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Sheng Wu Gong Cheng Xue Bao = Chinese... Oct 2019In industrial biotechnology, microbial cell factories utilize renewable resources to produce energy, materials and chemicals. Industrial biotechnology plays an... (Review)
Review
In industrial biotechnology, microbial cell factories utilize renewable resources to produce energy, materials and chemicals. Industrial biotechnology plays an increasingly important role in solving the resource, energy and environmental problems. Systems biology has shed new light on industrial biotechnology, deepening our understanding of industrial microbial cell factories and their bioprocess from "Black-box" to "White-box". Systems-wide profiling of genome, transcriptome, proteome, metabolome, and fluxome has proven valuable to better unveil network operation and regulation on the genome scale. System biology has been successfully applied to create microbial cell factories for numerous products and derive attractive industrial processes, which has constantly expedited the development of industrial biotechnology. This review focused on the recent advance and applications of omics and trans-omics in industrial biotechnology, including genomics, transcriptomics, proteomics, metabolomics, fluxomics and genome scale modeling, and so on. Furthermore, this review also discussed the potential and promise of systems biology in industrial biotechnology.
Topics: Biotechnology; Genomics; Industrial Microbiology; Metabolic Engineering; Metabolomics; Systems Biology
PubMed: 31668041
DOI: 10.13345/j.cjb.190217 -
Current Medicinal Chemistry 2016Traditional technologies using reductionist approach are relatively insufficient to solve problems in a biological system. Rather than a reductionist approach, systems... (Review)
Review
Traditional technologies using reductionist approach are relatively insufficient to solve problems in a biological system. Rather than a reductionist approach, systems biology uses a holistic and integrative approach to better figure out the whole process. Both qualitatively and quantitatively of biological system provide information about diseases, toxicities, therapies etc. Omics technologies, which systems biology brings, are valuable tools for comprehensive analyses. Automated DNA sequencers enabled the sequencing of genomes; microarray and mass spectrometry analysis permit global transcriptional profiling and lead to large-scale proteomic and metabolomics analysis. These high-throughput data need to be interpreted by bioinformatics. So far there has been no concrete published paper that compiles omics technologies according to PubMed database. In the present review, it was aimed to give brief description of systems biology and information on the advantages and disadvantages of omics technologies.
Topics: Chromatography, High Pressure Liquid; Gene Expression; Genomics; Mass Spectrometry; Metabolomics; Oligonucleotide Array Sequence Analysis; Proteomics; Systems Biology
PubMed: 27686657
DOI: 10.2174/0929867323666160926150617 -
EMBO Reports Jun 2004Biology's various affairs with holism and reductionism, and their contribution to understanding life at the molecular level (Review)
Review
Biology's various affairs with holism and reductionism, and their contribution to understanding life at the molecular level
Topics: History, 19th Century; History, 20th Century; Macromolecular Substances; Models, Biological; Molecular Biology; Probability
PubMed: 15170468
DOI: 10.1038/sj.embor.7400180 -
Nature Reviews. Cardiology May 2021Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems... (Review)
Review
Omics techniques generate large, multidimensional data that are amenable to analysis by new informatics approaches alongside conventional statistical methods. Systems theories, including network analysis and machine learning, are well placed for analysing these data but must be applied with an understanding of the relevant biological and computational theories. Through applying these techniques to omics data, systems biology addresses the problems posed by the complex organization of biological processes. In this Review, we describe the techniques and sources of omics data, outline network theory, and highlight exemplars of novel approaches that combine gene regulatory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics techniques to provide new insights into cardiovascular disease. The use of systems approaches will become necessary to integrate data from more than one omic technique. Although understanding the interactions between different omics data requires increasingly complex concepts and methods, we argue that hypothesis-driven investigations and independent validation must still accompany these novel systems biology approaches to realize their full potential.
Topics: Cardiovascular Diseases; Computational Biology; Gene Regulatory Networks; Genomics; Humans; Lipidomics; Machine Learning; Metabolomics; Neural Networks, Computer; Proteomics; Systems Biology
PubMed: 33340009
DOI: 10.1038/s41569-020-00477-1 -
Hereditas Nov 2020The founders of Hereditas envisioned that race biology would be a major subject that had social applications with utmost importance in the near future. Anthropometrics... (Review)
Review
BACKGROUND
The founders of Hereditas envisioned that race biology would be a major subject that had social applications with utmost importance in the near future. Anthropometrics was in this context understood to be the pure and eugenics the applied science. Sweden had a long tradition in physical anthropometry. Herman Lundborg, member of the advisory board of Hereditas, united the anthropometric and eugenic approaches in a synthesis. He was the first head of the Institute for Race Biology in Sweden. The contents of Hereditas reflect the development of race biology in the Nordic countries.
