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An annotation database for chemicals of emerging concern in exposome research

ENVIRONMENT INTERNATIONAL 2021年 152卷 106511-106511页

作者： Meijer, Jeroen Lamoree, Marja Hamers, Timo Antignac, Jean-Philippe Hutinet, Sebastien Debrauwer, Laurent Covaci, Adrian Huber, Carolin Krauss, Martin Walker, Douglas, I Schymanski, Emma L. Vermeulen, Roel Vlaanderen, Jelle Univ Utrecht Inst Risk Assessment Sci IRAS Yalelaan 2 NL-3584 CM Utrecht Netherlands Vrije Univ Dept Environm & Hlth Amsterdam Netherlands LABERCA INRAE Oniris Nantes France Toulouse Univ Toxalim Res Ctr Food Toxicol INP Purpan ENVTINRAE Toulouse France INRAE Natl Infrastruct Metabol & Flux MetaboHUB Metatoul Axiom Platform Toulouse France Univ Antwerp Toxicol Ctr Antwerp Belgium UFZ Helmholtz Ctr Environm Res Dept Effect Directed Anal Leipzig Germany Icahn Sch Med Mt Sinai Dept Environm Med & Publ Hlth New York NY 10029 USA Univ Luxembourg Luxembourg Ctr Syst Biomed Luxembourg Luxembourg

Background: Chemicals of Emerging Concern (CECs) include a very wide group of chemicals that are suspected to be responsible for adverse effects on health, but for which very limited information is available. Chromato-graphic techniques coupled with high-resolution mass spectrometry (HRMS) can be used for non-targeted screening and detection of CECs, by using comprehensive annotation databases. Establishing a database focused on the annotation of CECs in human samples will provide new insight into the distribution and extent of exposures to a wide range of CECs in humans. Objectives: This study describes an approach for the aggregation and curation of an annotation database (CECscreen) for the identification of CECs in human biological samples. Methods: The approach consists of three main parts. First, CECs compound lists from various sources were aggregated and duplications and inorganic compounds were removed. Subsequently, the list was curated by standardization of structures to create "MS-ready"and "QSAR-ready" SMILES, as well as calculation of exact masses (monoisotopic and adducts) and molecular formulas. The second step included the simulation of Phase I metabolites. The third and final step included the calculation of QSAR predictions related to physicochemical properties, environmental fate, toxicity and Absorption, Distribution, Metabolism, Excretion (ADME) processes and the retrieval of information from the US EPA CompTox Chemicals Dashboard. Results: All CECscreen database and property files are publicly available (DOI: https://***/10.5281/zenodo. 3956586). In total, 145,284 entries were aggregated from various CECs data sources. After elimination of du-plicates and curation, the pipeline produced 70,397 unique "MS-ready" structures and 66,071 unique QSAR-ready structures, corresponding with 69,526 CAS numbers. Simulation of Phase I metabolites resulted in 306,279 unique metabolites. QSAR predictions could be performed for 64,684 of the QSAR-ready st

关键词： annotation database High-resolution mass spectrometry Chemicals of emerging concern Exposome research

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DAVID Knowledgebase: a gene-centered database integrating heterogeneous gene annotation resources to facilitate high-throughput gene functional analysis

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BMC BIOINFORMATICS 2007年第1期8卷 426-426页

作者： Sherman, Brad T. Huang, Da Wei Tan, Qina Guo, Yongjian Bour, Stephan Liu, David Stephens, Robert Baseler, Michael W. Lane, H. Clifford Lempicki, Richard A. NCI Lab Immunopathogenesis & Bioinformat Clin Serv Program SAIC Frederick Inc Frederick MD 21702 USA NIAID Immunoregulat Lab NIH Bethesda MD 20892 USA NCI Adv Biomed Comp Ctr SAIC Frederick Inc Frederick MD 21702 USA NIAID Bioinformat & Sci IT Program NIAID Off Technol Informat Syst NIH Bethesda MD 20892 USA

