Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part I: Design and Theoretical Performance of Multivariate Optical Elements

2013 ◽  
Vol 67 (6) ◽  
pp. 620-629 ◽  
Author(s):  
Joseph A. Swanstrom ◽  
Laura S. Bruckman ◽  
Megan R. Pearl ◽  
Michael N. Simcock ◽  
Kathleen A. Donaldson ◽  
...  
Keyword(s):  
Optical Computing ◽  
Taxonomic Classification ◽  
Optical Elements ◽  
Multivariate Optical Computing ◽  
Theoretical Performance

Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part III: Demonstration

2013 ◽  
Vol 67 (6) ◽  
pp. 640-647 ◽  
Author(s):  
Megan R. Pearl ◽  
Joseph A. Swanstrom ◽  
Laura S. Bruckman ◽  
Tammi L. Richardson ◽  
Timothy J. Shaw ◽  
...  
Keyword(s):  
Optical Computing ◽  
Taxonomic Classification ◽  
Multivariate Optical Computing

Taxonomic Classification of Phytoplankton with Multivariate Optical Computing, Part II: Design and Experimental Protocol of a Shipboard Fluorescence Imaging Photometer

2013 ◽  
Vol 67 (6) ◽  
pp. 630-639 ◽  
Author(s):  
Joseph A. Swanstrom ◽  
Laura S. Bruckman ◽  
Megan R. Pearl ◽  
Elizabeth Abernathy ◽  
Tammi L. Richardson ◽  
...  
Keyword(s):  
Fluorescence Imaging ◽  
Optical Computing ◽  
Taxonomic Classification ◽  
Experimental Protocol ◽  
Multivariate Optical Computing

Genetic characteristics and taxonomic classification of Fimic Anthrosols in China

Geoderma ◽  
2003 ◽  
Vol 115 (1-2) ◽  
pp. 31-44 ◽  
Author(s):  
Min Zhang ◽  
Li Ma ◽  
Wenqing Li ◽  
Baocheng Chen ◽  
Jiwen Jia
Keyword(s):  
Taxonomic Classification ◽  
Genetic Characteristics

scholarly journals A singular value decomposition approach for improved taxonomic classification of biological sequences

BMC Genomics ◽  
2011 ◽  
Vol 12 (Suppl 4) ◽  
pp. S11 ◽  
Author(s):  
Anderson R Santos ◽  
Marcos A Santos ◽  
Jan Baumbach ◽  
John A McCulloch ◽  
Guilherme C Oliveira ◽  
...  
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Taxonomic Classification ◽  
Biological Sequences ◽  
Decomposition Approach ◽  
Value Decomposition

scholarly journals Extreme diversification driven by parallel events of massive loss of heterozygosity in the hybrid lineage of Candida albicans

Genetics ◽  
2020 ◽  
Vol 217 (2) ◽  
Author(s):  
Verónica Mixão ◽  
Ester Saus ◽  
Teun Boekhout ◽  
Toni Gabaldón
Keyword(s):  
Candida Albicans ◽  
Loss Of Heterozygosity ◽  
Type Strain ◽  
Taxonomic Classification ◽  
Hybrid Origin ◽  
Genomic Analyses ◽  
Candida Africana

Abstract Candida albicans is the most commonly reported species causing candidiasis. The taxonomic classification of C. albicans and related lineages is controversial, with Candida africana (syn. C. albicans var. africana) and Candida stellatoidea (syn. C. albicans var. stellatoidea) being considered different species or C. albicans varieties depending on the authors. Moreover, recent genomic analyses have suggested a shared hybrid origin of C. albicans and C. africana, but the potential parental lineages remain unidentified. Although the genomes of C. albicans and C. africana have been extensively studied, the genome of C. stellatoidea has not been sequenced so far. In order to get a better understanding of the evolution of the C. albicans clade, and to assess whether C. stellatoidea could represent one of the unknown C. albicans parental lineages, we sequenced C. stellatoidea type strain (CBS 1905). This genome was compared to that of C. albicans and of the closely related lineage C. africana. Our results show that, similarly to C. africana, C. stellatoidea descends from the same hybrid ancestor as other C. albicans strains and that it has undergone a parallel massive loss of heterozygosity.

VirusTaxo: Taxonomic classification of virus genome using multi-class hierarchical classification by k-mer enrichment

2021 ◽  
Author(s):  
Rajan Saha Raju ◽  
Abdullah Al Nahid ◽  
Preonath Shuvo ◽  
Rashedul Islam
Keyword(s):  
Genome Sequence ◽  
Rna Viruses ◽  
Hierarchical Classification ◽  
Classification Problem ◽  
Virus Genome ◽  
Taxonomic Classification ◽  
Dna Viruses ◽  
Dna And Rna ◽  
Full Length Genome

AbstractTaxonomic classification of viruses is a multi-class hierarchical classification problem, as taxonomic ranks (e.g., order, family and genus) of viruses are hierarchically structured and have multiple classes in each rank. Classification of biological sequences which are hierarchically structured with multiple classes is challenging. Here we developed a machine learning architecture, VirusTaxo, using a multi-class hierarchical classification by k-mer enrichment. VirusTaxo classifies DNA and RNA viruses to their taxonomic ranks using genome sequence. To assign taxonomic ranks, VirusTaxo extracts k-mers from genome sequence and creates bag-of-k-mers for each class in a rank. VirusTaxo uses a top-down hierarchical classification approach and accurately assigns the order, family and genus of a virus from the genome sequence. The average accuracies of VirusTaxo for DNA viruses are 99% (order), 98% (family) and 95% (genus) and for RNA viruses 97% (order), 96% (family) and 82% (genus). VirusTaxo can be used to detect taxonomy of novel viruses using full length genome or contig sequences.AvailabilityOnline version of VirusTaxo is available at https://omics-lab.com/virustaxo/.

scholarly journals Functional and taxonomic classification of a greenhouse water drain metagenome

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Gamaliel López-Leal ◽  
Fernanda Cornejo-Granados ◽  
Juan Manuel Hurtado-Ramírez ◽  
Alfredo Mendoza-Vargas ◽  
Adrian Ochoa-Leyva
Keyword(s):  
Taxonomic Classification ◽  
Water Drain

Detection and Classification of Acoustic Images: Theoretical Performance

1992 ◽  
pp. 89-93
Author(s):  
J. G. Kelly ◽  
R. N. Carpenter ◽  
D. R. Childs
Keyword(s):  
Acoustic Images ◽  
Theoretical Performance
Sign in / Sign up

Export Citation Format

Share Document