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Instrumentation for Assessing mTBI Events
Published in Mark A. Mentzer, Mild Traumatic Brain Injury, 2020
Systems biology has emerged as an integrative and holistic approach, aiming to assimilate knowledge through relatively large and complex amounts of data generated by high-throughput biological applications and tools … facilitated by the increased availability of novel high-throughput screening techniques such as whole genome sequencing proteomics, and next-generation sequencing (NGS) … all serving to ultimately transform heterogeneous data into useful knowledge that can influence healthcare and biomedical research. (Kobeissy et al., 2019)
Systems Biology
Published in Lawrence S. Chan, William C. Tang, Engineering-Medicine, 2019
Lawrence S. Chan, William C. Tang
In this chapter, we introduce the concept of systems biology, a new path of looking at biology from a systemic perspective. We have discussed the rationale behind the development of the field, some essential characteristics, and advantages and limitations of the field. We further reviewed the basic tools to build mathematical models for biological functions, including calculus, linear algebra, probability, Laplace and Fourier Transforms. A brief description of the common computational software was also included. Example of mathematical modeling was provided to introduce the students to this new knowledge element. The chapter concludes with a discussion on the human body as one interconnected and integrated system: homeostasis.
The Volatilome in Metabolomics
Published in Raquel Cumeras, Xavier Correig, Volatile organic compound analysis in biomedical diagnosis applications, 2018
Raquel Cumeras, Xavier Correig
Systems biology (Ideker et al., 2001) examines the behavior and relationships of all of the components in a particular biological system while it is functioning. An alternative description (Bekri, 2016) is that “systems biology is the computational integration of data generated –omic platforms to understand function across different levels of biomolecular organization.” The Human Genome Project unveiled the need to understand the relationship between genome by studying the products of the genome, namely proteins and expressed RNAs, such as tRNA and rRNA. This lead to the emergence of the transcriptomics and proteomics fields. This flowering of -omics sciences also spread to the low-molecular-weight compounds that carry out much of the cell’s function like lipids, carbohydrates, vitamins, and hormones, among others. In parallel to the terms ‘transcriptome’ and proteome,’ the set of metabolites synthesized by a biological system constitute its ‘metabolome’ (Fiehn, 2002). Volatilomics refers to the study of the volatile fraction of the metabolome. A reductionist view of every single -omic, will give an insight of what is happening in a precise level so that we can construct a whole model.
Novel predictive model of cell survival/death related effects of Extracellular Signal-Regulated kinase protein
Published in Artificial Cells, Nanomedicine, and Biotechnology, 2023
Shruti Jain, Ayodeji Olalekan Salau
System biology is the study of the properties of complex biological systems that develop from the interactions of several proteins. Systems biology aims to expand organisms' behavior by utilizing scientific and technological knowledge so they can carry out new tasks. Deoxyribonucleic acid (DNA), ribonucleic acid (RNA), proteins, and metabolites (including carbohydrates, lipids, amino acids, and nucleotides) from the newly constructed behaviour’s bottom-up hierarchy are a few examples of biological systems. Biological systems have recently been compared to electronic systems, which contain a bottom-up layer consisting of a physical layer, a device layer, and a module layer [1]. Transistors, capacitors, and resistors form the physical layer, while all the computations performed in the computer by the electrical circuits form the device layer, and components like the integrated circuits form the module layer [2,3].
Knowledge graphs and their applications in drug discovery
Published in Expert Opinion on Drug Discovery, 2021
Systems biology describes the computational modeling of molecular systems, drawing from many disciplines including computer science and physics. One of the fundamental principles of biological life is that the accumulation of simple, locally-acting components leads to complex structures and systems. Systems biology follows this principle, describing a complex biological system as a network of simple biological components (analogous to those in electronic circuits) and simulates how the system changes in response to certain stimuli. These systems consist of intra- and inter-cellular interactions amongst molecules that govern biological functions, and whose dysregulation leads to disease. Their networks often contain multi-scale elements, ranging from molecular components to tissues; both physical and abstract entities, ranging from proteins to phenotypic outcomes. Networks also contain diverse types of interactions between entities, such as inhibitions, activations, associations and causal interactions.
The combination of artificial intelligence and systems biology for intelligent vaccine design
Published in Expert Opinion on Drug Discovery, 2020
Giulia Russo, Pedro Reche, Marzio Pennisi, Francesco Pappalardo
On the other hand, systems biology refers to an interdisciplinary approach that systematically describes the complex interactions between all the parts in a biological system to elucidate new rules capable of predicting the behavior of the biological system [38]. Substantial attention has been given to one of its subfields called systems vaccinology [39], an interdisciplinary field that associates systems-wide measurements, networks, and predictive modeling in the context of vaccinology. Its aim is to enhance our understanding of immunity and improve the design of new vaccine systems, addressing specific issues with regard to potency, durability, and specificity [40]. This can be achieved through the aggregation of some critical properties such as perturbation of the system [41], monitoring responses at the systems level [42], data integration [43], network modeling [44] and prediction of vaccine response [45]. The main applications of systems vaccinology in vaccine research embrace all phases of vaccine development [46] through the implementation of high-throughput data from different techniques (e.g., cell-based assays [47], proteomics [48], transcriptomics [49]), providing detailed insight in composition, immunogenicity, and safety of the vaccine.