Background: Due to the complex and distributed nature of biological research, our current biological knowledge is spread over many redundant annotation databases maintained by many independent groups. Analysts usually need to visit many of these bioinformatics databases in order to integrate comprehensive annotation information for their genes, which becomes one of the bottlenecks, particularly for the analytic task associated with a large gene list. Thus, a highly centralized and ready-to-use gene-annotation knowledgebase is in demand for high throughput gene functional analysis. Description: The DAVID Knowledgebase is built around the DAVID Gene Concept, a single-linkage method to agglomerate tens of millions of gene/protein identifiers from a variety of public genomic resources into DAVID gene clusters. The grouping of such identifiers improves the cross-reference capability, particularly across NCBI and UniProt systems, enabling more than 40 publicly available functional annotation sources to be comprehensively integrated and centralized by the DAVID gene clusters. The simple, pair-wise, text format files which make up the DAVID Knowledgebase are freely downloadable for various data analysis uses. In addition, a well organized web interface allows users to query different types of heterogeneous annotations in a high-throughput manner. Conclusion: The DAVID Knowledgebase is designed to facilitate high throughput gene functional analysis. For a given gene list, it not only provides the quick accessibility to a wide range of heterogeneous annotation data in a centralized location, but also enriches the level of biological information for an individual gene. Moreover, the entire DAVID Knowledgebase is freely downloadable or searchable at http://***/knowledgebase/.

关键词： Gene Identifier annotation database annotation Content annotation Resource Gene Functional annotation

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Learning smoothing models of copy number profiles using breakpoint annotations

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BMC BIOINFORMATICS 2013年第1期14卷 1-15页

作者： Hocking, Toby Dylan Schleiermacher, Gudrun Janoueix-Lerosey, Isabelle Boeva, Valentina Cappo, Julie Delattre, Olivier Bach, Francis Vert, Jean-Philippe INRIA Sierra Project Team F-75013 Paris France Mines ParisTech Ctr Computat Biol F-77300 Fontainebleau France Inst Curie Paris France INSERM U900 F-75248 Paris France INSERM U830 F-75248 Paris France

Background: Many models have been proposed to detect copy number alterations in chromosomal copy number profiles, but it is usually not obvious to decide which is most effective for a given data set. Furthermore, most methods have a smoothing parameter that determines the number of breakpoints and must be chosen using various heuristics. Results: We present three contributions for copy number profile smoothing model selection. First, we propose to select the model and degree of smoothness that maximizes agreement with visual breakpoint region annotations. Second, we develop cross-validation procedures to estimate the error of the trained models. Third, we apply these methods to compare 17 smoothing models on a new database of 575 annotated neuroblastoma copy number profiles, which we make available as a public benchmark for testing new algorithms. Conclusions: Whereas previous studies have been qualitative or limited to simulated data, our annotation-guided approach is quantitative and suggests which algorithms are fastest and most accurate in practice on real data. In the neuroblastoma data, the equivalent pelt.n and cghseg.k methods were the best breakpoint detectors, and exhibited reasonable computation times.

关键词： Global Model Local Model annotation database annotation Error Default Model

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Algal Functional annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data

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BMC BIOINFORMATICS 2011年第1期12卷 1-10页

作者： Lopez, David Casero, David Cokus, Shawn J. Merchant, Sabeeha S. Pellegrini, Matteo Univ Calif Los Angeles Dept Mol Cell & Dev Biol Los Angeles CA 90095 USA Univ Calif Los Angeles Dept Chem & Biochem Los Angeles CA 90024 USA Univ Calif Los Angeles Inst Genom & Prote Los Angeles CA USA

Background: Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of 'interesting' genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data. Description: The Algal Functional annotation Tool is a web-based comprehensive analysis suite integrating annotation data from several pathway, ontology, and protein family databases. The current version provides annotation for the model alga Chlamydomonas reinhardtii, and in the future will include additional genomes. The site allows users to interpret large gene lists by identifying associated functional terms, and their enrichment. Additionally, expression data for several experimental conditions were compiled and analyzed to provide an expression-based enrichment search. A tool to search for functionally-related genes based on gene expression across these conditions is also provided. Other features include dynamic visualization of genes on KEGG pathway maps

关键词： Gene List Joint Genome Institute Gene Identifier Functional Term annotation database

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DynGO: a tool for visualizing and mining of Gene Ontology and its associations

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BMC BIOINFORMATICS 2005年第1期6卷 1-10页

作者： Liu, HF Hu, ZZ Wu, CH Univ Maryland Baltimore Cty Dept Informat Syst Baltimore MD 21050 USA Georgetown Univ Med Ctr 2 Dept Biochem & Mol Biol Washington DC 20057 USA

