Network analysis for systems biology

in Prokop, Aleš; Csukás (Eds.) Springer book in Systems Biology, Vol.1: Systems Biology:, Integrative Biology and Simulation Tools (2013)

Network analysis is an essential component of systems biology approaches toward understanding the molecular and cellular interactions underlying biological systems functionalities and their perturbations ... [more ▼]

Network analysis is an essential component of systems biology approaches toward understanding the molecular and cellular interactions underlying biological systems functionalities and their perturbations in disease. Regulatory and signalling pathways, which involve DNA, RNA proteins and metabolites as key elements, coordinate most aspects of cellular functioning. Cellular processes, which are dependent on the structure and dynamics of gene regulatory networks, can be studied by employing a network representation of molecular interactions. In this chapter we describe several types of networks and how combination of different analytic approaches can be used to study diseases. We provide a list of selected tools for visualization and network analysis. We introduce protein-protein interaction networks, gene regulatory networks, signalling networks and metabolic networks. We then define concepts underlying network representation of cellular processes and molecular interactions. We finally discuss how the level of accuracy in inferring functional relationships influences the choice of methods applied for the analysis of a particular network type. [less ▲]

Revolutionizing medicine in the 21(st) century through systems approaches

in Biotechnology Journal (2012), 7(8), 937-1054

Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to ... [more ▼]

Personalized medicine is a term for a revolution in medicine that envisions the individual patient as the central focus of healthcare in the future. The term "personalized medicine", however, fails to reflect the enormous dimensionality of this new medicine that will be predictive, preventive, personalized, and participatory-a vision of medicine we have termed P4 medicine. This reflects a paradigm change in how medicine will be practiced that is revolutionary rather than evolutionary. P4 medicine arises from the confluence of a systems approach to medicine and from the digitalization of medicine that creates the large data sets necessary to deal with the complexities of disease. We predict that systems approaches will empower the transition from conventional reactive medical practice to a more proactive P4 medicine focused on wellness, and will reverse the escalating costs of drug development an will have enormous social and economic benefits. Our vision for P4 medicine in 10 years is that each patient will be associated with a virtual data cloud of billions of data points and that we will have the information technology for healthcare to reduce this enormous data dimensionality to simple hypotheses about health and/or disease for each individual. These data will be multi-scale across all levels of biological organization and extremely heterogeneous in type - this enormous amount of data represents a striking signal-to-noise (S/N) challenge. The key to dealing with this S/N challenge is to take a "holistic systems approach" to disease as we will discuss in this article. [less ▲]

Candidate mutations for early-onset lung cancer by family genome sequencing

Poster (2011, July)

Early-onset lung cancer has been studied as a rare, but distinct, sub-type of lung cancer. Genome-wide association studies (GWAS) have linked several genes with this form of malignancy. We sequenced the ... [more ▼]

Early-onset lung cancer has been studied as a rare, but distinct, sub-type of lung cancer. Genome-wide association studies (GWAS) have linked several genes with this form of malignancy. We sequenced the genomes of a family quartet in which one of the offspring was diagnosed with early-onset lung cancer at about 48 years of age. The family has a history of heavy smoking and the father had in the past been diagnosed with head and neck cancer. The DNA source was blood, which leads us to concentrate our analysis on Mendelian inheritance models. To make the inheritance pattern explicit, we establish the parental origin of the offspring’s genomes through phasing of their chromosomes. This helps identify whether mutations in the proband came from the father or the mother. More than 18 million sequence variants were initially identified in the proband through comparison to the hg19 reference genome. We reduce this list to fewer than 200 potentially functional variants (e.g. single nucleotide variations and short indels) present in the genomes of the proband and at least one parent, by applying a series of filters. We refine the list of candidate mutations further by comparison to gene candidates from GWAS studies and genes that are mutated in lung cancer tissue as recorded by The Cancer Genome Atlas. The results of our analysis are discussed and conclusions about possible causative mutations for early-onset lung cancer are drawn. [less ▲]

Systems medicine and integrated care to combat chronic noncommunicable diseases

in Genome Medicine (2011), 3(7), 43-47

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic ... [more ▼]

We propose an innovative, integrated, cost-effective health system to combat major non-communicable diseases (NCDs), including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers, which together are the predominant health problem of the 21st century. This proposed holistic strategy involves comprehensive patient-centered integrated care and multi-scale, multi-modal and multi-level systems approaches to tackle NCDs as a common group of diseases. Rather than studying each disease individually, it will take into account their intertwined gene-environment, socio-economic interactions and co-morbidities that lead to individual-specific complex phenotypes. It will implement a road map for predictive, preventive, personalized and participatory (P4) medicine based on a robust and extensive knowledge management infrastructure that contains individual patient information. It will be supported by strategic partnerships involving all stakeholders, including general practitioners associated with patient-centered care. This systems medicine strategy, which will take a holistic approach to disease, is designed to allow the results to be used globally, taking into account the needs and specificities of local economies and health systems. [less ▲]