In the digital age of cardiovascular medicine, the rate of biomedical discovery can be greatly accelerated by the guidance and resources required to unearth potential collections of knowledge. A unified computational platform leverages metadata to not only provide direction but also empower researchers to mine a wealth of biomedical information and forge novel mechanistic insights. This review takes the opportunity to present an overview of the cloud-based computational environment, including the functional roles of metadata, the architecture schema of indexing and search, and the practical scenarios of machine learning-supported molecular signature extraction. By introducing several established resources and state-of-the-art workflows, we share with our readers a broadly defined informatics framework to phenotype cardiovascular health and disease.
Understanding the complex involvement of mitochondrial biology in disease development often requires the acquisition, analysis, and integration of large-scale molecular and phenotypic data. An increasing number of bioinformatics tools are currently employed to aid in mitochondrial investigations, most notably in predicting or corroborating the spatial and temporal dynamics of mitochondrial molecules, in retrieving structural data of mitochondrial components, and in aggregating as well as transforming mitochondrial centric biomedical knowledge. With the increasing prevalence of complex Big Data from omics experiments and clinical cohorts, informatics tools have become indispensable in our quest to understand mitochondrial physiology and pathology. Here we present an overview of the various informatics resources that are helping researchers explore this vital organelle and gain insights into its form, function, and dynamics.
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