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                    "firstName": "Alfonso",
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            "abstractNote": "Establishing protein interaction networks is crucial for understanding cellular operations. Detailed knowledge of the [`]interactome', the full network of protein-protein interactions, in model cellular systems should provide new insights into the structure and properties of these systems. Parallel to the first massive application of experimental techniques to the determination of protein interaction networks and protein complexes, the first computational methods, based on sequence and genomic information, have emerged.",
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            "title": "Berkeley PHOG: PhyloFacts orthology group prediction web server",
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                    "firstName": "Ruchira S.",
                    "lastName": "Datta"
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                    "firstName": "Christopher",
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                    "firstName": "Bushra",
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            "abstractNote": "Ortholog detection is essential in functional annotation of genomes, with applications to phylogenetic tree construction, prediction of protein-protein interaction and other bioinformatics tasks. We present here the PHOG web server employing a novel algorithm to identify orthologs based on phylogenetic analysis. Results on a benchmark dataset from the TreeFam-A manually curated orthology database show that PHOG provides a combination of high recall and precision competitive with both InParanoid and OrthoMCL, and allows users to target different taxonomic distances and precision levels through the use of tree-distance thresholds. For instance, OrthoMCL-DB achieved 76% recall and 66% precision on this dataset; at a slightly higher precision (68%) PHOG achieves 10% higher recall (86%). InParanoid achieved 87% recall at 24% precision on this dataset, while a PHOG variant designed for high recall achieves 88% recall at 61% precision, increasing precision by 37% over InParanoid. PHOG is based on pre-computed trees in the PhyloFacts resource, and contains over 366 K orthology groups with a minimum of three species. Predicted orthologs are linked to GO annotations, pathway information and biological literature. The PHOG web server is available at http://phylofacts.berkeley.edu/orthologs/.",
            "publicationTitle": "Nucl. Acids Res.",
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            "place": "",
            "date": "Mai 12, 2009",
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            "title": "A Bioinformatician's Guide to Metagenomics",
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                    "firstName": "Victor",
                    "lastName": "Kunin"
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                {
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                    "firstName": "Alex",
                    "lastName": "Copeland"
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                    "firstName": "Philip",
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            "abstractNote": "Summary: As random shotgun metagenomic projects proliferate and become the dominant source of publicly available sequence data, procedures for the best practices in their execution and analysis become increasingly important. Based on our experience at the Joint Genome Institute, we describe the chain of decisions accompanying a metagenomic project from the viewpoint of the bioinformatic analysis step by step. We guide the reader through a standard workflow for a metagenomic project beginning with presequencing considerations such as community composition and sequence data type that will greatly influence downstream analyses. We proceed with recommendations for sampling and data generation including sample and metadata collection, community profiling, construction of shotgun libraries, and sequencing strategies. We then discuss the application of generic sequence processing steps (read preprocessing, assembly, and gene prediction and annotation) to metagenomic data sets in contrast to genome projects. Different types of data analyses particular to metagenomes are then presented, including binning, dominant population analysis, and gene-centric analysis. Finally, data management issues are presented and discussed. We hope that this review will assist bioinformaticians and biologists in making better-informed decisions on their journey during a metagenomic project.",
            "publicationTitle": "Microbiol. Mol. Biol. Rev.",
            "publisher": "",
            "place": "",
            "date": "Dezember 1, 2008",
            "volume": "72",
            "issue": "4",
            "section": "",
            "partNumber": "",
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            "pages": "557-578",
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            "DOI": "10.1128/MMBR.00009-08",
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            "url": "http://mmbr.asm.org/cgi/content/abstract/72/4/557",
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            "creatorSummary": "Camon et al.",
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            "version": 5522,
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            "title": "The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Evelyn",
                    "lastName": "Camon"
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                {
                    "creatorType": "author",
                    "firstName": "Michele",
                    "lastName": "Magrane"
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                {
                    "creatorType": "author",
                    "firstName": "Daniel",
                    "lastName": "Barrell"
                },
                {
                    "creatorType": "author",
                    "firstName": "Vivian",
                    "lastName": "Lee"
                },
                {
                    "creatorType": "author",
                    "firstName": "Emily",
                    "lastName": "Dimmer"
                },
                {
                    "creatorType": "author",
                    "firstName": "John",
                    "lastName": "Maslen"
                },
                {
                    "creatorType": "author",
                    "firstName": "David",
                    "lastName": "Binns"
                },
                {
                    "creatorType": "author",
                    "firstName": "Nicola",
                    "lastName": "Harte"
                },
                {
                    "creatorType": "author",
                    "firstName": "Rodrigo",
                    "lastName": "Lopez"
                },
                {
                    "creatorType": "author",
                    "firstName": "Rolf",
                    "lastName": "Apweiler"
                }
            ],
