Systems biology - An understanding the functioning of biological systems
Systems biology is an interdisciplinary approach aimed at understanding the functioning of biological systems by integrating information of different nature and studying the network of dynamic connections existing between genes, proteins, metabolites and other molecules. it also aims to develop an explanatory model of systems of living organisms. Systems biology, which attempts to provide a single key to understanding the life phenomenon, is, in fact, not a new concept, since the attempt to look at a living system in a global way to fully understand its functioning is inherent in the scientific research of past decades. However, it has not yet been fully developed due to the lack of adequate computational and technological tools that allow the evaluation of several variables of the same system simultaneously.
Due to its nature, systems biology attracts different scientific areas and different skills, trying to develop a common language that overcomes the barriers between them. The disciplines that contribute to achieving this goal were widely developed during the twentieth century with extremely important results that allow us, for example, to explore space, to communicate through a mobile phone, surf the internet, and significantly extend the average life man. Nevertheless, we still fall ill with diabetes, cancer, neurodegenerative diseases, and other complex pathologies, since contemporary medicine has yet to develop effective strategies to predict and prevent the occurrence of these pathologies. The precise etiology of complex diseases and the reasons why some individuals show greater susceptibility to them are not yet known in detail. In other words, what is still lacking in our knowledge of how every single detail intervenes to modify the biological system.
Systems biology systematically addresses these questions. This new form of integrated science is supported in part by the desire to know the secrets of the biological universe, but even more by the richness of its applications. On the one hand, in fact, it should provide indications for personalizing medicine, on the other, it could have a significant impact in fields such as the development of new drugs, the preclinical and clinical trials necessary for their evaluation, diagnostics, and prediction the possible side effects of therapy. Add to this the possibility of focusing research on microorganisms, forcing their evolution towards an optimal adaptive state, useful, for example, to solve the problem of antibiotic resistance.
The pyramid of complexity
The reductionism of traditional biology (bottom-up approach), which has dominated scientific research for over a century, has generated an indescribable amount of information on individual cellular components and their function. It culminates in the much-discussed attempt to facilitate the understanding of life through the creation of a 'minimal organism' a single-celled individual, partially human-generated, containing as few genes as possible compatible with life. Although in some cases, interesting results have been obtained, none of them have been able to contribute to the global knowledge of living organisms. Hence the birth of the new research model called 'systems biology' (top-down approach). "Organisms work in an integrated way, our senses, our muscles, our metabolism, and our minds work together in perfect coordination. But biologists have historically studied organisms’ one part at a time and celebrated the modern ability to study them molecule by molecule, gene by gene.
High flow technology
The 21st century. It started with the completion of the human genome sequencing project. Although this has marked the achievement of an extraordinary milestone, it is now evident that the inventory, albeit detailed, of genes, as well as proteins and metabolites. They are the beginning of a new and more ambitious adventure, whose objective is the understanding of the interactions between each of the identified elements. Modern high throughput technology), the result of the integration between biology and engineering, intervenes at this level by providing indispensable support. By high flow technology, we mean the development of laboratory methods capable of simultaneously querying a biological system such as the cell at any time of its life, and of collecting all the information that derives from it, generating a database that can be subsequently analyzed. An example of high-flow technology that is widespread today is the microarray DNA, based on the use of glass supports of a few centimeters, which, by resorting to robotics, can contain the genome of an entire organism.
Complex network theory
Substantial support is provided by mathematics with the emerging ' complex network theory.’ In recent years, it has followed the path of understanding the principles that oversee the formation and evolution of numerous networks, be they technological or social. Probably the most interesting discovery of complex network theory consists in having understood that the structural characteristics of a network of molecular interactions within a cell are shared with those of other complex systems. Despite the remarkable diversity of systems in nature, they are governed by universal principles, which make it possible to use all the knowledge acquired from the large and well-known non-biological systems to characterize the intricate maze of relationships that exists in a living organism.
The behavior of many complex systems, from the cell to the internet, emerges from the concerted activity of numerous elements that interact with each other through relationships, the smallest of which is that existing between only two elements. In an abstract and simplifying way, each constituent of a system can be considered a node connected to other nodes through bonds. Each bond refers to the interaction between only two parts. Knots and ties together form a network or, in more strictly mathematical language, a graphic.
The networks can be defined as 'direct' or 'indirect' according to the nature of the interactions that occur in them. In direct networks, the interactions between any two nodes have a defined direction. For example, the flow of material needed in the production of new tissues or the flow of information that goes from a cell to another cell for communication with each other. In indirect networks, on the other hand, the bonds do not have a unique direction: for example, in the interactions between proteins, a bond represents a reciprocal interaction, if the protein X binds the protein Y, consequently, the protein Y binds the protein X.