Curator Dashboard

It contains the genotype, phenotype, and polymorphism data produced by the NSF-funded project; Genetic Architecture of Maize and Teosinte. The PANZEA project will identify genes that control domestication traits and three key agronomic traits: flowering time, plant height, and kernel quality. Genetic linkage, association, and fine mapping analyses will be performed on the largest and most diverse set of mapping families publicly available for any species. A large series of isogenic lines will be used to characterize allelic series and epistatic interactions. The genetic architecture of each of the four trait groups will be compared and contrasted, and the influence of recombination and past domestication bottlenecks on the genomic distribution of functional diversity will be examined. Finally, the ability of genetic architecture-based models to predict phenotype will be evaluated in a broad range of germplasm, including elite US hybrids. This project will take a step toward the ultimate goal of predicting phenotype from genotype.

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• SciCrunch
• 17 years ago - by Anonymous

It provides structure based sequence alignments for homologous proteins of known 3-D structure. The alignments available include those of pairwise (two proteins at a time) and multiple (simultaneous superposition of all the structures in a family). The database also provides dendrograms depicting phylogentic relationships based on sequence and structural similarities. The present version of the database consists of 1922 protein families containing over 13,500 protein domains, more than 2,00,000 structural alignments and over 1400 orphansorphans (single member families). PALI (version 2.7) has been derived largely from SCOP 1.73 database. The pairwise superpositions were performed using DALI by Holm and Sander while superposition of multiple structures has been performed using MUSTANG ver.3 by Konagurthu et.al. and the structural similarities are assessed using the metrices defined by Johnson and Levitt & Gerstein.

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• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 17, 2013. A collection of protein sequences and the BLAST and PSI-BLAST alignments between them. Instead of running BLAST or PSI-BLAST individually, results can be retrieved from a database of pre-computed alignments. PairsDB is continually updated and we aim to be as comprehensive as possible.

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• SciCrunch
• 17 years ago - by Anonymous

It has made an effort to collect known PAIs and to detect the potential PAI regions in the prokaryotic complete genomes. PAIDB was developed and maintained by Genome Encyclopedia of Microbes (GEM) at Korea Research Institute of Bioscience and Biotechnology (KRIBB) in Korea. Previously, we have developed a computational method for identifying PAIs in sequenced genomes by combining a homology-based method and detection of abnormalities in genomic composition.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE documented June 5, 2013 Proteome Analyst (PA) is a publicly available, high-throughput, web-based system for predicting various properties of each protein in an entire proteome. Using machine-learned classifiers, PA can predict, for example, the GeneQuiz general function and Gene Ontology (GO) molecular function of a protein. In addition, PA is currently the most accurate and most comprehensive system for predicting subcellular localization, the location within a cell where a protein performs its main function. Two other capabilities of PA are notable. First, PA can create a custom classifier to predict a new property, without requiring any programming, based on labeled training data (i.e. a set of examples, each with the correct classification label) provided by a user. PA has been used to create custom classifiers for potassium-ion channel proteins and other general function ontologies. Second, PA provides a sophisticated explanation feature that shows why one prediction is chosen over another. The PA system produces a Naïve Bayes classifier, which is amenable to a graphical and interactive approach to explanations for its predictions; transparent predictions increase the user's confidence in, and understanding of, PA.

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• SciCrunch
• 17 years ago - by Anonymous

It was established with an overall objective to provide a resource of protein phosphorylation data from multiple plants. P3DB was constructed with a dataset from oilseed rape. The data was obtained using a combination of data-dependent neutral loss and multistage activation mass spectrometry. The dataset includes 14,670 non-redundant phosphorylation sites from 8,894 phospho-peptides in 6,382 substrate proteins.

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• SciCrunch
• 17 years ago - by Anonymous

A comprehensive rice science database established in 2000 by rice researcher''s committee in Japan. The database is originally aimed to gather as much knowledge as possible ranging from classical rice genetics to recent genomics and from fundamental information to hot topics. The Oryzabase consists of five parts, (1) genetic resource stock information, (2) gene dictionary, (3) chromosome maps, (4) mutant images, and (5) fundamental knowledge of rice science. We are planning to do more extensive cross-referencing of Oryzabase to the major DNA sequence database, literature database and other plant databases in order to provide the wealth of information to rice researchers. We are calling for additional mutants and mapped gene information to incorporate into the Oryzabase. Newly identified mutants and mapped trait genes published in the scientific journals will be welcome to integrate into the Oryzabase maps.

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• SciCrunch
• 17 years ago - by Anonymous

OrthoMCL is a genome-scale algorithm for grouping orthologous protein sequences. It provides not only groups shared by two or more species/genomes, but also groups representing species-specific gene expansion families. OrthoMCL starts with reciprocal best hits within each genome as putative in-paralog/recent paralog pairs and reciprocal best hits across any two genomes as putative ortholog pairs. Related proteins are interlinked in a similarity graph. Then MCL (Markov Clustering algorithm,Van Dongen 2000; www.micans.org/mcl) is invoked to split mega-clusters. This process is analogous to the manual review in COG construction. MCL clustering is based on weights between each pair of proteins, so to correct for differences in evolutionary distance the weights are normalized before running MCL.

