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      The Effects of a Mixture of Cadmium, Lead, and Mercury on Metabolic Syndrome and Its Components, as well as Cognitive Impairment: Genes, MicroRNAs, Transcription Factors, and Sponge Relationships : The Effects of a Mixture of Cadmium, Lead, and Mercury on Metabolic Syndrome and Its Components, as well as Cognitive Impairment: Genes, MicroRNAs, Transcription Factors, and Sponge Relationships

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      Biological Trace Element Research
      Springer Science and Business Media LLC

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          Metascape provides a biologist-oriented resource for the analysis of systems-level datasets

          A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets. Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results. Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists. In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal. Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments. Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs. Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
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            The GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function

            GeneMANIA (http://www.genemania.org) is a flexible, user-friendly web interface for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query list, GeneMANIA extends the list with functionally similar genes that it identifies using available genomics and proteomics data. GeneMANIA also reports weights that indicate the predictive value of each selected data set for the query. Six organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Homo sapiens and Saccharomyces cerevisiae) and hundreds of data sets have been collected from GEO, BioGRID, Pathway Commons and I2D, as well as organism-specific functional genomics data sets. Users can select arbitrary subsets of the data sets associated with an organism to perform their analyses and can upload their own data sets to analyze. The GeneMANIA algorithm performs as well or better than other gene function prediction methods on yeast and mouse benchmarks. The high accuracy of the GeneMANIA prediction algorithm, an intuitive user interface and large database make GeneMANIA a useful tool for any biologist.
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              Inflammation as a central mechanism in Alzheimer's disease

              Alzheimer's disease (AD) is a progressive neurodegenerative disorder that is characterized by cognitive decline and the presence of two core pathologies, amyloid β plaques and neurofibrillary tangles. Over the last decade, the presence of a sustained immune response in the brain has emerged as a third core pathology in AD. The sustained activation of the brain's resident macrophages (microglia) and other immune cells has been demonstrated to exacerbate both amyloid and tau pathology and may serve as a link in the pathogenesis of the disorder. In the following review, we provide an overview of inflammation in AD and a detailed coverage of a number of microglia-related signaling mechanisms that have been implicated in AD. Additional information on microglia signaling and a number of cytokines in AD are also reviewed. We also review the potential connection of risk factors for AD and how they may be related to inflammatory mechanisms.
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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Biological Trace Element Research
                Biol Trace Elem Res
                Springer Science and Business Media LLC
                0163-4984
                1559-0720
                May 2023
                July 07 2022
                May 2023
                : 201
                : 5
                : 2200-2221
                Article
                10.1007/s12011-022-03343-y
                dafa702f-fcd3-46e7-81e0-78c0a2e2d5e2
                © 2023

                https://www.springernature.com/gp/researchers/text-and-data-mining

                https://www.springernature.com/gp/researchers/text-and-data-mining

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