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Bioinformatics and Applications in Biotechnology
Published in Ram Chandra, R.C. Sobti, Microbes for Sustainable Development and Bioremediation, 2019
Once the genome has been sequenced and assembled properly, it needs annotation for identification of genes, mobile genetic elements, repeats, genome duplication, and diversity. Similarity search tools such as BLAST are used to identify obvious homologs, and more sophisticated tools such as GLIMMER (Gene Locator and Interpolated Markov ModelER), GENSCAN, and Artemis are some of the tools widely used for genome annotation. GLIMMER uses interpolated Markov models for microbial gene identification (Salzberg et al., 1998). The encyclopedia of DNA elements (ENCODE) project of National Human Genome Research Institute aims to identify all functional elements in human genome. Since only 1.5% of the genomic DNA is recognized as coding region, the role of the remaining component is not clear. The project aims to identify and fully characterize the regulome, which controls gene expression, and the findings will have major impact on understanding of the disease. Various bioinformatics tools are extensively used in the project to analyze and store the data so that it become useful during subsequent uses. A major outcome of the project is the FactorBook repository, which houses the database of more than 100 different transcription factors and their recognition sites in genomic DNA.
Biological Data Mining:
Published in Wahiba Ben Abdessalem Karaa, Nilanjan Dey, Mining Multimedia Documents, 2017
Amira S. Ashour, Nilanjan Dey, Dac-Nhuong Le
The development of data mining methods is an active research area in bioinformatics to solve biological data analysis problems [4]. There are several biological data analysis types, including protein structure prediction, cancer classification, gene classification, and protein structure prediction, which are based on gene expression data analysis clustering, microarray data analysis, and protein–protein interaction statistical modeling. The observations for labeling the regulatory elements and genes locations on each chromosome is essential in order to represent the datasets for the entire genomes of DNA sequence. Through bioinformatics, sequence analysis and genome annotation can be performed. Several bioinformatics techniques are incorporated for sequence analysis to define the biological function as well as the proteins code. In addition, genome annotation identifies the genes locations and the coding regions for understanding the species’ genome.
Metabolic modeling of synthetic microbial communities for bioremediation
Published in Critical Reviews in Environmental Science and Technology, 2023
Lvjing Wang, Xiaoyu Wang, Hao Wu, Haixia Wang, Yihan Wang, Zhenmei Lu
The generic process of GEM reconstruction can be summarized as follows (Figure 3) (Bernstein et al., 2021; Thiele & Palsson, 2010). (1) Genome annotation. Genome annotation information can be obtained from public knowledge bases, and sequenced genomes can be annotated by RAST (the Rapid Annotation using Subsystems Technology) (Overbeek et al., 2014) or Prokka (Seemann, 2014). (2) Draft reconstruction. Draft models can be built by automatic GEM reconstruction programs (Table 1). Nutrients are generally defined by medium and culture conditions, and secretions can be detected by mass spectrometry. (3) Biomass composition determination. Biomass objective functions can be generated from the literature or experimental data (Lachance et al., 2019; Simensen et al., 2022). (4) Network gap-filling. Gap-filling requires algorithms to identify dead-end metabolites and choked reactions and is based on universal databases and the available curated models that are phylogenetically closest to the organisms of interest. (5) Model evaluation. The accuracy of the model can be validated by comparing in vitro phenotype data and in silico prediction, and the quality of the model can be evaluated by using alternative model testing toolboxes (Jensen et al., 2020), such as MEMOTE, short for metabolic model testing (Lieven et al., 2020). (6) Flux simulation. When model reconstruction and refinement are finished, flux simulation is carried out (Table 2). For instance, the final model can be used to simulate whole-cell metabolic fluxes in a given environmental condition at steady state using flux balance analysis (FBA) (Orth et al., 2010).