). A disease module (highlighted green) is a sub-network of proteins enriched with disease-relevant proteins, e.g., known disease associated proteins. (Figure and caption from this source)
provide one of the most promising for modeling systems biology and for their analysis.
I have verified this claim quantitatively, by building multilayer networks where nodes are genes and proteins, links represent their interactions, and each layer encodes a different relation (physical chemical, genetic, including regulatory, inhibitory, etc.) and quantify the overall structural reducibility of the resulting system.
- M. De Domenico, V. Nicosia, A. Arenas, V. Latora. Nature Communications 6, 6864 (2015)
More recently, I have applied this framework to map complex disease-gene and disease-symptom interactions to a multiplex networks with two layers. Layers encode phenotypic and genotypic relations, allowing a better characterization and classification of human diseases.
Figure: Multiplex disease network. (A) Two bipartite networks of disease-gene and disease-symptom interactions are projected onto diseases, (B) where diseases are connected in the genotype layer (blue) if they share a common gene and connected in the phenotype layer (green) if they share a symptom. (C) The two networks are considered as layers of a multiplex system, where nodes are the diseases and colored links encode their interactions. Disease-disease interactions that are present in both layers are named overlapping links.
- A. Halu*, M. De Domenico*, A. Arenas, A. Sharma. bioRxiv 100370 (2017) [View]
Multilayer networks approach to computational neuroscience
After proposing a novel multilayer representation of fuctional connectivity in human brain, I have shown that multilayer analysis allows to identify crucial regions (ie, hubs) that can be used to increase accuracy in distinguishing between healthy and schizophrenic patients from resting-state fMRI measurements. If you are interesting in knowing more about multilayer approaches to model and to analyze the human brain, you can read my very recent review on the topic
Figure: Multilayer functional brain. Brain activity is measured in different regions and signals are decomposed in the frequency domain. The frequency domain consists of (possibly overlapping) frequency bands and, for each band, coherence -- or other similarity descriptors -- is measured between all pairs of regions. A similarity matrix is built for each frequency domain and statistical analysis of significance is used to map each matrix into a functional network, constituting a functional layer of the overall multilayer system.
Figure: Visualizing the multilayer functional brain. Three-dimensional representations of the multilayer functional brain of a schizophrenic subject, based on frequency decomposition (11 layers, non-overlapping frequency bands between 0.01~Hz and 0.23~Hz). Only links with at least 6 standard deviations from the mean are shown. Top panels: edge-colored representation, where connections are colored according to the frequency band and node size is proportional to their functional versatility. Bottom panel: multi-slice representation, where each layer encodes information about a specific frequency bandand inter-layer connectivity is not shown explicitly for sake of simplicity. The color scheme is the same in the two representations.
- M. De Domenico, S. Sasai, A. Arenas. Frontiers in Neuroscience 10, 326 (2016)
- M. De Domenico. GigaScience (In press) (2017)