CONCLUSIONS
The initial enthusiasm for applied race biology did not last long. In the 1920's Hereditas carried papers on both physical anthropology and eugenics. Most paper dealt, however, with human genetics without eugenic content. Two papers, published in 1921 and 1939 show how the intellectual climate had changed from positive to negative. Finally only human genetics prevailed as the legitimate study of the human race or humankind. A belated defense of eugenics published in 1951 did not help; geneticists had abandoned anthropometrics for good around the year 1940 and eugenics about a decade later. In spite of that, eugenic legislation was amended astonishingly late, in the 1970's. The development was essentially similar in all Nordic countries.
Topics: Anthropometry; Biology; Breeding; Eugenics; Genetic Association Studies; Genetics, Population; History, 20th Century; Human Genetics; Humans; Plant Breeding; Racial Groups; Scandinavian and Nordic Countries
PubMed: 33239087
DOI: 10.1186/s41065-020-00161-x -
Advances in Experimental Medicine and... 2018Systems biology is an approach to collect high-dimensional data and analyze in an integrated manner. As aging is a complicated physiological functional decline in... (Review)
Review
Systems biology is an approach to collect high-dimensional data and analyze in an integrated manner. As aging is a complicated physiological functional decline in biological system, the methods in systems biology could be utilized in aging studies. Here we reviewed recent advances in systems biology in aging research and divide them into two major parts. One is the data resource, which includes omics data from DNA, RNA, proteins, epigenetic changes, metabolisms, and recently single-cell-level variations. The other is the data analysis methods consisting of network and modeling approaches. With all the data and the tools to analyze them, we could further promote our understanding of the systematic aging.
Topics: Aging; Computational Biology; Data Analysis; Epigenesis, Genetic; Genomics; Humans; Proteomics; Research; Systems Biology
PubMed: 30232749
DOI: 10.1007/978-981-13-1117-8_1 -
Proteomics Feb 2021
Topics: Computational Biology; Genomics; Metabolomics; Systems Biology
PubMed: 33543584
DOI: 10.1002/pmic.202000306 -
Advances in Protein Chemistry and... 2021A cell integrates various signals through a network of biomolecules that crosstalk to synergistically regulate the replication, transcription, translation and other... (Review)
Review
A cell integrates various signals through a network of biomolecules that crosstalk to synergistically regulate the replication, transcription, translation and other metabolic activities of a cell. These networks regulate signal perception and processing that drives biological functions. The biological complexity cannot be fully captured by a single -omics discipline. The holistic study of an organism-in health, perturbation, exposure to environment and disease, is studied under systems biology. The bottom-up molecular approaches (genes, mRNA, protein, metabolite, etc.) have laid the foundation of current biological knowledge covering the horizon from viruses, bacteria, fungi, plants and animals. Yet, these techniques provide a rather myopic view of biology at the molecular level. To understand how the interconnected molecular components are formed and rewired in disease or exposure to environmental stimuli is the holy grail of modern biology. The omics era was heralded by the genomics revolution but advanced sequencing techniques are now also ubiquitous in transcriptomics, proteomics, metabolomics and lipidomics. Multi-omics data analysis and integration techniques are driving the quest for deeper insights into how the different layers of biomolecules talk to each other in diverse contexts.
Topics: Animals; Big Data; Genomics; Humans; Metabolomics; Proteomics; Systems Biology
PubMed: 34340766
DOI: 10.1016/bs.apcsb.2021.03.006 -
Archives of Microbiology Sep 2016Existing at the interface of science and engineering, synthetic biology represents a new and emerging field of mainstream biology. However, there also exists a... (Review)
Review
Existing at the interface of science and engineering, synthetic biology represents a new and emerging field of mainstream biology. However, there also exists a counterculture of Do-It-Yourself biologists, citizen scientists, who have made significant inroads, particularly in the design and development of new tools and techniques. Herein, I review the development and convergence of synthetic biology's mainstream and countercultures.
Topics: Biomedical Research; Biotechnology; Containment of Biohazards; Humans; Synthetic Biology
PubMed: 27316777
DOI: 10.1007/s00203-016-1257-x -
Proteomics Sep 2020Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data... (Review)
Review
Omic technologies have enabled the complete readout of the molecular state of a cell at different biological scales. In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach. Here, genome-scale models (GEMs) are focused upon as one computational systems biology approach for interpreting and integrating multi-omic data. GEMs convert the reactions (related to metabolism, transcription, and translation) that occur in an organism to a mathematical formulation that can be modeled using optimization principles. A variety of genome-scale modeling methods used to interpret multiple omic data types, including genomics, transcriptomics, proteomics, metabolomics, and meta-omics are reviewed. The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering. The authors find that concurrent with advancements in omic technologies, genome-scale modeling methods are also expanding to enable better interpretation of omic data. Therefore, continued synthesis of valuable knowledge, through the integration of omic data with GEMs, are expected.
Topics: Computational Biology; Genome; Genomics; Humans; Metabolomics; Proteomics; Systems Biology
PubMed: 32579720
DOI: 10.1002/pmic.201900282