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Poxvirus bioinformatics resource Center:: a comprehensive Poxviridae informational and analytical resource

NUCLEIC ACIDS RESEARCH 2005年第Database issue期33卷 D311-D316页

作者： Lefkowitz, EJ Upton, C Changayil, SS Buck, C Traktman, P Buller, RML Univ Alabama Dept Microbiol Birmingham AL 35294 USA Univ Victoria Dept Biochem & Microbiol Victoria BC V8W 2Y2 Canada ATCC Virol Collect Manassas VA 20108 USA Med Coll Wisconsin Dept Microbiol & Mol Genet Milwaukee WI 53226 USA St Louis Univ Ctr Hlth Sci Dept Mol Microbiol & Immunol St Louis MO 63104 USA

The Poxvirus bioinformatics resource Center (PBRC) has been established to provide informational and analytical resources to the scientific community to aid research directed at providing a better understanding of the Poxviridae family of viruses. The PBRC was specifically established as the result of the concern that variola virus, the causative agent of smallpox, as well as related viruses, might be utilized as biological weapons. In addition, the PBRC supports research on poxviruses that might be considered new and emerging infectious agents such as monkeypox virus. The PBRC consists of a relational database and web application that supports the data storage, annotation, analysis and information exchange goals of the project. The current release consists of over 35 complete genomic sequences of various genera, species and strains of viruses from the Poxviridae family. Sequence and annotation information for these viruses has been obtained from sequences publicly available from GenBank as well as sequences not yet deposited in GenBank that have been obtained from ongoing sequencing projects. In addition to sequence data, the PBRC provides comprehensive annotation and curation of virus genes;analytical tools to aid in the understanding of the available sequence data, including tools for the comparative analysis of different virus isolates;and visualization tools to help better display the results of various analyses. The PBRC represents the initial development of what will become a more comprehensive Viral bioinformatics resource Center for Biodefense that will be one of the National Institute of Allergy and Infectious Diseases' 'bioinformatics resource Centers for Biodefense and Emerging or Re-Emerging Infectious Diseases'. The PBRC website is available at http://***.

关键词： .Poxvirus bioinformatics resource Poxviridae PBRC

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ThalInd, a β-Thalassemia and Hemoglobinopathies Database for India: Defining a Model Country-Specific and Disease-Centric bioinformatics resource

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HUMAN MUTATION 2011年第8期32卷 887-893页

作者： Sinha, Sujata Black, Michael L. Agarwal, Sarita Das, Reena Bittles, Alan H. Bellgard, Matthew Murdoch Univ Ctr Comparat Genom Perth WA 6150 Australia Sanjay Gandhi Postgrad Inst Med Sci Lucknow Uttar Pradesh India Thalassemia Working Grp Varanasi Uttar Pradesh India Postgrad Inst Med Educ & Res Chandigarh 160012 India Edith Cowan Univ Perth WA Australia

Web-based informatics resources for genetic disorders have evolved from genome-wide databases like OMIM and HGMD to Locus Specific databases (LSDBs) and National and Ethnic Mutation Databases (NEMDBs). However, with the increasing amenability of genetic disorders to diagnosis and better management, many previously underreported conditions are emerging as disorders of public health significance. In turn, the greater emphasis on noncommunicable disorders has generated a demand for comprehensive and relevant disease-based information from end-users, including clinicians, patients, genetic epidemiologists, health administrators and policymakers. To accommodate these demands, country-specific and disease-centric resources are required to complement the existing LSDBs and NEMDBs. Currently available preconfigured Web-based software applications can be customized for this purpose. The present article describes the formulation and construction of a Web-based informatics resource for beta-thalassemia and other hemoglobinopathies, initially for use in India, a multiethnic, multireligious country with a population approaching 1,200 million. The resource ThalInd (http://***/thalind) has been created using the LOVD system, an open source platform-independent database system. The system has been customized to incorporate and accommodate data pertinent to molecular genetics, population genetics, genotype-phenotype correlations, disease burden, and infrastructural assessment. Importantly, the resource also has been aligned with the administrative health system and demographic resources of the country. Hum Mutat 32:887-893, 2011. (C) 2011 Wiley-Liss, Inc.

