共查询到20条相似文献,搜索用时 31 毫秒
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Rhee SY Beavis W Berardini TZ Chen G Dixon D Doyle A Garcia-Hernandez M Huala E Lander G Montoya M Miller N Mueller LA Mundodi S Reiser L Tacklind J Weems DC Wu Y Xu I Yoo D Yoon J Zhang P 《Nucleic acids research》2003,31(1):224-228
Arabidopsis thaliana is the most widely-studied plant today. The concerted efforts of over 11 000 researchers and 4000 organizations around the world are generating a rich diversity and quantity of information and materials. This information is made available through a comprehensive on-line resource called the Arabidopsis Information Resource (TAIR) (http://arabidopsis.org), which is accessible via commonly used web browsers and can be searched and downloaded in a number of ways. In the last two years, efforts have been focused on increasing data content and diversity, functionally annotating genes and gene products with controlled vocabularies, and improving data retrieval, analysis and visualization tools. New information include sequence polymorphisms including alleles, germplasms and phenotypes, Gene Ontology annotations, gene families, protein information, metabolic pathways, gene expression data from microarray experiments and seed and DNA stocks. New data visualization and analysis tools include SeqViewer, which interactively displays the genome from the whole chromosome down to 10 kb of nucleotide sequence and AraCyc, a metabolic pathway database and map tool that allows overlaying expression data onto the pathway diagrams. Finally, we have recently incorporated seed and DNA stock information from the Arabidopsis Biological Resource Center (ABRC) and implemented a shopping-cart style on-line ordering system. 相似文献
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SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu 相似文献
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Evangelos Pafilis Sune P. Frankild Lucia Fanini Sarah Faulwetter Christina Pavloudi Aikaterini Vasileiadou Christos Arvanitidis Lars Juhl Jensen 《PloS one》2013,8(6)
The exponential growth of the biomedical literature is making the need for efficient, accurate text-mining tools increasingly clear. The identification of named biological entities in text is a central and difficult task. We have developed an efficient algorithm and implementation of a dictionary-based approach to named entity recognition, which we here use to identify names of species and other taxa in text. The tool, SPECIES, is more than an order of magnitude faster and as accurate as existing tools. The precision and recall was assessed both on an existing gold-standard corpus and on a new corpus of 800 abstracts, which were manually annotated after the development of the tool. The corpus comprises abstracts from journals selected to represent many taxonomic groups, which gives insights into which types of organism names are hard to detect and which are easy. Finally, we have tagged organism names in the entire Medline database and developed a web resource, ORGANISMS, that makes the results accessible to the broad community of biologists. The SPECIES software is open source and can be downloaded from http://species.jensenlab.org along with dictionary files and the manually annotated gold-standard corpus. The ORGANISMS web resource can be found at http://organisms.jensenlab.org. 相似文献
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Andra Waagmeester Martina Kutmon Anders Riutta Ryan Miller Egon L. Willighagen Chris T. Evelo Alexander R. Pico 《PLoS computational biology》2016,12(6)
The diversity of online resources storing biological data in different formats provides a challenge for bioinformaticians to integrate and analyse their biological data. The semantic web provides a standard to facilitate knowledge integration using statements built as triples describing a relation between two objects. WikiPathways, an online collaborative pathway resource, is now available in the semantic web through a SPARQL endpoint at http://sparql.wikipathways.org. Having biological pathways in the semantic web allows rapid integration with data from other resources that contain information about elements present in pathways using SPARQL queries. In order to convert WikiPathways content into meaningful triples we developed two new vocabularies that capture the graphical representation and the pathway logic, respectively. Each gene, protein, and metabolite in a given pathway is defined with a standard set of identifiers to support linking to several other biological resources in the semantic web. WikiPathways triples were loaded into the Open PHACTS discovery platform and are available through its Web API (https://dev.openphacts.org/docs) to be used in various tools for drug development. We combined various semantic web resources with the newly converted WikiPathways content using a variety of SPARQL query types and third-party resources, such as the Open PHACTS API. The ability to use pathway information to form new links across diverse biological data highlights the utility of integrating WikiPathways in the semantic web. 相似文献
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Costanzo MC Crawford ME Hirschman JE Kranz JE Olsen P Robertson LS Skrzypek MS Braun BR Hopkins KL Kondu P Lengieza C Lew-Smith JE Tillberg M Garrels JI 《Nucleic acids research》2001,29(1):75-79
The BioKnowledge Library is a relational database and web site (http://www.proteome.com) composed of protein-specific information collected from the scientific literature. Each Protein Report on the web site summarizes and displays published information about a single protein, including its biochemical function, role in the cell and in the whole organism, localization, mutant phenotype and genetic interactions, regulation, domains and motifs, interactions with other proteins and other relevant data. This report describes four species-specific volumes of the BioKnowledge Library, concerned with the model organisms Saccharomyces cerevisiae (YPD), Schizosaccharomyces pombe (PombePD) and Caenorhabditis elegans (WormPD), and with the fungal pathogen Candida albicans (CalPD). Protein Reports of each species are unified in format, easily searchable and extensively cross-referenced between species. The relevance of these comprehensively curated resources to analysis of proteins in other species is discussed, and is illustrated by a survey of model organism proteins that have similarity to human proteins involved in disease. 相似文献
