CLASSIFICATION OF GENETIC SEQUENCES WITH BACKPROPAGATION

1994 ◽  
Vol 05 (03) ◽  
pp. 159-163
Author(s):  
R. LENDE ◽  
L.P. CSERNAI ◽  
D. KAMP
Keyword(s):  
Statistical Analysis ◽  
Dna Sequences ◽  
Biological Species ◽  
Neural Net ◽  
Training Phase ◽  
Backpropagation Algorithm ◽  
Genetic Sequences

A backpropagation algorithm is used to train a neural net with the goal of distinguishing between two groups of biological species: prokaryotic and eukaryotic, based on frequencies of all 16 doublets in DNA sequences. An improvement of about 15% is obtained compared to statistical analysis based on one doublet only. This is done first by presenting sequences of species to the network with known classification (the training phase) and then showing species which the neural net has never seen before, and looking for the response. A brief discussion of the speed of training is given.

scholarly journals The Taxonomic Rank of Spizella Taverneri: A Response to Mayr and Johnson

The Condor ◽  
2001 ◽  
Vol 103 (2) ◽  
pp. 420-422 ◽  
Author(s):  
John Klicka ◽  
Robert M. Zink ◽  
Jon C. Barlow ◽  
W. Bruce McGillivray ◽  
Terry J. Doyle
Keyword(s):  
Mitochondrial Dna ◽  
Dna Sequences ◽  
Habitat Preferences ◽  
Sequence Divergence ◽  
Biological Species ◽  
Sister Species ◽  
Timing Of Breeding ◽  
Species Status ◽  
Taxonomic Rank

AbstractMayr and Johnson suggest that Spizella taverneri should be a subspecies of the biological species S. breweri, because it is possibly not reproductively isolated. We originally concluded that evidence from mitochondrial DNA sequences, habitat preferences, timing of breeding, vocalizations, and morphology supported the recognition of S. taverneri as a phylogenetic and biological species. Nothing in the commentary by Mayr and Johnson causes us to change that conclusion. We believe that it is probable that these two allopatric taxa are isolated. Contrary to Mayr and Johnson, we believe that more information is given by ranking S. taverneri as a species, because it reveals the fact that they are independently evolving taxa. The classification of Spizella should convey the sister-species status of S. taverneri and S. breweri, without regard for balancing the degree of sequence divergence among species, as suggested by Mayr and Johnson.

Discovery of New Genera Challenges the Subtribal Classification of Tok-Tok Beetles (Coleoptera: Tenebrionidae: Sepidiini)

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Olivia M Gearner ◽  
Marcin J Kamiński ◽  
Kojun Kanda ◽  
Kali Swichtenberg ◽  
Aaron D Smith
Keyword(s):  
Dna Sequences ◽  
Species Group ◽  
Phylogenetic Placement ◽  
Darkling Beetles ◽  
Species Groups ◽  
Taxonomic Groups ◽  
Inference Methods ◽  
A New Species ◽  
Coleoptera Tenebrionidae

Abstract Sepidiini is a speciose tribe of desert-inhabiting darkling beetles, which contains a number of poorly defined taxonomic groups and is in need of revision at all taxonomic levels. In this study, two previously unrecognized lineages were discovered, based on morphological traits, among the extremely speciose genera Psammodes Kirby, 1819 (164 species and subspecies) and Ocnodes Fåhraeus, 1870 (144 species and subspecies), namely the Psammodes spinosus species-group and Ocnodes humeralis species-group. In order to test their phylogenetic placement, a phylogeny of the tribe was reconstructed based on analyses of DNA sequences from six nonoverlapping genetic loci (CAD, wg, COI JP, COI BC, COII, and 28S) using Bayesian and maximum likelihood inference methods. The aforementioned, morphologically defined, species-groups were recovered as distinct and well-supported lineages within Molurina + Phanerotomeina and are interpreted as independent genera, respectively, Tibiocnodes Gearner & Kamiński gen. nov. and Tuberocnodes Gearner & Kamiński gen. nov. A new species, Tuberocnodes synhimboides Gearner & Kamiński sp. nov., is also described. Furthermore, as the recovered phylogenetic placement of Tibiocnodes and Tuberocnodes undermines the monophyly of Molurina and Phanerotomeina, an analysis of the available diagnostic characters for those subtribes is also performed. As a consequence, Phanerotomeina is considered as a synonym of the newly redefined Molurina sens. nov. Finally, spectrograms of vibrations produced by substrate tapping of two Molurina species, Toktokkus vialis (Burchell, 1822) and T. synhimboides, are presented.

