AGCDA. Artículos de Investigación

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Examinando AGCDA. Artículos de Investigación por Autor "Biomol"

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  • Publicación
    Acceso abierto
    Determinación de marcadores moleculares para la hepatitis B, mediante secuenciación profunda del genoma viral y la expresión de miARNs en muestras obtenidas de bancos de sangre en Colombia
    (Universidad de Antioquia, 2021-06-29) Rueda-Forero, Nora Juliana; Bedoya, Astrid; Goyeneche-Patiño, Diego A.; Biomol
    La hepatitis B (HB), enfermedad producida por el Virus de la hepatitis B (VHB), se ha establecido como un problema de salud pública mundial. Entender con mayor detalle la interacción entre el virus y el huésped mediante el análisis profundo del genoma del VHB y el análisis de la expresión de micro ARNs (miARNs) permitirá abordar la complejidad y diversidad de la infección, generando posibles marcadores moleculares importantes en la detección, definición de fenotipos clínicos o tratamiento de la enfermedad. Con el fin de abordar este objetivo, el análisis genómico mediante secuenciación profunda de las poblaciones virales identificadas en las muestras, así como la caracterización de los miARN presentes en individuos, soportados en estrategias de secuenciación de próxima generación, permitirá desarrollar por primera vez un estudio que evidencie la diversidad viral, las mutaciones sub representadas para los genotipos F, A y la respuesta generada a la infección viral.
  • Publicación
    Acceso abierto
    Generation of Cry11 Variants of Bacillus thuringiensis by Heuristic Computational Modeling
    (2020-07-27) Pinzón-Reyes, Efraín Hernando; Sierra-Bueno, Daniel Alfonso; Suarez-Barrera, Miguel Orlando; Rueda-Forero, Nohora Juliana; Biomol
    Directed evolution methods mimic in vitro Darwinian evolution, inducing random mutations and selective pressure in genes to obtain proteins with enhanced characteristics. These techniques are developed using trial-and-error testing at an experimental level with a high degree of uncertainty. Therefore, in silico modeling of directed evolution is required to support experimental assays. Several in silico approaches have reproduced directed evolution, using statistical, thermodynamic, and kinetic models in an attempt to recreate experimental conditions. Likewise, optimization techniques using heuristic models have been used to understand and find the best scenarios of directed evolution. Our study uses an in silico model named HeurIstics DirecteD EvolutioN, which is based on a genetic algorithm designed to generate chimeric libraries from 2 parental genes, cry11Aa and cry11Ba, of Bacillus thuringiensis. These genes encode crystal-shaped δ-endotoxins with 3 conserved domains. Cry11 toxins are of biotechnological interest because they have shown to be effective as biopesticides for disease-spreading vectors. With our heuristic model, we considered experimental parameters such as DNA fragmentation length, number of generations or simulation cycles, and mutation rate, to get characteristics of Cry11 chimeric libraries such as percentage of population identity, truncation of variants obtained from the presence of internal stop codons, percentage of thermodynamic diversity, and stability of variants. Our study allowed us to focus on experimental conditions that may be useful for the design of in vitro and in silico experiments of directed evolution with Cry toxins of 3 conserved domains. Furthermore, we obtained in silico libraries of Cry11 variants, in which structural characteristics of wild Cry families were observed in a review of a sample of in silico sequences. We consider that future studies could use our in silico libraries and heuristic computational models, as the one suggested here, to support in vitro experiments of directed evolution.