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Ana R. Cortázar Ana M. Aransay Manuel Alfaro José A. Oguiza José L. Lavín 《Amino acids》2014,46(2):471-473
The secretome (full set of secreted proteins) has been studied in multiple fungal genomes to elucidate the potential role of those protein collections involved in a number of metabolic processes from host infection to wood degradation. Being aminoacid composition a key factor to recognize secretory proteins, SECRETOOL comprises a group of web tools that enable secretome predictions out of aminoacid sequence files, up to complete fungal proteomes, in one step. SECRETOOL is freely available on the web at http://genomics.cicbiogune.es/SECRETOOL/Secretool.php. 相似文献
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Andreas Wilke Jared Bischof Travis Harrison Tom Brettin Mark D'Souza Wolfgang Gerlach Hunter Matthews Tobias Paczian Jared Wilkening Elizabeth M. Glass Narayan Desai Folker Meyer 《PLoS computational biology》2015,11(1)
Metagenomic sequencing has produced significant amounts of data in recent years. For example, as of summer 2013, MG-RAST has been used to annotate over 110,000 data sets totaling over 43 Terabases. With metagenomic sequencing finding even wider adoption in the scientific community, the existing web-based analysis tools and infrastructure in MG-RAST provide limited capability for data retrieval and analysis, such as comparative analysis between multiple data sets. Moreover, although the system provides many analysis tools, it is not comprehensive. By opening MG-RAST up via a web services API (application programmers interface) we have greatly expanded access to MG-RAST data, as well as provided a mechanism for the use of third-party analysis tools with MG-RAST data. This RESTful API makes all data and data objects created by the MG-RAST pipeline accessible as JSON objects. As part of the DOE Systems Biology Knowledgebase project (KBase, http://kbase.us) we have implemented a web services API for MG-RAST. This API complements the existing MG-RAST web interface and constitutes the basis of KBase''s microbial community capabilities. In addition, the API exposes a comprehensive collection of data to programmers. This API, which uses a RESTful (Representational State Transfer) implementation, is compatible with most programming environments and should be easy to use for end users and third parties. It provides comprehensive access to sequence data, quality control results, annotations, and many other data types. Where feasible, we have used standards to expose data and metadata. Code examples are provided in a number of languages both to show the versatility of the API and to provide a starting point for users. We present an API that exposes the data in MG-RAST for consumption by our users, greatly enhancing the utility of the MG-RAST service. 相似文献
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Midori A Harris Kim M Rutherford Jacqueline Hayles Antonia Lock Jürg Bhler Stephen G Oliver Juan Mata Valerie Wood 《Genetics》2022,220(4)
PomBase (www.pombase.org), the model organism database (MOD) for the fission yeast Schizosaccharomyces pombe, supports research within and beyond the S. pombe community by integrating and presenting genetic, molecular, and cell biological knowledge into intuitive displays and comprehensive data collections. With new content, novel query capabilities, and biologist-friendly data summaries and visualization, PomBase also drives innovation in the MOD community. 相似文献
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Tayyaba Yasmin Inayat Ur Rehman Adnan Ahmad Ansari Khurrum liaqat Muhammad Irfan khan 《Bioinformation》2012,8(25):1277-1279
The availability of genomic sequences of many organisms has opened new challenges in many aspects particularly in terms of
genome analysis. Sequence extraction is a vital step and many tools have been developed to solve this issue. These tools are
available publically but have limitations with reference to the sequence extraction, length of the sequence to be extracted, organism
specificity and lack of user friendly interface. We have developed a java based software package having three modules which can
be used independently or sequentially. The tool efficiently extracts sequences from large datasets with few simple steps. It can
efficiently extract multiple sequences of any desired length from a genome of any organism. The results are crosschecked by
published data.
Availability
URL 1: http://ww3.comsats.edu.pk/bio/ResearchProjects.aspxURL 2: http://ww3.comsats.edu.pk/bio/SequenceManeuverer.aspx 相似文献19.
High-throughput experiments, most significantly DNA microarrays, provide us with system-scale profiles. Connecting these data with existing biological networks poses a formidable challenge to uncover facts about a cell's proteome. Studies and tools with this purpose are limited to networks with simple structure, such as protein-protein interaction graphs, or do not go much beyond than simply displaying values on the network. We have built a microarray data analysis tool, named PATIKAmad, which can be used to associate microarray data with the pathway models in mechanistic detail, and provides facilities for visualization, clustering, querying, and navigation of biological graphs related with loaded microarray experiments. PATIKAmad is freely available to noncommercial users as a new module of PATIKAweb at http://web.patika.org. 相似文献
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