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http://www.athamap.de/

Genome wide map of putative transcription factor binding sites in Arabidopsis thaliana genome.Data in AthaMap is based on published transcription factor (TF) binding specificities available as alignment matrices or experimentally determined single binding sites.Integrated transcriptional and post transcriptional data.Provides web tools for analysis and identification of co-regulated genes. Provides web tools for database assisted identification of combinatorial cis-regulatory elements and the display of highly conserved transcription factor binding sites in Arabidopsis thaliana.

Proper citation: AthaMap (RRID:SCR_006717) Copy   

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http://metacrop.ipk-gatersleben.de

Database that summarizes diverse information about metabolic pathways in crop plants and allows automatic export of information for the creation of detailed metabolic models. It contains manually curated, highly detailed information about metabolic pathways in crop plants, including pathway diagrams, reactions, locations, transport processes, reaction kinetics, taxonomy and literature. It contains information about seven major crop plants with high agronomical importance and two model plants.

Proper citation: MetaCrop (RRID:SCR_003100) Copy   

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http://gpcr.biocomp.unibo.it/esldb

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 22,2022. database of protein subcellular localization annotation for eukaryotic organisms. It contains experimental annotations derived from primary protein databases, homology based annotations and computational predictions.

Proper citation: eSLDB - eukaryotic Subcellular Localization database (RRID:SCR_000052) Copy   

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http://caps.ncbs.res.in/stifdb2/

Database of biotic and abiotic stress responsive genes in Arabidopsis thaliana and Oryza sativa L. with options to identify probable Transcription Factor Binding Sites in their promoters. In the response to biotic stress like Bacteria and abiotic stresses like ABA, drought, cold, salinity, dehydration, UV-B, high light, heat,heavy metals etc, ten specific families of transcription factors in Arabidopsis thaliana and six in Oryza sativa L. are known to be involved. HMM-based models are used to identify binding sites of transcription factors belonging to these families. They have also consulted literature reports to cross-validate the Transcription Factor Binding Sites predicted by the method.

Proper citation: STIFDB (RRID:SCR_002131) Copy   

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http://wikipathways.org/

Open and collaborative platform dedicated to curation of biological pathways. Each pathway has dedicated wiki page, displaying current diagram, description, references, download options, version history, and component gene and protein lists. Database of biological pathways maintained by and for scientific community.

Proper citation: WikiPathways (RRID:SCR_002134) Copy   

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http://zope.bioinfo.cnio.es/plan2l/plan2l.html

A web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. The system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned.

Proper citation: PLAN2L (RRID:SCR_013346) Copy   

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http://rarge.psc.riken.jp/rartf/

Database of complete sets of Arabidopsis transcription factors with a variety of information on Arabidopsis thaliana transcription factor families including: full-length cDNA sequences, Ds-tagged mutants, multiple sequences alignments of family members, phylogenic trees, functional motifs, and so on. In addition, expression profiles of all transcription factor genes are available.

Proper citation: RARTF (RRID:SCR_013457) Copy   

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https://github.com/lucventurini/mikado/

Mikado is a lightweight Python3 pipeline whose purpose is to facilitate the identification of expressed loci from RNA-Seq data * and to select the best models in each locus.

Proper citation: Mikado (RRID:SCR_016159) Copy   

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http://dnatraffic.ibb.waw.pl/

DNAtraffic database is dedicated to be an unique comprehensive and richly annotated database of genome dynamics during the cell life. DNAtraffic contains extensive data on the nomenclature, ontology, structure and function of proteins related to control of the DNA integrity mechanisms such as chromatin remodeling, DNA repair and damage response pathways from eight model organisms commonly used in the DNA-related study: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli and Arabidopsis thaliana. DNAtraffic contains comprehensive information on diseases related to the assembled human proteins. Database is richly annotated in the systemic information on the nomenclature, chemistry and structure of the DNA damage and drugs targeting nucleic acids and/or proteins involved in the maintenance of genome stability. One of the DNAtraffic database aim is to create the first platform of the combinatorial complexity of DNA metabolism pathway analysis. Database includes illustrations of pathway, damage, protein and drug. Since DNAtraffic is designed to cover a broad spectrum of scientific disciplines it has to be extensively linked to numerous external data sources. Database represents the result of the manual annotation work aimed at making the DNAtraffic database much more useful for a wide range of systems biology applications. DNAtraffic database is freely available and can be queried by the name of DNA network process, DNA damage, protein, disease, and drug.

