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Species included in PlantTFDB 4.0 covers the main lineages of green plants. Therefore, PlantTFDB provides genomic TF repertoires across Viridiplantae. To provide comprehensive information for the TF family, a brief introduction and key references are presented for each family. Comprehensive annotations are made for each identified TF, including functional domains, 3D structures, gene ontology (GO), plant ontology (PO), expression information, expert-curated functional description, regulation information, interaction, conserved elements, references, and annotations in various databases such as UniProt, RefSeq, TransFac, STRING, and VISTA. By inferring orthologous groups and constructing phylogenetic trees, evolutionary relationships among identified TFs were inferred. In addition, PlantTFDB has a simple and user-friendly interface to allow users to query based on combined conditions or make sequence similarity search using BLAST. The new version PlantTFDB 5.0 has been incorporated into PlantRegMap http://plantregmap.gao-lab.org/.
The Mikulski Archive for Space Telescopes (MAST) is a NASA funded project to support and provide to the astronomical community a variety of astronomical data archives, with the primary focus on scientifically related data sets in the optical, ultraviolet, and near-infrared parts of the spectrum. MAST is located at the Space Telescope Science Institute (STScI).
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CRAN is a network of ftp and web servers around the world that store identical, up-to-date, versions of code and documentation for R. R is ‘GNU S’, a freely available language and environment for statistical computing and graphics which provides a wide variety of statistical and graphical techniques: linear and nonlinear modelling, statistical tests, time series analysis, classification, clustering, etc. Please consult the R project homepage for further information.
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms. It is used by students, educators, and researchers all over the world as a primary source of machine learning data sets. As an indication of the impact of the archive, it has been cited over 1000 times.