2018
DOI: 10.1186/s12864-018-5194-8
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Colombia, an unknown genetic diversity in the era of Big Data

Abstract: BackgroundLatin America harbors some of the most biodiverse countries in the world, including Colombia. Despite the increasing use of cutting-edge technologies in genomics and bioinformatics in several biological science fields around the world, the region has fallen behind in the inclusion of these approaches in biodiversity studies. In this study, we used data mining methods to search in four main public databases of genetic sequences such as: NCBI Nucleotide and BioProject, Pathosystems Resource Integration… Show more

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Cited by 19 publications
(20 citation statements)
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“…The discovery of hidden information is achieved by running data mining algorithms that combine statistics with computer science to mine valuable information from a seemingly meaningless data jumble. Data mining can be applied in various fields such as engineering (Adekitan et al., 2019; Saini and Aggarwal, 2018), business management (Zuo et al., 2016), marketing and product design (Jin et al., 2019), computer science (Mahendra et al., 2019), education (Ibrahim et al., 2019; Porouhan, 2018), genetics (Noreña et al., 2018), biological studies (Gu et al., 2018), facility maintenance management (Miguel-Cruz et al., 2019), health and drug development studies (Keserci et al., 2017), chemistry and toxicity analysis (Saini and Srivastava, 2019), meteorology (Kovalchuk et al., 2019), transportation safety (Divya et al., 2019) and traffic management (Amiruzzaman, 2019), fraud detection (Vardhani et al., 2019), and so forth. In the educational sector, volumes of data are daily generated from various teaching and learning activities within an institution.…”
Section: Introductionmentioning
confidence: 99%
“…The discovery of hidden information is achieved by running data mining algorithms that combine statistics with computer science to mine valuable information from a seemingly meaningless data jumble. Data mining can be applied in various fields such as engineering (Adekitan et al., 2019; Saini and Aggarwal, 2018), business management (Zuo et al., 2016), marketing and product design (Jin et al., 2019), computer science (Mahendra et al., 2019), education (Ibrahim et al., 2019; Porouhan, 2018), genetics (Noreña et al., 2018), biological studies (Gu et al., 2018), facility maintenance management (Miguel-Cruz et al., 2019), health and drug development studies (Keserci et al., 2017), chemistry and toxicity analysis (Saini and Srivastava, 2019), meteorology (Kovalchuk et al., 2019), transportation safety (Divya et al., 2019) and traffic management (Amiruzzaman, 2019), fraud detection (Vardhani et al., 2019), and so forth. In the educational sector, volumes of data are daily generated from various teaching and learning activities within an institution.…”
Section: Introductionmentioning
confidence: 99%
“…Species identification efforts have drastically being influenced by the use of molecular data acting as a complement to taxonomic information obtained from morphology alone (Camargo & Sites, 2013; Carstens et al, 2013; Luo, Ling, Ho, & Zhu, 2018); however, the availability of molecular datasets (genes or genomes) is still restricted to particular biotic groups, while many others—in which high diversity occurs—lack proper molecular information, hindering the ability of addressing evolutionary questions, biogeographic hypothesis, and accurate species delimitation and identification (Helmy, Awad, & Mosa, 2016; Noreña, González Muñoz, Mosquera‐Rendón, Botero, & Cristancho, 2018). Traditional barcoding approaches have proven useful for species identification (Barco, Raupach, Laakmann, Neumann, & Knebelsberger, 2016; Hebert, Ratnasingham, et al, 2003), but they are not suitable for certain taxa lacking reference genomes or specific primers for PCR amplification when universal primers do not work as expected (Ford et al, 2009; Moulton, Song, & Whiting, 2010; Pino‐Bodas, Martín, Burgaz, & Lumbsch, 2013).…”
Section: Discussionmentioning
confidence: 99%
“…However, there is still a long way to go, 29 especially in Latin America, where this type of technology is underdeveloped in the areas of natural sciences and health. [30][31][32] Even with the benefits they offer, these techniques have limitations, including the lack of quality standards and validation methods for some of their records, as they may be incomplete, inconsistent, and subject to a great deal of potential bias and confusion. On the other hand, the use of massive amounts of data may cause an existing relationship to go undetected due to the masking or dilution of a phenomenon.…”
Section: Big Data In the Health Areamentioning
confidence: 99%