Proper citation: DNAtraffic (RRID:SCR_008886) Copy   

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http://bpg.utoledo.edu/~afedorov/lab/eid.html

Data sets of protein-coding intron-containing genes that contain gene information from humans, mice, rats, and other eukaryotes, as well as genes from species whose genomes have not been completely sequenced. This is a comprehensive and convenient dataset of sequences for computational biologists who study exon-intron gene structures and pre-mRNA splicing. The database is derived from GenBank release 112, and it contains protein-coding genes that harbor introns, along with extensive descriptions of each gene and its DNA and protein sequences, as well as splice motif information. They have created subdatabases of genes whose intron positions have been experimentally determined. The collection also contains data on untranslated regions of gene sequences and intron-less genes. For species with entirely sequenced genomes, species-specific databases have been generated. A novel Mammalian Orthologous Intron Database (MOID) has been introduced which includes the full set of introns that come from orthologous genes that have the same positions relative to the reading frames.

Proper citation: EID: Exon-Intron Database (RRID:SCR_002469) Copy   

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http://aafc-aac.usask.ca/fst/

Population of almost 50,000 activation tagged Arabidopsis thaliana lines that have been archived as individual lines to the T3 generation. The population is an excellent tool for both reverse and forward genetic screens and has been used successfully to identify a number of novel mutants. Flanking sequence tags (FST) have been generated and mapped for 15,507 lines to enable further application of the population, while providing a clear distribution of T-DNA insertions across the genome. The population is being screened for a number of biochemical and developmental phenotypes. The population provides an additional tool for plant researcher's to assist with determining gene function for the many as yet uncharacterized genes annotated within the Arabidopsis genome sequence. The presence of enhancer elements on the inserted T-DNA element (pSKI015) allows both knock-out and dominant activation phenotypes to be identified for traits of interest.

Proper citation: Saskatoon Arabidopsis T-DNA mutant population SK Collection (RRID:SCR_004939) Copy   

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http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

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http://ahd.cbi.pku.edu.cn

Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.

Proper citation: Arabidopsis Hormone Database (RRID:SCR_001792) Copy   

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http://www.plantgdb.org/AtGDB/

Database providing a sequence-centered genome view for Arabidopsis thaliana, with a narrow focus on gene structure annotation. The current genome assembly displayed at AtGDB is version TAIR9. Annotated gene models are TAIR10. They have mapped the complete set of 176,915 publicly available Arabidopsis EST sequences onto the Arabidopsis genome using GeneSeqer, a spliced alignment program incorporating sequence similarity and splice site scoring. About 96% of the available ESTs could be properly aligned with a genomic locus, with the remaining ESTs deriving from organelle genomes and non-Arabidopsis sources or displaying insufficient sequence quality for alignment. The mapping provides verified sets of EST clusters for evaluation of EST clustering programs. Analysis of the spliced alignments suggests corrections to current gene structure annotation and provides examples of alternative and non-canonical pre-mRNA splicing.

Proper citation: Arabidopsis thaliana Genome Database (RRID:SCR_001901) Copy   

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http://biodev.extra.cea.fr/interoporc/

Automatic prediction tool to infer protein-protein interaction networks, it is applicable for lots of species using orthology and known interactions. The interoPORC method is based on the interolog concept and combines source interaction datasets from public databases as well as clusters of orthologous proteins (PORC) available on Integr8. Users can use this page to ask InteroPorc for all species present in Integr8. Some results are already computed and users can run InteroPorc to investigate any other species. Currently, the following databases are processed and merged (with datetime of the last available public release for each database used): IntAct, MINT, DIP, and Integr8.

Proper citation: InteroPorc (RRID:SCR_002067) Copy   

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http://www.megabionet.org/atpid/webfile/

Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.