关键词： bioinformatics resource database beta-thalassemia hemoglobinopathies India ThalInd

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BIRI: a new approach for automatically discovering and indexing available public bioinformatics resources from the literature

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BMC bioinformatics 2009年第1期10卷 320-320页

作者： de la Calle, Guillermo Garcia-Remesal, Miguel Chiesa, Stefano de la Iglesia, Diana Maojo, Victor Univ Politecn Madrid Fac Informat Dept Inteligencia Artificial E-28660 Madrid Spain

Background: The rapid evolution of Internet technologies and the collaborative approaches that dominate the field have stimulated the development of numerous bioinformatics resources. To address this new framework, several initiatives have tried to organize these services and resources. In this paper, we present the bioinformatics resource Inventory (BIRI), a new approach for automatically discovering and indexing available public bioinformatics resources using information extracted from the scientific literature. The index generated can be automatically updated by adding additional manuscripts describing new resources. We have developed web services and applications to test and validate our approach. It has not been designed to replace current indexes but to extend their capabilities with richer functionalities. Results: We developed a web service to provide a set of high-level query primitives to access the index. The web service can be used by third-party web services or web-based applications. To test the web service, we created a pilot web application to access a preliminary knowledge base of resources. We tested our tool using an initial set of 400 abstracts. Almost 90% of the resources described in the abstracts were correctly classified. More than 500 descriptions of functionalities were extracted. Conclusion: These experiments suggest the feasibility of our approach for automatically discovering and indexing current and future bioinformatics resources. Given the domain-independent characteristics of this tool, it is currently being applied by the authors in other areas, such as medical nanoinformatics. BIRI is available at http://***/biri/.

关键词： Target Domain Proper Noun bioinformatics resource Biomedical Ontology resource Category

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From single- to multi-omics: future research trends in medicinal plants

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BRIEFINGS IN bioinformatics 2023年第1期24卷 bbac485-bbac485页

作者： Yang, Lifang Yang, Ye Huang, Luqi Cui, Xiuming Liu, Yuan Kunming Univ Sci & Technol Kunming Peoples R China Chinese Acad Chinese Med Sci Beijing Peoples R China

Medicinal plants are the main source of natural metabolites with specialised pharmacological activities and have been widely examined by plant researchers. Numerous omics studies of medicinal plants have been performed to identify molecular markers of species and functional genes controlling key biological traits, as well as to understand biosynthetic pathways of bioactive metabolites and the regulatory mechanisms of environmental responses. Omics technologies have been widely applied to medicinal plants, including as taxonomies, transcriptomics, metabolomics, proteomics, genomics, pangenomics, epigenomics and mutagenomics. However, because of the complex biological regulation network, single omics usually fail to explain the specific biological phenomena. In recent years, reports of integrated multi-omics studies of medicinal plants have increased. Until now, there have few assessments of recent developments and upcoming trends in omics studies of medicinal plants. We highlight recent developments in omics research of medicinal plants, summarise the typical bioinformatics resources available for analysing omics datasets, and discuss related future directions and challenges. This information facilitates further studies of medicinal plants, refinement of current approaches and leads to new ideas.

关键词： medicinal plant single omics multi-omics analysis bioinformatics resource

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Non-coding RNA notations, regulations and interactive resources

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FUNCTIONAL & INTEGRATIVE GENOMICS 2024年第6期24卷 1-18页

作者： Cheng, Mengwei Zhu, Yinhuan Yu, Han Shao, Linlin Zhang, Yiming Li, Lanxing Tu, Haohong Xie, Luyao Chao, Haoyu Zhang, Peijing Xin, Saige Feng, Cong Ivanisenko, Vladimir Orlov, Yuriy Chen, Dijun Wong, Aloysius Yang, Yixin Eric Chen, Ming Wenzhou Kean Univ Coll Sci Math & Technol Wenzhou 325060 Peoples R China Univ Chinese Acad Sci Wenzhou Inst Wenzhou 325001 Peoples R China Zhejiang Univ Coll Life Sci Dept Bioinformat Hangzhou 310058 Peoples R China Russian Acad Sci Inst Cytol & Genet Siberian Branch Novosibirsk 630060 Russia IM Sechenov First Moscow State Med Univ Sechenov Univ Digital Hlth Inst Minist Hlth Russian Federat Moscow 119991 Russia Nanjing Univ Sch Life Sci Nanjing 210023 Peoples R China

An increasing number of non-coding RNAs (ncRNAs) are found to have roles in gene expression and cellular regulations. However, there are still a large number of ncRNAs whose functions remain to be studied. Despite decades of research, the field continues to evolve, with each newly identified ncRNA undergoing processes such as biogenesis, identification, and functional annotation. bioinformatics methodologies, alongside traditional biochemical experimental methods, have played an important role in advancing ncRNA research across various stages. Presently, over 50 types of ncRNAs have been characterized, each exhibiting diverse functions. However, there remains a need for standardization and integration of these ncRNAs within a unified framework. In response to this gap, this review traces the historical trajectory of ncRNA research and proposes a unified notation system. Additionally, we comprehensively elucidate the ncRNA interactome, detailing its associations with DNAs, RNAs, proteins, complexes, and chromatin. A web portal named ncRNA Hub (https://***/nchub/) is also constructed to provide detailed notations of ncRNAs and share a collection of bioinformatics resources. This review aims to provide a broader perspective and standardized paradigm for advancing ncRNA research.

