Investigation of molecular mechanisms of human disorders, especially rare diseases, require exploration of various knowledge repositories for building precise hypotheses and complex data interpretation. Recently, increasingly more resources offer diagrammatic representation of such mechanisms, including disease-dedicated schematics in pathway databases and disease maps. However, collection of knowledge across them is challenging, especially for research projects with limited manpower.
View Article and Find Full Text PDFProtein function is often interpreted using molecular interaction diagrams, encoding roles a given protein plays in various molecular mechanisms. Information about disease-related mechanisms can be inferred from disease maps, knowledge repositories containing manually constructed systems biology diagrams. Disease maps hosted on the Molecular Interaction Network VisuAlization (MINERVA) Platform are individually accessible through a REST API interface of each instance, making it challenging to systematically explore their contents.
View Article and Find Full Text PDFObjective: Facilitate the multi-appointment scheduling problems (MASPs) characteristic of longitudinal clinical research studies. Additional goals include: reducing management time, optimizing clinical resources, and securing personally identifiable information.
Materials And Methods: Following a model view controller architecture, we developed a web-based tool written in Python 3.
We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources.
View Article and Find Full Text PDFSummary: The complexity of molecular networks makes them difficult to navigate and interpret, creating a need for specialized software. MINERVA is a web platform for visualization, exploration and management of molecular networks. Here, we introduce an extension to MINERVA architecture that greatly facilitates the access and use of the stored molecular network data.
View Article and Find Full Text PDFAs urban atmosphere is depleted of (13)CO2, its imprint should be detectable in the local vegetation and therefore in its CO2 respiratory emissions. This work was aimed at characterising strength and isotope signature of CO2 fluxes from soil in urban areas with varying distances from anthropogenic CO2 emissions. The soil CO2 flux and its δ(13)C isotope signature were measured using a chamber method on a monthly basis from July 2009 to May 2012 within the metropolitan area of Krakow, Southern Poland, at two locations representing different levels of anthropogenic influence: a lawn adjacent to a busy street (A) and an urban meadow (B).
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