Proper citation: Arabidopsis thaliana Protein Interactome Database (RRID:SCR_001896) Copy   

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http://comgen.pl/mirex/

mirEX is a comprehensive platform for comparative analysis of primary microRNA expression data. quantitative real-time PCR-based gene expression profiles are stored in a universal and expandable database scheme and wrapped by an intuitive user-friendly interface. A new way of accessing gene expression data in mirEX includes a simple mouse operated querying system and dynamic graphs for data mining analyses. In contrast to other publicly available databases, the mirEX interface allows a simultaneous comparison of expression levels between various microRNA genes in diverse organs and developmental stages. Currently, mirEX integrates information about the expression profile of 190 Arabidopsis thaliana pri-miRNAs in seven different developmental stages: seeds, seedlings and various organs of mature plants. Additionally, by providing RNA structural models, publicly available deep sequencing results, experimental procedure details and careful selection of auxiliary data in the form of web links, mirEX can function as a one-stop solution for Arabidopsis microRNA information. This database aims to be useful to anyone investigating the role of microRNAs in shaping plant development, organ formation and response to different biotic and abiotic stresses. To start exploring the database just press the "Browse Atlas" button or search for a particular microRNA record by typing at least two numbers from its ID in the window.

Proper citation: mirEX (RRID:SCR_006060) Copy   

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http://hannonlab.cshl.edu/index.html

The Hannon laboratory comprises a broad spectrum of programs in small RNA biology, mammalian genetics and genomics. We study RNAi and related pathways in a wide variety of organisms to extract common themes that define both the mechanisms by which small RNAs act and the biological processes which they impact. Currently, we focus on microRNAs, endogenous siRNAs and piRNAs and their roles in gene regulation, cancer biology, stem cell biology and in defense of the genome against transposons. In collaboration with Steve Elledge (Harvard) and Scott Lowe (CSHL), we develop genome-wide shRNA tools for RNAi-based genetics in mammalian cells, and we are now producing similar collections of artificial microRNAs for Arabidopsis with Detlef Weigel (MPI), Dick McCombie (CSHL) and Rob Martienssen (CSHL) as part of the 2010 project (see 2010.cshl.edu). Our genomic efforts include the application of RNAi-based genetic screens to cancer biology and stem cells. We also make heavy use of next generation sequencing methodologies for probing small RNA populations, in part as a member of the ENCODE consortium (with Tom Gingeras, CSHL). Finally, we develop (with Dick McCombie) and apply focal re-sequencing methods for identifying disease relevant mutations, for probing the epigenetic landscape and for the study of human evolution.

Proper citation: CSHL - Hannon Lab (RRID:SCR_005982) Copy   

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http://phosphat.uni-hohenheim.de/

Database containing information on Arabidopsis phosphorylation sites which were identified by mass spectrometry in large scale experiments from different research groups. Specific information on the peptide properties as well as on the experimental and analytical context is given. The PhosPhAt service has a built-in plant specific phosphorylation site predictor trained on the experimental dataset for Serine, threonine and tyrosine phosphorylation (pSer, pThr, pTyr). Protein sequences or Arabidopsis AGI gene identifier can be submitted to the predictor. Users and researchers are encouraged to assist in keeping the database current by submitting either published data or unpublished data (MS/MS data required).

Proper citation: PhosPhAt (RRID:SCR_003332) Copy   

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http://www.arabidopsis.org

Database of genetic and molecular biology data for the model higher plant Arabidopsis thaliana. Data available includes the complete genome sequence along with gene structure, gene product information, metabolism, gene expression, DNA and seed stocks, genome maps, genetic and physical markers, publications, and information about the Arabidopsis research community. Gene product function data is updated every two weeks from the latest published research literature and community data submissions. Gene structures are updated 1-2 times per year using computational and manual methods as well as community submissions of new and updated genes. TAIR also provides extensive linkouts from data pages to other Arabidopsis resources. The data can be searched, viewed and analyzed. Datasets can also be downloaded. Pages on news, job postings, conference announcements, Arabidopsis lab protocols, and useful links are provided.

Proper citation: TAIR (RRID:SCR_004618) Copy   

•   Source: SciCrunch Registry