Increasingly, conventional approaches and technologies (e.g., use of a single methodology like whole proteomics or whole genomics) are inefficient to explain biological systems. Therefore, systems biology needs an integrative approach to clarify complex, multi-dimensional processes within cells or whole ...
Increasingly, conventional approaches and technologies (e.g., use of a single methodology like whole proteomics or whole genomics) are inefficient to explain biological systems. Therefore, systems biology needs an integrative approach to clarify complex, multi-dimensional processes within cells or whole organisms. Both qualitative and quantitative analyses performed by different omics techniques in the frame of systems biology elaborate information about organ development and differentiation, cell interactions, diseases or therapy regimes, stress and defense mechanisms, etc. Omics tools and approaches are the only technologies that utilize information from a majority of the involved biomolecules at one single time point to understand the hidden parts or black boxes of a biological system (e.g., the pathways or signal transduction proteins) and identify the most probable mechanisms underlying a biological event or process. A prominent example is undoubtedly p53, a well-known protein, which has over 6000 cited functions. In order to understand its role in distinct biological phenomenology, we need integrative approaches to minimize the biased information and to understand the main biological function. In fact, most proteins are involved in more than one function and pathway, so data interpretation becomes in most cases an impossible mission.
Automated and high-throughput genome sequencing, microarray, and modern mass spectrometry transcriptomics used for proteomics and metabolomics profiling lead to large-scale data analysis burdens. The delivered huge amounts of data resulting from high-throughput machinery need to be interpreted by bioinformatics. The aim of this Research Topic is to give a concise description of systems biology and information on the benefits and disadvantages of any given sample and organism analyzed by omics and integrative approaches. The contributions should be representative for this research strategy to solve prominent topics in a variety of biological research fields.
The scope of the current Research Topic is to cover promising, recent, and novel research trends in the application of omics technologies for exploration of systems biology.
Image credit : Meraj Sharifi ©
Keywords:
Integrative view, bioinformatics, systems biology, transdisciplinary knowledge, data interpretation
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