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Taxonomic classes of sets

James F Lynch
1990 Journal of combinatorial theory. Series A  
INTRODUCTION By a class of sets we mean a set whose members are sets.  ...  , = number of connected complete taxonomic classes on n M, = number of maximal taxonomic classes on n.  ... 
doi:10.1016/0097-3165(90)90054-z fatcat:p43qvbobvvbj5bwdatjsf4yske

TACOA – Taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach

Naryttza N Diaz, Lutz Krause, Alexander Goesmann, Karsten Niehaus, Tim W Nattkemper
2009 BMC Bioinformatics  
Remarkably, TACOA also produces reliable results when the taxonomic origin of a fragment is not represented in the reference set, thus classifying such fragments to its known broader taxonomic class or  ...  However, the taxonomic classification is an essential task in the analysis of metagenomics data sets that it is still far from being solved.  ...  The authors wish to thank Torsten Kasch, Achim Neumann, Ralf Nolte, Björn Fischer and Volker Tölle as members of the Bioinformatics Resource Facility for providing the computational and technical support  ... 
doi:10.1186/1471-2105-10-56 pmid:19210774 pmcid:PMC2653487 fatcat:e23qeugs2renhm6vkb4o6lvoie

A Model to Represent Nomenclatural and Taxonomic Information as Linked Data. Application to the French Taxonomic Register, TAXREF

Franck Michel, Olivier Gargominy, Sandrine Tercerie, Catherine Faron-Zucker
2017 International Semantic Web Conference  
Finally, using the example of TAXREF, we show that the model enables interlinking with third-party LOD data sets, may they represent nomenclatural or taxonomic information.  ...  Taxonomic registers are key tools to help us comprehend the diversity of nature.  ...  OWL class characterizes a taxon as the set of individuals of that biological entity.  ... 
dblp:conf/semweb/MichelGTF17 fatcat:gndxmz45vbae7odvskzpzbnyaq

C16S — A Hidden Markov Model based algorithm for taxonomic classification of 16S rRNA gene sequences

Tarini Shankar Ghosh, Purnachander Gajjalla, Monzoorul Haque Mohammed, Sharmila S Mande
2012 Genomics  
The taxonomic affiliation of these 16S rDNA fragments is subsequently obtained using either BLAST-based or word frequency based approaches.  ...  In this study, we present a 16S rDNA classification algorithm, called C16S, that uses genus-specific Hidden Markov Models for taxonomic classification of 16S rDNA sequences.  ...  Acknowledgments We thank Sudha Chadaram for her help during the course of this study. We thank Qiong Wang for her suggestions in using the RDP classifier in various simulated scenarios.  ... 
doi:10.1016/j.ygeno.2012.01.008 pmid:22326741 fatcat:d3za4qbhlzgj7h6aoh5lpq4b6a

Using the taxon-specific genes for the taxonomic classification of bacterial genomes

Ankit Gupta, Vineet K Sharma
2015 BMC Genomics  
The correct taxonomic assignment of bacterial genomes is a primary and challenging task.  ...  This approach has been implemented for the development of a tool 'Microtaxi' which can be used for the taxonomic assignment of complete bacterial genomes.  ...  However, the views expressed in this manuscript are that of the authors alone and no approval of the same, explicit or implicit, by MHRD should be assumed.  ... 
doi:10.1186/s12864-015-1542-0 pmid:25990029 pmcid:PMC4438512 fatcat:w4bd24a3x5dbvam54owbprtyuq

Structured Output Prediction with Hierarchical Loss Functions for Seafloor Imagery Taxonomic Categorization [chapter]

Navid Nourani-Vatani, Roberto López-Sastre, Stefan Williams
2015 Lecture Notes in Computer Science  
In this paper we study the challenging problem of seafloor imagery taxonomic categorization. Our contribution is threefold.  ...  And third, we show how the Structured SVM can naturally deal with the problem of learning from data imbalance by scaling the cost of misclassification during the optimization.  ...  The authors acknowledge the Australian National Research Program (NERP) Marine Biodiversity Hub for the taxonomical labeling and the Australian Centre for Field Robotics for gathering the image data.  ... 
doi:10.1007/978-3-319-19390-8_20 fatcat:kp3m6j7rgvei7dv3llghocxxrq

Species-level microbial sequence classification is improved by source-environment information [article]

Benjamin D Kaehler, Nicholas Bokulich, J Gregory Caporaso, Gavin A Huttley
2018 bioRxiv   pre-print
a utility for estimating how effectively a new set of taxonomic class weights will improve taxonomic classification accuracy.  ...  This improvement comes from setting EMPO habitat type-specific taxonomic class weights for a naive Bayes taxonomic classifier to the average microbial composition for that habitat.  ...  These funding bodies had no role in the design of the study, the collection, analysis, or interpretation of data, or in writing the manuscript.  ... 
doi:10.1101/406611 fatcat:fb5mqln7n5bgddbau55v2c46su

Modelling Biodiversity Linked Data: Pragmatism May Narrow Future Opportunities

Franck Michel, Catherine Faron-Zucker, Sandrine Tercerie, Gargominy Olivier
2018 Biodiversity Information Science and Standards  
An OWL class exactly captures this semantics through the set of necessary and sufficient conditions that an individual must meet to be a class member.  ...  However, the SW addresses a much broader set of problems involving automatic reasoning.  ...  An OWL class exactly captures this semantics through the set of necessary and sufficient conditions that an individual must meet to be a class member.  ... 
doi:10.3897/biss.2.26235 fatcat:cg6soxs4hfh7blgzg5ftkl3cam

How many dimensions of biodiversity do we need?