scholarly journals An application of slow feature analysis to the genetic sequences of coronaviruses and influenza viruses

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Anastasios A. Tsonis ◽  
Geli Wang ◽  
Lvyi Zhang ◽  
Wenxu Lu ◽  
Aristotle Kayafas ◽  
...  
Keyword(s):  
Mathematical Method ◽  
Dna Sequence ◽  
Dna Sequences ◽  
Transmission Rate ◽  
Complex Structure ◽  
Mortality Rates ◽  
Influenza Viruses ◽  
Feature Analysis ◽  
Slow Feature Analysis ◽  
Genetic Sequences

Abstract Background Mathematical approaches have been for decades used to probe the structure of DNA sequences. This has led to the development of Bioinformatics. In this exploratory work, a novel mathematical method is applied to probe the DNA structure of two related viral families: those of coronaviruses and those of influenza viruses. The coronaviruses are SARS-CoV-2, SARS-CoV-1, and MERS. The influenza viruses include H1N1-1918, H1N1-2009, H2N2-1957, and H3N2-1968. Methods The mathematical method used is the slow feature analysis (SFA), a rather new but promising method to delineate complex structure in DNA sequences. Results The analysis indicates that the DNA sequences exhibit an elaborate and convoluted structure akin to complex networks. We define a measure of complexity and show that each DNA sequence exhibits a certain degree of complexity within itself, while at the same time there exists complex inter-relationships between the sequences within a family and between the two families. From these relationships, we find evidence, especially for the coronavirus family, that increasing complexity in a sequence is associated with higher transmission rate but with lower mortality. Conclusions The complexity measure defined here may hold a promise and could become a useful tool in the prediction of transmission and mortality rates in future new viral strains.

Discriminating arboviral species

2021 ◽  
Vol 102 (4) ◽  
Author(s):  
Yiyuan Li ◽  
Angela C. O’Donnell ◽  
Howard Ochman
Keyword(s):  
Evolutionary History ◽  
Viral Vectors ◽  
Species Concept ◽  
International Committee ◽  
Biological Species ◽  
Biological Species Concept ◽  
Substantial Variation ◽  
Artificial Boundaries ◽  
Human Infections

Mosquito-borne arboviruses, including a diverse array of alphaviruses and flaviviruses, lead to hundreds of millions of human infections each year. Current methods for species-level classification of arboviruses adhere to guidelines prescribed by the International Committee on Taxonomy of Viruses (ICTV), and generally apply a polyphasic approach that might include information about viral vectors, hosts, geographical distribution, antigenicity, levels of DNA similarity, disease association and/or ecological characteristics. However, there is substantial variation in the criteria used to define viral species, which can lead to the establishment of artificial boundaries between species and inconsistencies when inferring their relatedness, variation and evolutionary history. In this study, we apply a single, uniform principle – that underlying the Biological Species Concept (BSC) – to define biological species of arboviruses based on recombination between genomes. Given that few recombination events have been documented in arboviruses, we investigate the incidence of recombination within and among major arboviral groups using an approach based on the ratio of homoplastic sites (recombinant alleles) to non-homoplastic sites (vertically transmitted alleles). This approach supports many ICTV-designations but also recognizes several cases in which a named species comprises multiple biological species. These findings demonstrate that this metric may be applied to all lifeforms, including viruses, and lead to more consistent and accurate delineation of viral species.

Enhanced Backpropagation Approach for Identifying Genetic Disease

2014 ◽  
Vol 622 ◽  
pp. 75-80
Author(s):  
Baskar Nisha ◽  
B. Madasamy ◽  
J.Jebamalar Tamilselvi
Keyword(s):  
Machine Learning ◽  
Genetic Disease ◽  
Classification Accuracy ◽  
Gene Selection ◽  
New Classification ◽  
Backpropagation Algorithm ◽  
High Classification Accuracy ◽  
Disease Associations ◽  
Disease Analysis

Classification of data on genetic disease is a useful application in microarray analysis. The genetic disease data analysis has the potential for discovering the diseased genes which may be the signature of certain diseases. Machine learning methodologies and data mining techniques are used to predict genetic disease associations of bio informatics data. Among numerous existing methods for gene selection, Backpropagation algorithm has become one of the leading methods and it gives less classification accuracy. It aims to develop a new classification algorithm (Enhanced Backpropagation Algorithm) for genetic disease analysis. Knowledge derived by the Enhanced Backpropagation Algorithm has high classification accuracy with the ability to identify the most significant genes.

