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- UniHI 7: an enhanced database for retrieval and interactive analysis of human molecular interaction networksPublication . Kalathur, Ravi Kiran Reddy; Pinto, Jose Pedro; Hernandez-Prieto, Miguel A.; Machado, Rui; Almeida, Dulce; Chaurasia, Gautam; Futschik, Matthias E.Unified Human Interactome (UniHI) (http://www.unihi.org) is a database for retrieval, analysis and visualization of human molecular interaction networks. Its primary aim is to provide a comprehensive and easy-to-use platform for network-based investigations to a wide community of researchers in biology and medicine. Here, we describe a major update (version 7) of the database previously featured in NAR Database Issue. UniHI 7 currently includes almost 350 000 molecular interactions between genes, proteins and drugs, as well as numerous other types of data such as gene expression and functional annotation. Multiple options for interactive filtering and highlighting of proteins can be employed to obtain more reliable and specific network structures. Expression and other genomic data can be uploaded by the user to examine local network structures. Additional built-in tools enable ready identification of known drug targets, as well as of biological processes, phenotypes and pathways enriched with network proteins. A distinctive feature of UniHI 7 is its user-friendly interface designed to be utilized in an intuitive manner, enabling researchers less acquainted with network analysis to perform state-of-the-art network-based investigations.
- StemMapper: a curated gene expression database for stem cell lineage analysisPublication . Pinto, Jose P.; Machado, Rui S. R.; Magno, Ramiro; Oliveira, Daniel V.; Machado, Susana; Andrade, Raquel P.; Braganca, Jose; Duarte, Isabel; Futschik, Matthias E.Transcriptomic data have become a fundamental resource for stem cell (SC) biologists as well as for a wider research audience studying SC-related processes such as aging, embryonic development and prevalent diseases including cancer, diabetes and neurodegenerative diseases. Access and analysis of the growing amount of freely available transcriptomics datasets for SCs, however, are not trivial tasks. Here, we present StemMapper, a manually curated gene expression database and comprehensive resource for SC research, built on integrated data for different lineages of human and mouse SCs. It is based on careful selection, standardized processing and stringent quality control of relevant transcriptomics datasets to minimize artefacts, and includes currently over 960 transcriptomes covering a broad range of SC types. Each of the integrated datasets was individually inspected andmanually curated. StemMapper's user-friendly interface enables fast querying, comparison, and interactive visualization of quality-controlled SC gene expression data in a comprehensive manner. A proof-of-principle analysis discovering novel putative astrocyte/neural SC lineage markers exemplifies the utility of the integrated data resource. We believe that StemMapper can open the way for new insights and advances in SC research by greatly simplifying the access and analysis of SC transcriptomic data.