Olga Lyashevska, Keith D. Farnsworth
2012 Ecological Indicators  
Here we attempt a reduction to the minimal set of metrics needed to describe biodiversity (often by default taken to be species richness). 1000 model communities with realistic taxonomic composition were  ...  We found the three major axes of biodiversity were (a) structural complexity, and (b) two different mixtures of taxonomic and functional diversity: it was well approximated by a three-dimensional space  ...  For each taxonomic class C j (i), (j = 1, . . ., N C (i)), of the community set of classes C W (i), the number of taxonomic orders N O (i, j) in C j (i) was assigned by random sampling following the OiC  ... 
doi:10.1016/j.ecolind.2011.12.016 fatcat:seyubuydsfc5zfhlu3kw3g6cp4

Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

Jennifer I Deegan (née Clark), Emily C Dimmer, Christopher J Mungall
2010 BMC Bioinformatics  
Results: We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology.  ...  The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation.  ...  useful discussion at the inception of the project, following on from his publication of relationships to link GO classes to taxonomic groups.  ... 
doi:10.1186/1471-2105-11-530 pmid:20973947 pmcid:PMC3098089 fatcat:g4sk4hdey5dozowyyk3nmjrdwq

BERTax: taxonomic classification of DNA sequences with Deep Neural Networks [article]

Florian Mock, Fleming Kretschmer, Anton Kriese, Sebastian Böcker, Manja Marz
2021 bioRxiv   pre-print
We show BERTax to be at least on par with the state-of-the-art approaches when taxonomically similar species are part of the training data.  ...  Since BERTax is not based on homologous entries in databases, it allows precise taxonomic classification of a broader range of genomic sequences.  ...  taxonomic classes.  ... 
doi:10.1101/2021.07.09.451778 fatcat:7g7n245hsncwfj47towr2mq7ty

Page 343 of American Anthropologist Vol. 64, Issue 2 [page]

1962 American Anthropologist  
By the use of this technique, three sets of folk taxonomic data were elicited: (1) broad taxonomic classes, (2) narrow taxonomic classes, and (3) taxonomic labels.  ...  In this set of data, there is thus a strong statistical trend towards a corre- spondence between cultural classes and linguistic classes.  ... 

Solving Long-tailed Recognition with Deep Realistic Taxonomic Classifier [article]

Tz-Ying Wu, Pedro Morgado, Pei Wang, Chih-Hui Ho, Nuno Vasconcelos
2020 arXiv   pre-print
While modern classifiers perform well on populated classes, its performance degrades significantly on tail classes.  ...  Experiments on the long-tailed version of four datasets, CIFAR100, AWA2, Imagenet, and iNaturalist, demonstrate that the proposed approach preserves more information on all classes with different popularity  ...  Realistic Taxonomic Classification A taxonomic classifier maps images x ∈ X into a set of C classes y ∈ Y ∈ {1, . . . , C}, organized into a taxonomic structure where classes are recursively grouped into  ... 
arXiv:2007.09898v1 fatcat:tttr66jedfgwrom46ymt4vzofq

Taxa: An R package implementing data standards and methods for taxonomic data

Zachary S.L. Foster, Scott Chamberlain, Niklaus J. Grünwald
2018 F1000Research  
The taxa R package provides a set of tools for defining and manipulating taxonomic data.  ...  The recent and widespread application of DNA sequencing to community composition studies is making large data sets with taxonomic information commonplace.  ...  The taxmap class. The taxmap class inherits the taxonomy class and is used to store any number of data sets associated with taxa in a taxonomy (Figure 1) .  ... 
doi:10.12688/f1000research.14013.1 pmid:29707201 pmcid:PMC5887078 fatcat:z6qncijoznfhtmioellnw2zujy

The effect of training set on the classification of honey bee gut microbiota using the Naïve Bayesian Classifier

Irene LG Newton, Guus Roeselers
2012 BMC Microbiology  
We conclude that for the exploration of relatively novel habitats, the inclusion of high-quality, full-length 16S rRNA gene sequences allows for a more confident taxonomic classification.  ...  However, the consistency and confidence of classifications provided by the RDP-NBC is dependent on the training set utilized.  ...  The manuscript benefited from the critiques of four anonymous reviewers, to which we are thankful.  ... 
doi:10.1186/1471-2180-12-221 pmid:23013113 pmcid:PMC3520854 fatcat:pcbpe6qn5zcqnjptmamqnjfkhy
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