            "abstractNote": "The Gene Ontology Annotation (GOA) database (http://www.ebi.ac.uk/GOA) aims to provide high-quality electronic and manual annotations to the UniProt Knowledgebase (Swiss-Prot, TrEMBL and PIR-PSD) using the standardized vocabulary of the Gene Ontology (GO). As a supplementary archive of GO annotation, GOA promotes a high level of integration of the knowledge represented in UniProt with other databases. This is achieved by converting UniProt annotation into a recognized computational format. GOA provides annotated entries for nearly 60,000 species (GOA-SPTr) and is the largest and most comprehensive open-source contributor of annotations to the GO Consortium annotation effort. By integrating GO annotations from other model organism groups, GOA consolidates specialized knowledge and expertise to ensure the data remain a key reference for up-to-date biological information. Furthermore, the GOA database fully endorses the Human Proteomics Initiative by prioritizing the annotation of proteins likely to benefit human health and disease. In addition to a non-redundant set of annotations to the human proteome (GOA-Human) and monthly releases of its GO annotation for all species (GOA-SPTr), a series of GO mapping files and specific cross-references in other databases are also regularly distributed. GOA can be queried through a simple user-friendly web interface or downloaded in a parsable format via the EBI and GO FTP websites. The GOA data set can be used to enhance the annotation of particular model organism or gene expression data sets, although increasingly it has been used to evaluate GO predictions generated from text mining or protein interaction experiments. In 2004, the GOA team will build on its success and will continue to supplement the functional annotation of UniProt and work towards enhancing the ability of scientists to access all available biological information. Researchers wishing to query or contribute to the GOA project are encouraged to email: goa@ebi.ac.uk.",
            "publicationTitle": "Nucleic Acids Research",
            "publisher": "",
            "place": "",
            "date": "Jan 1, 2004",
            "volume": "32",
            "issue": "Database issue",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "D262-266",
            "series": "",
            "seriesTitle": "",
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            "journalAbbreviation": "Nucleic Acids Res",
            "DOI": "10.1093/nar/gkh021",
            "citationKey": "",
            "url": "http://www.ncbi.nlm.nih.gov/pubmed/14681408",
            "accessDate": "2009-05-29T08:39:38Z",
            "PMID": "14681408",
            "PMCID": "",
            "ISSN": "1362-4962",
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            "shortTitle": "The Gene Ontology Annotation (GOA) Database",
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                {
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                    "tag": "Internet",
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                {
                    "tag": "Proteome",
                    "type": 1
                },
                {
                    "tag": "Proteomics",
                    "type": 1
                },
                {
                    "tag": "Terminology as Topic",
                    "type": 1
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            ],
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            "dateAdded": "2009-06-05T11:49:14Z",
            "dateModified": "2011-02-02T20:56:19Z"
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    },
    {
        "key": "IREUWZPU",
        "version": 5523,
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            "creatorSummary": "Kuzniar et al.",
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            "version": 5523,
            "itemType": "journalArticle",
            "title": "The quest for orthologs: finding the corresponding gene across genomes",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Arnold",
                    "lastName": "Kuzniar"
                },
                {
                    "creatorType": "author",
                    "firstName": "Roeland C H J",
                    "lastName": "van Ham"
                },
                {
                    "creatorType": "author",
                    "firstName": "Sándor",
                    "lastName": "Pongor"
                },
                {
                    "creatorType": "author",
                    "firstName": "Jack A M",
                    "lastName": "Leunissen"
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            ],
            "abstractNote": "Orthology is a key evolutionary concept in many areas of genomic research. It provides a framework for subjects as diverse as the evolution of genomes, gene functions, cellular networks and functional genome annotation. Although orthologous proteins usually perform equivalent functions in different species, establishing true orthologous relationships requires a phylogenetic approach, which combines both trees and graphs (networks) using reliable species phylogeny and available genomic data from more than two species, and an insight into the processes of molecular evolution. Here, we evaluate the available bioinformatics tools and provide a set of guidelines to aid researchers in choosing the most appropriate tool for any situation.",
            "publicationTitle": "Trends in Genetics: TIG",
            "publisher": "",
            "place": "",
            "date": "Nov 2008",
            "volume": "24",
            "issue": "11",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "539-551",
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            "seriesTitle": "",
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            "journalAbbreviation": "Trends Genet",
            "DOI": "10.1016/j.tig.2008.08.009",
            "citationKey": "",
            "url": "http://www.ncbi.nlm.nih.gov/pubmed/18819722",
            "accessDate": "2009-05-29T08:43:39Z",
            "PMID": "18819722",
            "PMCID": "",
            "ISSN": "0168-9525",
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            "shortTitle": "The quest for orthologs",
            "language": "",
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            "callNumber": "0041",
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                    "tag": "Evolution, Molecular",
                    "type": 1
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                {
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                    "type": 1
                },
                {
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                    "type": 1
                },
                {
                    "tag": "Humans",
                    "type": 1
                },
                {
                    "tag": "Phylogeny",
                    "type": 1
                },
                {
                    "tag": "Proteins",
                    "type": 1
                },
                {
                    "tag": "Sequence Homology",
                    "type": 1
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            ],
            "collections": [],
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            "dateAdded": "2009-06-05T11:49:14Z",
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