Equivalent mutant identification using hybrid wavelet convolutional rain optimization

2021 ◽  
Author(s):  
Kiran Jammalamadaka ◽  
Nikhat Parveen
Keyword(s):  
Mutant Identification

scholarly journals Variability and Correlation Studies on Induced Mutants of Marigold (Tagetes erecta L.) for Different Traits and Assessing Them Using Molecular Markers

2018 ◽  
Vol 28 (2) ◽  
pp. 223-236
Author(s):  
Jayoti Majumder ◽  
SK Singh ◽  
Meenu Kumari ◽  
Manjusha Verma
Keyword(s):  
Large Scale ◽  
Field Evaluation ◽  
Issr Markers ◽  
Phenotypic Correlation ◽  
Induced Mutations ◽  
Single Marker ◽  
Tagetes Erecta L ◽  
Mutant Identification

Induced mutations are important for creating novel variabilities in marigold for different purposes. Distinct putative mutants of marigold var. Pusa Narangi Gainda generated through gamma irradiation (in vivo and in vitro), were studied for variability and correlation in M2 generation for 11 traits. The maximum heritability (h2) was noted for days to flower harvest (0.9982%). The highest positive phenotypic correlation (0.637) was noted for number of flowers per plant to the days to first flower harvest. The most positive genotypic correlation (0.915) was found for seed yield (g) to the number of flowers per plant. Furthermore, the putative mutants in M2 were assessed for their diversity using ISSR markers and the amplified DNA fragments were compared with their respective parent genotype maintained (in vivo and in vitro). Single marker regression analysis indicated that the ISSR 811 and ISSR 817 were highly efficient markers for mutant identification in marigold. On the basis of dendrogram, putative mutant No. 3 (pm3) showed the highest dissimilarity with the parent (0.58). The mutants, pm5 and pm6 were found to be similar to each other (0.65), though they were quite distinct from the parent genotype morphologically. These selected mutants were multiplied up to six generations to attain the desired level of homozygosity for their large scale field evaluation. Plant Tissue Cult. & Biotech. 28(2): 223-236, 2018 (December)

scholarly journals Mutant identification and characterization of the laccase gene family in Arabidopsis

2006 ◽  
Vol 57 (11) ◽  
pp. 2563-2569 ◽  
Author(s):  
Xiaoning Cai ◽  
Elizabeth J. Davis ◽  
Jenny Ballif ◽  
Mingxiang Liang ◽  
Emily Bushman ◽  
...  
Keyword(s):  
Gene Family ◽  
Laccase Gene ◽  
Mutant Identification ◽  
Identification And Characterization

scholarly journals Comparing Platforms for C. elegans Mutant Identification Using High-Throughput Whole-Genome Sequencing

PLoS ONE ◽  
2008 ◽  
Vol 3 (12) ◽  
pp. e4012 ◽  
Author(s):  
Yufeng Shen ◽  
Sumeet Sarin ◽  
Ye Liu ◽  
Oliver Hobert ◽  
Itsik Pe'er
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
High Throughput ◽  
Whole Genome ◽  
C Elegans ◽  
Mutant Identification

scholarly journals ImReMuDF: Redundant Mutants Identification Method Based on Definition and Reference of Variables

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zhenpeng Liu ◽  
Xianwei Yang ◽  
Yi Liu ◽  
Yonggang Zhao ◽  
Xiaofei Li
Keyword(s):  
Flow Analysis ◽  
Mutation Testing ◽  
Industrial Engineering ◽  
Data Flow Analysis ◽  
Identification Rate ◽  
C Programs ◽  
Identification Method ◽  
Maximum Improvement ◽  
Mutant Identification ◽  
The Cost

Mutation testing is an effective defect-based software testing method, but a large number of mutants lead to expensive testing costs, which hinders the application of variation testing in industrial engineering. To solve this problem and enable mutation testing to be applied in industrial engineering, this paper improves the method of identifying redundant mutants based on data flow analysis and proposes the inclusion relationship between redundant mutants, so that the redundancy rate of mutants is reduced. In turn, the cost of mutation testing can be reduced. The redundant mutants identification method based on definition and reference of variables (ImReMuDF) was validated and evaluated using 8 C programs. The minimum improvement in redundant mutant identification rate was 34.0%, and the maximum improvement was 71.3% in the 8 C programs tested, and the verification results showed that the method is feasible and effective and has been improved in reducing redundant mutants and effectively reducing the execution time of mutation testing.

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