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• SciCrunch
• 17 years ago - by Anonymous

Curated sequence data and related information on organelles from NCBI Refseq for the community to use as a standard. The animal mitochondrial records are considered reviewed; that is, they have been manually curated by the NCBI staff. Other mitochondrial and chloroplast genome records are provisional and are presented with varying levels of review compared to the primary record used to build the RefSeq. Additionally, protein clusters for the metazoan and plastid genomes proteins can be reviewed with Entrez Protein Clusters.

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• SciCrunch
• 17 years ago - by Anonymous

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.

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• SciCrunch
• 17 years ago - by Anonymous

ORENZA is a relational database of Orphan Enzyme Activities. ORENZA provides an accurate and up to date list of Enzyme Activities for which no sequences are available in the main sequence protein databases. Orphan enzyme activities correpond to the enzyme activities (EC numbers) defined by the Nomenclature Committee of the International Union of Biochemistry and Molecular Biology (NC-IUBMB), and which are not associated with any amino acid sequences in the major public databases.

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• SciCrunch
• 17 years ago - by Anonymous

Open source, open access database and literature curation system for community based annotation of experimentally identified DNA regulatory regions, transcription factor binding sites and regulatory variants. Automatically cross referenced against PubMED, Entrez Gene, EnsEMBL, dbSNP, eVOC: Cell type ontology, and Taxonomy database. Community driven resource for curated regulatory annotation.

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• SciCrunch
• 17 years ago - by Anonymous

Oncomine Research Platform is a partially-commercial suite of products for online cancer gene expression analysis dedicated to the academic and non-profit research community. Oncomine combines a rapidly growing compendium of 20,000+ cancer transcriptome profiles with a sophisticated analysis engine and a powerful web application for data-mining and visualization. Oncomine facilitates rapid and reliable biomarker and therapeutic target discovery, validation and prioritization. Oncomine was developed by physicians, scientists, and software engineers at the University of Michigan and is now fully supported for the academic and non-profit research community by Compendia Bioscience.

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• 17 years ago - by Anonymous

Spanish higher education institution, located in the city of Salamanca, west of Madrid, in the autonomous community of Castile and León. It was founded in 1134 and given the Royal charter of foundation by King Alfonso IX in 1218.

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• SciCrunch
• 13 years ago - submitted by Andrea Stagg

Ontology for Solanaceae crop phenotypes and traits, developed in collaboration with the research community, especially for breeder traits of agronomic importance.

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• 13 years ago - by Anonymous

OncoDB.HCC is the first comprehensive oncogenomic database for HCC. It effectively integrates three datasets from public references to provide multi-dimension view of current HCC studies. The three datasets included are Chromosome aberration studies, Gene expression studies, and HCC model organisms (rats and mice).

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• SciCrunch
• 17 years ago - by Anonymous

Database of vertebrate olfactory receptors genes and proteins. It supports sequencing and analysis of these receptors by providing a comprehensive archive with search tools for this expanding family. The database also incorporates a broad range of chemosensory genes and proteins, including the taste papilla receptors (TPRs), vomeronasal organ receptors (VNRs), insect olfaction receptors (IORs), Caenorhabditis elegans chemosensory receptors (CeCRs), and fungal pheromone receptors (FPRs). ORDB currently houses chemosensory receptors for more than 50 organisms. ORDB contains public and private sections which provide tools for investigators to analyze the functions of these very large gene families of G protein-coupled receptors. It also provides links to a local cluster of databases of related information in SenseLab, and to other relevant databases worldwide. The database aims to house all of the known olfactory receptor and chemoreceptor sequences in both nucleotide and amino acid form and serves four main purposes: * It is a repository of olfactory receptor sequences. * It provides tools for sequence analysis. * It supports similarity searches (screens) which reduces duplicate work. * It provides links to other types of receptor information, e.g. 3D models. The database is accessible to two classes of users: * General public www users have full access to all the public sequences, models and resources in the database. * Source laboratories are the laboratories that clone olfactory receptors and submit sequences in the private or public database. They can search any sequence they deposited to the database against any private or public sequence in the database. This user level is suited for laboratories that are actively cloning olfactory receptors.

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• SciCrunch
• 17 years ago - by Anonymous

OGRe is a searchable relational database which currently contains the complete mitochondrial genome sequences of 1244 metazoan organisms. In addition to gene sequences, OGRe also contains information on gene order and codon usage., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

The Oomycete Genomics Database is a publicly accessible resource that includes functional assays and expression data, combined with transcript and genomic analysis and annotation. OGD builds upon data available from the Phytophthora Genome Consortium, Syngenta Phytophthora Consortium and the Phytophthora Functional Genomics Database. Data are analyzed and annotated using NCGR''s XGI System. The knowledge gained from these studies provide significant insight into key molecular processes regulating an economically important pathosystem and will provide novel tools for improvement of disease resistance in crop plants.

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• SciCrunch
• 17 years ago - by Anonymous

ODB (Operon DataBase) aims to collect known operons in multiple species and to offer a system to predict operons by user definitions. All the known operons are derived from the literature and from publicly available database including operon information. This system provides candidates of operons based on the conditions that users choice and also provide its prediction accuracy. This database integrates both known literature-based operons and as well as operon prediction, to provide a useful system for bioinformatics researchers and experimental biologists.

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• SciCrunch
• 17 years ago - by Anonymous