Examinando por Materia "DNA"

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    Ítem
    Gravitational topological quantum computation
    (SPRINGER, 2007-01-01) Velez, Mario; Ospina, Juan; Velez, Mario; Ospina, Juan; Universidad EAFIT. Departamento de Ciencias; Lógica y Computación
    A new model in topological quantum computing, named Gravitational Topological Quantum Computing (GTQC), is introduced as an alternative respect to the Anyonic Topological Quantum Computing and DNA Computing. In the new model the quantum computer is the quantum space-time itself and the corresponding quantum algorithms refer to the computation of topological invariants for knots, links and tangles. Some applications of GTQC in quantum complexity theory and computability theory are discussed, particularly it is conjectured that the Khovanov polynomial for knots and links is more hard than #P-hard; and that the homeomorphism problem, which is noncomputable, maybe can be computed after all via a hyper-computer based on GTQC. © Springer-Verlag Berlin Heidelberg 2007.
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    Molecular and morphological identification of Phylloderma stenops Peters, 1865 (Chiroptera, Phyllostomidae) and new records for Colombia
    (Centro de Referencia em Informacao Ambiental, 2019-01-01) Martínez-Cerón J.M.; Patiño-Castillo E.; Carvalho-Madrigal S.; Díaz-Nieto J.F.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Based on revisionary work of recently collected material in Colombian museums we confirm the presence of Phylloderma stenops Peters, 1865 in 6 new localities for the country, including the first record of the species in the dry lowlands of the northern Caribbean coast, and the increase by more than 800 m of the elevational range of the species in Colombia. DNA-barcoding confirmed our morphological identification, and supported a paraphyletic composition of the cis-Andean populations. Our records exemplify the little knowledge on the ecogeographic distribution of this species and provide further evidence to consider this as a widespread but rare species. © Martínez-Cerón et al.
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    Rapid mitochondrial genome sequencing based on Oxford Nanopore Sequencing and a proxy for vertebrate species identification
    (John Wiley and Sons Ltd, 2020-01-01) Franco-Sierra, N.D.; Díaz-Nieto, J.F.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Molecular information is crucial for species identification when facing challenging morphology-based specimen identifications. The use of DNA barcodes partially solves this problem, but in some cases when PCR is not an option (i.e., primers are not available, problems in reaction standardization), amplification-free approaches could be an optimal alternative. Recent advances in DNA sequencing, like the MinION device from Oxford Nanopore Technologies (ONT), allow to obtain genomic data with low laboratory and technical requirements, and at a relatively low cost. In this study, we explore ONT sequencing for molecular species identification from a total DNA sample obtained from a neotropical rodent and we also test the technology for complete mitochondrial genome reconstruction via genome skimming. We were able to obtain “de novo” the complete mitogenome of a specimen from the genus Melanomys (Cricetidae: Sigmodontinae) with average depth coverage of 78X using ONT-only data and by combining multiple assembly routines. Our pipeline for an automated species identification was able to identify the sample using unassembled sequence data (raw) in a reasonable computing time, which was substantially reduced when a priori information related to the organism identity was known. Our findings suggest ONT sequencing as a suitable candidate to solve species identification problems in metazoan nonmodel organisms and generate complete mtDNA datasets. © 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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    Redescription and phylogenetic position of Ctenomys dorsalis Thomas 1900, an enigmatic tuco tuco (Rodentia, Ctenomyidae) from the Paraguayan Chaco
    (De Gruyter, 2019-01-01) Londoño-Gaviria M.; Teta P.; Ríos S.D.; Patterson B.D.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Ctenomys dorsalis is known only from its type specimen, a female preserved as skin without skull (except for the upper incisors) from an imprecise locality in the "Northern Chaco of Paraguay". Here, we report additional individuals of this species housed, since the 1940s, at the Field Museum of Natural History (Chicago, USA). Based on these specimens, which fully match the original description of this rodent, we provide novel information regarding its phylogenetic position, external and cranial morphology, and distribution. The analysis of mtDNA sequences supports the distinctiveness of this taxon and suggests its placement within the boliviensis group of Ctenomys. Our study highlights once more the importance of museum collections as repositories of biodiversity. © 2018 Walter de Gruyter GmbH, Berlin/Boston 2018.
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    Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings
    (Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Ciencias Biológicas y Bioprocesos (CIBIOP)
    Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.
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    Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings
    (Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Departamento de Ciencias; Biodiversidad, Evolución y Conservación
    Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.
  • No hay miniatura disponible
    Ítem
    Unsupervised fuzzy binning of metagenomic sequence fragments on three-dimensional Barnes-Hut t-Stochastic Neighbor Embeddings
    (Institute of Electrical and Electronics Engineers Inc., 2018-01-01) Ariza-Jimenez L.; Quintero O.L.; Pinel N.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
    Shotgun metagenomic studies attempt to reconstruct population genome sequences from complex microbial communities. In some traditional genome demarcation approaches, high-dimensional sequence data are embedded into two-dimensional spaces and subsequently binned into candidate genomic populations. One such approach uses a combination of the Barnes-Hut approximation and the t -Stochastic Neighbor Embedding (BH-SNE) algorithm for dimensionality reduction of DNA sequence data pentamer profiles; and demarcation of groups based on Gaussian mixture models within humanimposed boundaries. We found that genome demarcation from three-dimensional BH-SNE embeddings consistently results in more accurate binnings than 2-D embeddings. We further addressed the lack of a priori population number information by developing an unsupervised binning approach based on the Subtractive and Fuzzy c-means (FCM) clustering algorithms combined with internal clustering validity indices. Lastly, we addressed the subject of shared membership of individual data objects in a mixed community by assigning a degree of membership to individual objects using the FCM algorithm, and discriminated between confidently binned and uncertain sequence data objects from the community for subsequent biological interpretation. The binning of metagenome sequence fragments according to thresholds in the degree of membership opens the door for the identification of horizontally transferred elements and other genomic regions of uncertain assignment in which biologically meaningful information resides. The reported approach improves the unsupervised genome demarcation of populations within complex communities, increases the confidence in the coherence of the binned elements, and enables the identification of evolutionary processes ignored in hard-binning approaches in shotgun metagenomic studies. © 2018 IEEE.