Towards a monophyletic classification of Lejeuneaceae III: the systematic position of Leiolejeunea

Phytotaxa ◽  
2014 ◽  
Vol 170 (3) ◽  
pp. 187 ◽  
Author(s):  
ALFONS SCHÄFER-VERWIMP ◽  
KATHRIN FELDBERG ◽  
SHANSHAN DONG ◽  
HUUB VAN MELICK ◽  
DENILSON F. PERALTA ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Maximum Likelihood ◽  
Dna Sequences ◽  
Its Region ◽  
Systematic Position ◽  
Leaf Cell ◽  
Oil Bodies ◽  
Sister Relationship ◽  
First Time

The derived liverwort Leiolejeunea grandiflora was recollected at the type locality in Jamaica after more than 100 years. The characteristics of its oil bodies were described for the first time based on the new collections. Each leaf cell possesses 2-4(-6) rather small, subhomogeneous to very finely segmented, subglobose to ellipsoidal, colorless oil bodies. The plants were either dioicous or autoicous. DNA sequences of two chloroplast regions (trnL-trnF, rbcL) and the nuclear ribosomal ITS region were obtained for two accessions of Leiolejeunea to enable the inference of the phylogenetic relationships of these plants. Based on Bayesian inference of phylogeny as well as maximum parsimony and maximum likelihood analyses of a dataset including 87 representatives of Lejeuneaceae, Leiolejeunea was found as the putative sister to either Echinolejeuneinae or Cheilolejeuneinae. Thus, we propose the new monogeneric subtribe Leiolejeuneinae with relationships to Cheilolejeuneinae and Echinolejeuneinae. The analyses included also one accession of the generitype of Cheilolejeunea, C. decidua [= Cheilolejeunea adnata]. This species was found in a well supported sister relationship with Cystolejeunea. To avoid nomenclatural confusion, we propose a wide genus concept for Cheilolejeunea including Aureolejeunea, Cyrtolejeunea, Cystolejeunea, Evansiolejeunea, Leucolejeunea, and Omphalanthus.

scholarly journals Identification and Classification of Real Estate Features for the Purpose of an Algorithm-Based Valuation– Case Study within Szczecin

2019 ◽  
Vol 19 (2) ◽  
pp. 38-55
Author(s):  
Sebastian Kokot ◽  
Sebastian Gnat
Keyword(s):  
Statistical Analysis ◽  
Real Estate ◽  
Point Of View ◽  
Graphical Methods ◽  
Scientific Discussion ◽  
Valuation Process ◽  
Deductive Method ◽  
Research Criteria

Abstract Research background: The article discusses the issue of the identification and measurement of market characteristics of real estate for valuation purposes. This problem is the most difficult stage of the whole valuation process in terms of both a substantive, methodological and analytical basis. Goal: The aim of the research is to outline and explore on the basis of literature studies as well as developed problems to be solved in the process of mass valuation together with the presentation of an exemplary solution. Methodology: In the theoretical part a hypothetical-deductive method which consists of developing a certain hypothesis and deducing its consequences was applied. The empirical section uses the method of scientific discussion among scientists and practicing valuers and, for the presentation of the results; some graphical methods were used for a statistical analysis. Results: As a result of the conducted research, criteria to be used in identifying and classifying market characteristics for the purposes of valuation were identified and a set of market characteristics of properties was developed along with a method of identifying their states for the purposes of mass valuation. Novelty: The article proves that the problem of the identification and classification of market characteristics of real estate for valuation purposes is extremely important from the point of view of the valuation process and the results obtained as a result of it as well. In addition, for some features, it is proposed to develop special measures such as the plot shape attractiveness ratio. This meets the problem of the objective measurement of market features of real estate. In relation to other features, the legitimacy of the expert approach was pointed out.

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