Integration of “omics” Data and Phenotypic Data Within a Unified Extensible Multimodal Framework

Analysis of “omics” data is often a long and segmented process, encompassing multiple stages from initial data collection to processing, quality control and visualization. The cross-modal nature of recent genomic analyses renders this process challenging to both automate and standardize; consequently, users often resort to manual interventions that compromise data reliability and reproducibility. This in turn can produce multiple versions of datasets across storage systems. As a result, scientists can lose significant time and resources trying to execute and monitor their analytical workflows and encounter difficulties sharing versioned data. In 2015, the Ludmer Centre for Neuroinformatics and Mental Health at McGill University brought together expertise from the Douglas Mental Health University Institute, the Lady Davis Institute and the Montreal Neurological Institute (MNI) to form a genetics/epigenetics working group. The objectives of this working group are to: (i) design an automated and seamless process for (epi)genetic data that consolidates heterogeneous datasets into the LORIS open-source data platform; (ii) streamline data analysis; (iii) integrate results with provenance information; and (iv) facilitate structured and versioned sharing of pipelines for optimized reproducibility using high-performance computing (HPC) environments via the CBRAIN processing portal. This article outlines the resulting generalizable “omics” framework and its benefits, specifically, the ability to: (i) integrate multiple types of biological and multi-modal datasets (imaging, clinical, demographics and behavioral); (ii) automate the process of launching analysis pipelines on HPC platforms; (iii) remove the bioinformatic barriers that are inherent to this process; (iv) ensure standardization and transparent sharing of processing pipelines to improve computational consistency; (v) store results in a queryable web interface; (vi) offer visualization tools to better view the data; and (vii) provide the mechanisms to ensure usability and reproducibility. This framework for workflows facilitates brain research discovery by reducing human error through automation of analysis pipelines and seamless linking of multimodal data, allowing investigators to focus on research instead of data handling

Soporte al proceso de análisis e interpretación de variantes genéticas en Exoma humano

El avance de las ciencias médicas en especial de la bioinformática, la genética y el diagnóstico genético han traído grandes cambios en los tratamientos de las enfermedades y por ende en nuestra calidad de vida. De esto surge la necesidad de proveer a los médicos de herramientas informáticas cada vez más complejas en apoyo al trabajo con los pacientes y sus familiares. En esta tesis se plantean los escenarios llevados a cabo, por el médico Genetista, para ejecutar el proceso de análisis e interpretación de variantes genéticas, a través de un Exoma Humano, que llevan a la detección y diagnóstico de enfermedades monogénicas en un paciente. Para tal fin, se modela el proceso de toma de decisiones y los distintos escenarios, la trazabilidad en la ejecución de los filtros de las variantes presentadas, se muestra cómo se arriba a un diagnóstico, cómo se retroalimenta un panel bioinformático, que cumplirá la función de base de datos propia, y también cómo se retroalimetan los diagnósticos futuros. Se especifican los requerimientos y se propone una solución en base a la construcción de un prototipo que cumple con todo lo requerido. Finalmente, se valida dicha solución con un médico genetista y se arriba a las conclusiones.Magister en Ingeniería de SoftwareUniversidad Nacional de La PlataFacultad de Informátic

Approaches for rejuvenating the natural product discovery process from Streptomyces

In 1940, a bacterial enzyme was identified which was capable of destroying penicillin (Abraham & Chain, 1940). This discovery actually predated both the awarding of the Nobel Peace Prize in Medicine and Physiology for its discovery and the year it became available over the counter for the first time in the United States by five years (Gaynes, 2017). In short, Antimicrobial Resistance (AMR) is a phenomenon that has long plagued the field of natural product drug discovery. To attempt to overcome come this, it is imperative that the natural product discovery field is shunted forward by the continued advancement of microbial culturing methods and analytical tools (Atanasov et al., 2021). This work contributes towards the rejuvenation of natural product drug discovery by describing new methods for eliciting potentially novel antimicrobial specialised metabolites, as well as outlining metabologenomic methods for analysing the resultant datasets. [See thesis text for references].In 1940, a bacterial enzyme was identified which was capable of destroying penicillin (Abraham & Chain, 1940). This discovery actually predated both the awarding of the Nobel Peace Prize in Medicine and Physiology for its discovery and the year it became available over the counter for the first time in the United States by five years (Gaynes, 2017). In short, Antimicrobial Resistance (AMR) is a phenomenon that has long plagued the field of natural product drug discovery. To attempt to overcome come this, it is imperative that the natural product discovery field is shunted forward by the continued advancement of microbial culturing methods and analytical tools (Atanasov et al., 2021). This work contributes towards the rejuvenation of natural product drug discovery by describing new methods for eliciting potentially novel antimicrobial specialised metabolites, as well as outlining metabologenomic methods for analysing the resultant datasets. [See thesis text for references]