scholarly journals SOFT COMPUTING BASED IDENTIFICATION AND ASSESSMENT OF POTENTIAL DNA BARCODES OF SOLANACEOUS SPECIES USING cpDNA SEQUENCES

2021 ◽  
Vol 12 (3) ◽  
pp. 641-652
Author(s):  
Bhupinder Pal Singh ◽  
Ajay Kumar ◽  
Harpreet Singh ◽  
Avinash Kaur Nagpal
Keyword(s):  
Soft Computing ◽  
Dna Barcodes ◽  
Solanaceous Species

Soft Computing in Electromagnetics

2015 ◽  
Author(s):  
Balamati Choudhury ◽  
Rakesh Mohan Jha
Keyword(s):  
Soft Computing

DNA barcodes tag species

Nature ◽  
2004 ◽  
Author(s):  
Helen Pearson
Keyword(s):  
Dna Barcodes

Notes on the molecular taxonomy of the Proclossiana eunomia complex (Lepidoptera, Nymphalidae: Argynnini): analysis of DNA barcodes

2018 ◽  
Vol 8 (1) ◽  
pp. 222-232 ◽  
Author(s):  
R. V. Yakovlev ◽  
N. A. Shapoval ◽  
G. N. Kuftina ◽  
A. V. Kulak ◽  
S. V. Kovalev
Keyword(s):  
Body Size ◽  
Molecular Taxonomy ◽  
Taxonomic Status ◽  
Molecular Data ◽  
Coi Gene ◽  
Wing Pattern ◽  
Molecular Approach ◽  
Dna Barcodes ◽  
Morphological Differences ◽  
Proclossiana Eunomia

The Proclossiana eunomia (Esper, 1799) complex is currently composed of the several subspecies distributed throughout Palaearсtic region and North America. Despite the fact that some of the taxa have differences in wing pattern and body size, previous assumptions on taxonomy not supported by molecular data. Therefore, the identity of certain populations of this complex has remained unclear and the taxonomic status of several recently described taxa is debated. Here, we provide insights into systematics of some Palaearctic members of this group using molecular approach, based on the analysis of the barcoding fragment of the COI gene taking into account known morphological differences.

MACHINE LEARNING FOR SOFTWARE

2019 ◽  
pp. 251-255
Author(s):  
Shafagat Mahmudova
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
Soft Computing ◽  
Computing Technology

The study machine learning for software based on Soft Computing technology. It analyzes Soft Computing components. Their use in software, their advantages and challenges are studied. Machine learning and its features are highlighted. The functions and features of neural networks are clarified, and recommendations were given.

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