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Stem cell paracrine activity is implicated in cardiac repair. Linkage between secretome functionality and therapeutic outcome was here interrogated by systems analytics of biobanked human cardiopoietic cells, a regenerative biologic in advanced clinical trials. Protein chip array identified 155 proteins differentially secreted by cardiopoietic cells with clinical benefit, expanded into a 520 node network, collectively revealing inherent vasculogenic properties along with cardiac and smooth muscle differentiation and development. Next generation RNA sequencing, refined by pathway analysis, pinpointed miR-146 dependent regulation upstream of the decoded secretome. Intracellular and extracellular integration unmasked commonality across cardio-vasculogenic processes. Mirroring the secretome pattern, infarcted hearts benefiting from cardiopoietic cell therapy restored the disease proteome engaging cardiovascular system functions. The cardiopoietic cell secretome thus confers a therapeutic molecular imprint on recipient hearts, with response informed by predictive systems profiling.
Pubmed ID: 34047493 RIS Download
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Web user interface for visualizing clustering of multivariate data. Web server allows users to upload their own data and create Principal Component Analysis plots and heatmaps.
View all literature mentionsThe Biological Networks Gene Ontology tool (BiNGO) is an open-source Java tool to determine which Gene Ontology (GO) terms are significantly overrepresented in a set of genes. BiNGO can be used either on a list of genes, pasted as text, or interactively on subgraphs of biological networks visualized in Cytoscape. BiNGO maps the predominant functional themes of the tested gene set on the GO hierarchy, and takes advantage of Cytoscape''''s versatile visualization environment to produce an intuitive and customizable visual representation of the results. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
View all literature mentionsA web-based software application that enables users to analyze, integrate, and understand data derived from gene expression, microRNA, and SNP microarrays, metabolomics, proteomics, and RNA-Seq experiments, and small-scale experiments that generate gene and chemical lists. Users can search for targeted information on genes, proteins, chemicals, and drugs, and build interactive models of experimental systems. IPA allows exploration of molecular, chemical, gene, protein and miRNA interactions, creation of custom molecular pathways, and the ability to view and modify metabolic, signaling, and toxicological canonical pathways. In addition to the networks and pathways that can be created, IPA can provide multiple layering of additional information, such as drugs, disease genes, expression data, cellular functions and processes, or a researchers own genes or chemicals of interest.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
View all literature mentionsA quantitative proteomics software package for analyzing large-scale mass-spectrometric data sets. It is a set of algorithms that include peak detection and scoring of peptides, mass calibration, database searches for protein identification, protein quantification, and provides summary statistics.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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