Background: A large volume of data and information about genes and gene products has been stored in various molecular biology databases. A major challenge for knowledge discovery using these databases is to identify related genes and gene products in disparate databases. The development of Gene Ontology (GO) as a common vocabulary for annotation allows integrated queries across multiple databases and identification of semantically related genes and gene products (i.e., genes and gene products that have similar GO annotations). Meanwhile, dozens of tools have been developed for browsing, mining or editing GO terms, their hierarchical relationships, or their "associated" genes and gene products (i.e., genes and gene products annotated with GO terms). Tools that allow users to directly search and inspect relations among all GO terms and their associated genes and gene products from multiple databases are needed. Results: We present a standalone package called DynGO, which provides several advanced functionalities in addition to the standard browsing capability of the official GO browsing tool (AmiGO). DynGO allows users to conduct batch retrieval of GO annotations for a list of genes and gene products, and semantic retrieval of genes and gene products sharing similar GO annotations. The result are shown in an association tree organized according to GO hierarchies and supported with many dynamic display options such as sorting tree nodes or changing orientation of the tree. For GO curators and frequent GO users, DynGO provides fast and convenient access to GO annotation data. DynGO is generally applicable to any data set where the records are annotated with GO terms, as illustrated by two examples. Conclusion: We have presented a standalone package DynGO that provides functionalities to search and browse GO and its association databases as well as several additional functions such as batch retrieval and semantic retrieval. The complete documentation and software are fre

关键词： Gene Ontology Leaf Node Semantic Similarity annotation database Semantic Retrieval

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Validation and quality assurance for genome browser database exports

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BMC BIOINFORMATICS 2015年第15-Sup期16卷 1-2页

作者： Chui, Roger Jaromczyk, Jerzy W. Moore, Neil Schardl, Christopher L. Univ Kentucky Dept Comp Sci Lexington KY 40506 USA Univ Kentucky Dept Plant Pathol Lexington KY 40546 USA

P13

关键词： Genome Browser Fungal Endophyte annotation database Quadratic Number Independent Verification

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Exploration of whole-genome responses of the human AIDS-associated yeast pathogen Cryptococcus neoformans var grubii:: nitric oxide stress and body temperature

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CURRENT GENETICS 2007年第3-4期52卷 137-148页

作者： Chow, Eric D. Liu, Oliver W. O'Brien, Sean Madhani, Hiten D. Univ Calif San Francisco Dept Biochem & Biophys San Francisco CA 94158 USA

Cryptococcus neoformans var grubii is an opportunistic basidiomycete yeast pathogen that is a significant cause of HIV/AIDS-related deaths worldwide. We describe a whole-genome oligonucleotide microarray for this pathogen. These arrays have been used to elucidate the transcriptional responses of the genome to heat shock as well as to two conditions relevant to human infections: body temperature and nitric oxide (NO) stress produced by the NO donor DPTA-NONOate. This analysis revealed an NO-inducible C. neoformans-specific four-gene family that showed a highly similar transcriptional profile to that of FHB1, a previously described NO dioxygenase/flavohemoglobin required for virulence. NO treatment also induced genes involved in the synthesis of the antioxidant mannitol, a polyol that accumulates in the cerebrospinal fluid of infected patients. Exposure to NO also caused increased expression of the sole C. neoformans var grubii protein with HHE/hemerythrin cation binding motifs. Notably, a similar gene in E. coli, ytfE, has been shown to be NO-inducible and protects bacterial cells from killing by NO. Genes induced by NO were highly enriched for those repressed at 37 degrees C, indicating an unexpected interplay between temperature and NO regulation in this basidiomycete. Resources described here should facilitate future investigations of this lethal human yeast pathogen.

关键词： fungal pathogenesis nitric oxide DNA microarray transcriptional profiling annotation database genomic

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Gene set enrichment;a problem of pathways

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BRIEFINGS IN FUNCTIONAL GENOMICS 2010年第5-6期9卷 385-390页

作者： Davies, Matthew N. Meaburn, Emma L. Schalkwyk, Leonard C. Kings Coll London Inst Psychiat London SE5 8AF England Univ London Dept Psychol Sci Birkbeck Coll London WC1E 7HU England

Gene Set Enrichment (GSE) is a computational technique which determines whether a priori defined set of genes show statistically significant differential expression between two phenotypes. Currently, the gene sets used for GSE are derived from annotation or pathway databases, which often contain computationally based and unrepresentative data. Here, we propose a novel approach for the generation of comprehensive and biologically derived gene sets, deriving sets through the application of machine learning techniques to gene expression data. These gene sets can be produced for specific tissues, developmental stages or environments. They provide a powerful and functionally meaningful way in which to mine genomewide association and next generation sequencing data in order to identify disease-associated variants and pathways.

