Graphs, Trees, and Hierarchies

Celko, Joe

doi:10.1016/b978-155860920-4/50002-7

Cited by 18 publications

(4 citation statements)

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“…Retrieval of ancestor and descendent taxa to arbitrary depth is supported by secondary indexing according to a modified preorder tree traversal algorithm [49]. Two sources (Tropicos, equivalent to the APG III classification [50], and NCBI taxonomy) serve as alternative family classifications; genera, species and infraspecific taxa from all sources are joined to these families by genus.…”

Section: Methodsmentioning

confidence: 99%

The taxonomic name resolution service: an online tool for automated standardization of plant names

Boyle

Hopkins²,

et al. 2013

BMC Bioinformatics

458

382

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BackgroundThe digitization of biodiversity data is leading to the widespread application of taxon names that are superfluous, ambiguous or incorrect, resulting in mismatched records and inflated species numbers. The ultimate consequences of misspelled names and bad taxonomy are erroneous scientific conclusions and faulty policy decisions. The lack of tools for correcting this ‘names problem’ has become a fundamental obstacle to integrating disparate data sources and advancing the progress of biodiversity science.ResultsThe TNRS, or Taxonomic Name Resolution Service, is an online application for automated and user-supervised standardization of plant scientific names. The TNRS builds upon and extends existing open-source applications for name parsing and fuzzy matching. Names are standardized against multiple reference taxonomies, including the Missouri Botanical Garden's Tropicos database. Capable of processing thousands of names in a single operation, the TNRS parses and corrects misspelled names and authorities, standardizes variant spellings, and converts nomenclatural synonyms to accepted names. Family names can be included to increase match accuracy and resolve many types of homonyms. Partial matching of higher taxa combined with extraction of annotations, accession numbers and morphospecies allows the TNRS to standardize taxonomy across a broad range of active and legacy datasets.ConclusionsWe show how the TNRS can resolve many forms of taxonomic semantic heterogeneity, correct spelling errors and eliminate spurious names. As a result, the TNRS can aid the integration of disparate biological datasets. Although the TNRS was developed to aid in standardizing plant names, its underlying algorithms and design can be extended to all organisms and nomenclatural codes. The TNRS is accessible via a web interface at http://tnrs.iplantcollaborative.org/ and as a RESTful web service and application programming interface. Source code is available at https://github.com/iPlantCollaborativeOpenSource/TNRS/.

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Section: Methodsmentioning

confidence: 99%

The taxonomic name resolution service: an online tool for automated standardization of plant names

Boyle

Hopkins²,

et al. 2013

BMC Bioinformatics

458

382

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“…The search engine is built on top of MySQL, an open-source relational database management system (RDBMS) [16]. PhyloFinder stores the phylogenetic trees, which in our test implementation are from TreeBASE [12,13], and the NCBI taxonomy tree [11] in MySQL using a slight modification [17] of nested-set representation [18,19]. Under this scheme, each node x of a given tree is represented by an interval [ N x , R x ], where N x , called the NodeID of x , is an integer defined by a preorder walk of the tree [20], and R x is the largest NodeID of a descendant of x (see Figure 5).…”

Section: Methodsmentioning

confidence: 99%

PhyloFinder: An intelligent search engine for phylogenetic tree databases

et al. 2008

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BackgroundBioinformatic tools are needed to store and access the rapidly growing phylogenetic data. These tools should enable users to identify existing phylogenetic trees containing a specified taxon or set of taxa and to compare a specified phylogenetic hypothesis to existing phylogenetic trees.ResultsPhyloFinder is an intelligent search engine for phylogenetic databases that we have implemented using trees from TreeBASE. It enables taxonomic queries, in which it identifies trees in the database containing the exact name of the query taxon and/or any synonymous taxon names, and it provides spelling suggestions for the query when there is no match. Additionally, PhyloFinder can identify trees containing descendants or direct ancestors of the query taxon. PhyloFinder also performs phylogenetic queries, in which it identifies trees that contain the query tree or topologies that are similar to the query tree.ConclusionPhyloFinder can enhance the utility of any tree database by providing tools for both taxonomic and phylogenetic queries as well as visualization tools that highlight the query results and provide links to NCBI and TBMap. An implementation of PhyloFinder using trees from TreeBASE is available from the web client application found in the availability and requirements section.

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“…In order to reach a compromise between simplicity and flexibility, the authors chose a star-like databaseschematorepresentthemathematicalmodel,asshowninFigure3.Noticethegivenschema isneitherastarschemanoranERschema:itisahybridrepresentation.Duringtheinitialstageof theproject,itwasastar-schema,becauseitprovidesabasicschemathatcouldbegrownwithnew cubedimensions,dependingonadditionalinformationgivenbyusers'requirements.Butontheother hand,unfortunately,therecursiveparsertreestructurecouldnotberepresentedasapurestarschema, because it required a recursive node entity (Karwin, 2010;Celko, 2004). Therefore, introducing many-to-many(M:N)relationshipsintothestarschemathatoriginallyhadonlyone-to-many(1:N) relationshipswasnecessary.However,theauthorsmadeanefforttomaketheschemaassimilaras possibletoanactualstar-schemainordertoeasilyaddnewdimensionstothemodel,whichwould allowstoringusefulinformationabouttheequations(e.g.,dateofinsertion,experiment,nameof theexperimenter,etc).Forinstance,eachequationcanbelinkedtotheexperimenterwhoaddedthe equations.Theexperimenterhaspersonalinformationattributes(id,name,position,etc),butsuch personisalsopartofateam,whichispartofadepartment.Therefore,theexperimenterdimension hasthefollowinghierarchy:department<team<experimenter.Thenthestar-likeschemagives theopportunitytoperformaggregationoperationssuchasRoll-UporDrill-Down,inordertogroup equationsthatbelongstothesameexperimenter,thesameteam,orthesamedepartment.Similarly, addingthedateofinsertionoftheequationsinducesanadditionaltimedimension.Thenequations canbeaggregatedbymonth,yearoratimerange,whichcanhelptrackingthelaboratoryactivity.…”

Section: From Binary Parser Tree To Er Modelmentioning

confidence: 99%

A Mathematical Database to Process Time Series

Ponchateau

Bellatreche

Ordóñez

et al. 2018

International Journal of Data Warehousing and Mining

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In scientific research, the results of an experiment commonly take the form of a time series, in which such time series consists of measurements collected from a sensor over time. After time series are stored, mathematical models are derived using numerical methods. Even though there exist plenty of tools to store and analyze time series data, there is scarce research aimed at storing and querying derived models, which are the most important mechanism for a scientist to understand data. In this article, the authors propose to help scientists with a flexible database structure to persist and manage mathematical models with a mathematical models store, with extended features, to handle time series. In this article, the authors introduce the concept of a mathematical models store enriched with numerical processing methods to allow queries based on raw time series data. Then they introduce a prototype, that is an implementation of such a data store with PostgreSQL.

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Graphs, Trees, and Hierarchies

Cited by 18 publications

References 0 publications

The taxonomic name resolution service: an online tool for automated standardization of plant names

The taxonomic name resolution service: an online tool for automated standardization of plant names

PhyloFinder: An intelligent search engine for phylogenetic tree databases

A Mathematical Database to Process Time Series

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