关键词： Non-coding RNA Notation Interactome bioinformatics resource

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Reconstructing the virulome of the human pathogen Streptococcus pyogenes using NMPDR subsystems-based annotation

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BMC bioinformatics 2009年第SUPPL 7期10卷 A7-A7页

作者： Aziz, Ramy K. Mcneil, Leslie K. Cairo Univ Fac Pharm Dept Microbiol & Immunol Cairo Egypt Univ Chicago Computat Inst Chicago IL 60637 USA Univ Illinois Natl Ctr Supercomp Applicat Urbana IL 61801 USA

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Two's twice as useful

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Genome Biology 2001年第5期2卷 1-4页

作者： Weitzman, Jonathan B.

关键词： Human Genome Human Genome Project Human Genome Sequence bioinformatics resource 15mer Sequence

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Classification of the glyphosate target enzyme (5-enolpyruvylshikimate-3-phosphate synthase) for assessing sensitivity of organisms to the herbicide

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JOURNAL OF HAZARDOUS MATERIALS 2021年 408卷 124556-124556页

作者： Leino, Lyydia Tall, Tuomas Helander, Marjo Saloniemi, Irma Saikkonen, Kari Ruuskanen, Suvi Puigbo, Pere Univ Turku Dept Biol Turku Finland Univ Turku Biodivers Unit Turku Finland Eurecat Technol Ctr Catalonia Nutr & Hlth Unit Reus Catalonia Spain Rovira & Virgili Univ Dept Biochem & Biotechnol Tarragona Catalonia Spain

Glyphosate is the most common broad-spectrum herbicide. It targets the key enzyme of the shikimate pathway, 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS), which synthesizes three essential aromatic amino acids (phenylalanine, tyrosine and tryptophan) in plants. Because the shikimate pathway is also found in many prokaryotes and fungi, the widespread use of glyphosate may have unsuspected impacts on the diversity and composition of microbial communities, including the human gut microbiome. Here, we introduce the first bioinformatics method to assess the potential sensitivity of organisms to glyphosate based on the type of EPSPS enzyme. We have precomputed a dataset of EPSPS sequences from thousands of species that will be an invaluable resource to advancing the research field. This novel methodology can classify sequences from nearly 90% of eukaryotes and >80% of prokaryotes. A conservative estimate from our results shows that 54% of species in the core human gut microbiome are sensitive to glyphosate.

关键词： Shikimate pathway Epsps enzyme Glyphosate Herbicide Resistance Microbiome bioinformatics resource Biomarkers Sensitivity

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Identifier mapping performance for integrating transcriptomics and proteomics experimental results

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BMC bioinformatics 2011年第1期12卷 1-14页

作者： Day, Roger S. McDade, Kevin K. Chandran, Uma R. Lisovich, Alex Conrads, Thomas P. Hood, Brian L. Kolli, V. S. Kumar Kirchner, David Litzi, Traci Maxwell, G. Larry Univ Pittsburgh Sch Med Dept Biomed Informat Pittsburgh PA 15261 USA Univ Pittsburgh Dept Biostat Pittsburgh PA 15260 USA Inova Hlth Syst Womens Hlth Integrated Res Ctr Falls Church VA 22042 USA Windber Res Inst Windber PA 15963 USA Walter Reed Army Med Ctr Div Gynecol Oncol Washington DC 20307 USA

Background: Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit. Results: We compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed. Conclusions: The methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging.

关键词： Application Programming Interface Spectral Count Mapping resource bioinformatics resource Annotation resource

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CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline

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BMC GENOMICS 2017年第1期18卷 332-332页

作者： Agrawal, Sonia Arze, Cesar Adkins, Ricky S. Crabtree, Jonathan Riley, David Vangala, Mahesh Galens, Kevin Fraser, Claire M. Tettelin, Herve White, Owen Angiuoli, Samuel V. Mahurkar, Anup Fricke, W. Florian Inst Genome Sci Baltimore MD 21201 USA Univ Maryland Sch Med Dept Microbiol & Immunol Baltimore MD 21201 USA Univ Maryland Sch Med Dept Epidemiol Baltimore MD 21201 USA Univ Hohenheim Dept Nutrigen Stuttgart Germany

Background: The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. Results: CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up-and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. Conclusions: CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

关键词： Comparative genomics Microbial genomics Automated analysis Whole-genome alignment bioinformatics resource Virtual machine Cloud computing

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