关键词： gene set enrichment annotation database gene expression data machine learning next generation sequencing

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ContDist: a tool for the analysis of quantitative gene and promoter properties

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BMC BIOINFORMATICS 2009年第1期10卷 7-7页

作者： Hackenberg, Michael Lasso, Gorka Matthiesen, Rune CIBER HEPAD CIC bioGUNE Bioinformat Grp Derio 48160 Bizkai Spain CIBER HEPAD CIC bioGUNE Funct Genom Unit Derio 48160 Bizkai Spain CIC bioGUNE Struct Biol Unit Derio 48160 Bizkai Spain IPATIMUP P-4200465 Oporto Portugal

Background: The understanding of how promoter regions regulate gene expression is complicated and far from being fully understood. It is known that histones' regulation of DNA compactness, DNA methylation, transcription factor binding sites and CpG islands play a role in the transcriptional regulation of a gene. Many high-throughput techniques exist nowadays which permit the detection of epigenetic marks and regulatory elements in the promoter regions of thousands of genes. However, so far the subsequent analysis of such experiments (e. g. the resulting gene lists) have been hampered by the fact that currently no tool exists for a detailed analysis of the promoter regions. Results: We present ContDist, a tool to statistically analyze quantitative gene and promoter properties. The software includes approximately 200 quantitative features of gene and promoter regions for 7 commonly studied species. In contrast to "traditionally" ontological analysis which only works on qualitative data, all the features in the underlying annotation database are quantitative gene and promoter properties. Utilizing the strong focus on the promoter region of this tool, we show its usefulness in two case studies;the first on differentially methylated promoters and the second on the fundamental differences between housekeeping and tissue specific genes. The two case studies allow both the confirmation of recent findings as well as revealing previously unreported biological relations. Conclusion: ContDist is a new tool with two important properties: 1) it has a strong focus on the promoter region which is usually disregarded by virtually all ontology tools and 2) it uses quantitative (continuously distributed) features of the genes and its promoter regions which are not available in any other tool. ContDist is available from http://***/CD/***

关键词： Promoter Region Gene List Tissue Specific Gene annotation database Input List

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GARNET - gene set analysis with exploration of annotation relations

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BMC BIOINFORMATICS 2011年第Sup1期12卷 1-8页

作者： Rho, Kyoohyoung Kim, Bumjin Jang, Youngjun Lee, Sanghyun Bae, Taejeong Seo, Jihae Seo, Chaehwa Lee, Jihyun Kang, Hyunjung Yu, Ungsik Kim, Sunghoon Lee, Sanghyuk Kim, Wan Kyu Ewha Womans Univ Div Mol Life Sci Seoul 120750 South Korea Seoul Natl Univ Informat Ctr Biopharmacol Network Suwon 443270 South Korea Ewha Womans Univ ERCSB Seoul 120750 South Korea Seoul Natl Univ Coll Pharm Ctr Med Prot Network & Syst Biol Seoul 151742 South Korea Gachon Univ Med & Sci Canc & Diabet Inst Inchon 406840 South Korea

Background: Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information. Results: GARNET (Gene annotation Relationship NEtwork Tools) is an integrative platform for gene set analysis with many novel features. It includes tools for retrieval of genes from annotation database, statistical analysis & visualization of annotation relationships, and managing gene sets. In an effort to allow access to a full spectrum of amassed biological knowledge, we have integrated a variety of annotation data that include the GO, domain, disease, drug, chromosomal location, and custom-defined annotations. Diverse types of molecular networks (pathways, transcription and microRNA regulations, protein-protein interaction) are also included. The pair-wise relationship between annotation gene sets was calculated using kappa statistics. GARNET consists of three modules - gene set manager, gene set analysis and gene set retrieval, which are tightly integrated to provide virtually automatic analysis for gene sets. A dedicated viewer for annotation network has been developed to facilitate exploration of the related annotations. Conclusions: GARNET (gene annotation relationship network tools) is an integrative platform for diverse types of gene set analysis, where complex relationships among gene annotations can be easily explored with an intuitive network visualization tool (http://***/orhttp://***/garnet/).

关键词： Gene Ontology Gene annotation Molecular Network annotation database annotation Term

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