RFLP-kenzy：用于对 RFLP 技术中的关键限制酶进行硅检测的新型生物信息学工具

IF 2.5 Q2 MULTIDISCIPLINARY SCIENCES Beni-Suef University Journal of Basic and Applied Sciences Pub Date : 2024-09-02 DOI:10.1186/s43088-024-00531-8

Nora Laref, Khadidja Belkheir, Mohamed Belazreg, Abdelhadi Hireche

{"title":"RFLP-kenzy：用于对 RFLP 技术中的关键限制酶进行硅检测的新型生物信息学工具","authors":"Nora Laref, Khadidja Belkheir, Mohamed Belazreg, Abdelhadi Hireche","doi":"10.1186/s43088-024-00531-8","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Today, several bioinformatics tools are available for analyzing restriction fragment length data. RFLP-kenzy is a new bioinformatic tool for identifying restriction key enzyme that cut at least 1 sequence and a maximum of n-1 sequence.</p><h3>Results</h3><p>This bioinformatic tool helps researchers to select appropriate enzymes that yield different RFLP patterns, especially from overly identical sequences with single nucleotide mutation or other small variations. By using RFLP-kenzy, multiple DNA sequences could be analyzed simultaneously and the key enzymes list is provided. The present paper also demonstrates the ability of RFLP-kenzy to identify the key enzymes through the analysis of 16S rRNA sequences and the complete genome of various genera of microorganisms.</p><h3>Conclusion</h3><p>From the results, several key enzymes were provided indicating the importance of this new tool in the selection of appropriate restriction enzymes.</p></div>","PeriodicalId":481,"journal":{"name":"Beni-Suef University Journal of Basic and Applied Sciences","volume":"13 1","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bjbas.springeropen.com/counter/pdf/10.1186/s43088-024-00531-8","citationCount":"0","resultStr":"{\"title\":\"RFLP-kenzy: a new bioinformatics tool for in silico detection of key restriction enzyme in RFLP technique\",\"authors\":\"Nora Laref, Khadidja Belkheir, Mohamed Belazreg, Abdelhadi Hireche\",\"doi\":\"10.1186/s43088-024-00531-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Today, several bioinformatics tools are available for analyzing restriction fragment length data. RFLP-kenzy is a new bioinformatic tool for identifying restriction key enzyme that cut at least 1 sequence and a maximum of n-1 sequence.</p><h3>Results</h3><p>This bioinformatic tool helps researchers to select appropriate enzymes that yield different RFLP patterns, especially from overly identical sequences with single nucleotide mutation or other small variations. By using RFLP-kenzy, multiple DNA sequences could be analyzed simultaneously and the key enzymes list is provided. The present paper also demonstrates the ability of RFLP-kenzy to identify the key enzymes through the analysis of 16S rRNA sequences and the complete genome of various genera of microorganisms.</p><h3>Conclusion</h3><p>From the results, several key enzymes were provided indicating the importance of this new tool in the selection of appropriate restriction enzymes.</p></div>\",\"PeriodicalId\":481,\"journal\":{\"name\":\"Beni-Suef University Journal of Basic and Applied Sciences\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://bjbas.springeropen.com/counter/pdf/10.1186/s43088-024-00531-8\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Beni-Suef University Journal of Basic and Applied Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s43088-024-00531-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Beni-Suef University Journal of Basic and Applied Sciences","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s43088-024-00531-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}

引用次数: 0

摘要

背景如今，有多种生物信息学工具可用于分析限制性片段长度数据。RFLP-kenzy是一种新的生物信息学工具，用于识别至少能切割1个序列、最多能切割n-1个序列的限制性关键酶。结果这种生物信息学工具能帮助研究人员选择产生不同RFLP模式的适当酶，特别是从具有单核苷酸突变或其他微小变异的过于相同的序列中选择。使用 RFLP-kenzy 可以同时分析多个 DNA 序列，并提供关键酶列表。本文还通过分析 16S rRNA 序列和各种微生物属的完整基因组，证明了 RFLP-kenzy 识别关键酶的能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

RFLP-kenzy: a new bioinformatics tool for in silico detection of key restriction enzyme in RFLP technique

Background

Today, several bioinformatics tools are available for analyzing restriction fragment length data. RFLP-kenzy is a new bioinformatic tool for identifying restriction key enzyme that cut at least 1 sequence and a maximum of n-1 sequence.

Results

This bioinformatic tool helps researchers to select appropriate enzymes that yield different RFLP patterns, especially from overly identical sequences with single nucleotide mutation or other small variations. By using RFLP-kenzy, multiple DNA sequences could be analyzed simultaneously and the key enzymes list is provided. The present paper also demonstrates the ability of RFLP-kenzy to identify the key enzymes through the analysis of 16S rRNA sequences and the complete genome of various genera of microorganisms.

Conclusion

From the results, several key enzymes were provided indicating the importance of this new tool in the selection of appropriate restriction enzymes.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Beni-Suef University Journal of Basic and Applied Sciences MULTIDISCIPLINARY SCIENCES-

CiteScore

2.60

自引率

0.00%

发文量

期刊介绍： Beni-Suef University Journal of Basic and Applied Sciences (BJBAS) is a peer-reviewed, open-access journal. This journal welcomes submissions of original research, literature reviews, and editorials in its respected fields of fundamental science, applied science (with a particular focus on the fields of applied nanotechnology and biotechnology), medical sciences, pharmaceutical sciences, and engineering. The multidisciplinary aspects of the journal encourage global collaboration between researchers in multiple fields and provide cross-disciplinary dissemination of findings.