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020 _a9789811258992
_q(ebook)
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_q(ebook)
020 _z9811258988
_q(hbk.)
020 _z9789811258985
_q(hbk.)
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082 0 4 _a570.285
049 _aMAIN
245 0 0 _aPractical bioinformatics for beginners :
_bfrom raw sequence analysis to machine learning applications /
_cedited by Lloyd Low, Martti Tammi.
260 _aSingapore :
_bWorld Scientific,
_c2023.
300 _a1 online resource (268 p.).
504 _aIncludes bibliographical references and index.
505 0 _aIntroduction to next generation sequencing technologies / Lloyd Low and Martti T Tammi -- Primer on Linux / Adeel Malik and Muhammad Farhan Sjaugi -- Inspection of sequence quality / Kwong Qi Bin, Ong Ai Ling, Heng Huey Ying and Martti T Tammi -- Alignment of sequenced reads / Akzam Saidin --- Establish a research workflow / Joel Low Zi-Bin and Heng Huey Ying -- De novo assembly of a genome / Joel Low Zi-Bin, Martti T Tammi and Wai Yee Low -- Exome sequencing / Setia Pramana, Kwong Qi Bin, Heng Huey Ying, Nuha Hassim and Ong Ai Ling -- Transcriptomics / Yan Ren, Akzam Saidin and Wai Yee Low -- Metagenomics / Sim Chun Hock, Kee Shao Yong, Ong Ai Ling, Heng Huey Ying and Teh Chee Keng -- Applications of NGS data / Teh Chee Keng, Ong Ai Ling and Kwong Qi Bin -- Predicting human enhancers with machine learning / Callum MacPhillamy and Wai Yee Low.
520 _a"Next-Generation Sequencing (NGS) is increasingly common and has applications in various fields such as clinical diagnosis, animal and plant breeding, and conservation of species. This incredible tool has become cost-effective. However, it generates a deluge of sequence data that requires efficient analysis. The highly sought-after skills in computational and statistical analyses include machine learning and, are essential for successful research within a wide range of specializations, such as identifying causes of cancer, vaccine design, new antibiotics, drug development, personalized medicine, and increased crop yields in agriculture. This invaluable book provides step-by-step guides to complex topics that make it easy for readers to perform specific analyses, from raw sequenced data to answer important biological questions using machine learning methods. It is an excellent hands-on material for lecturers who conduct courses in bioinformatics and as reference material for professionals. The chapters are standalone recipes making them suitable for readers who wish to self-learn selected topics. Readers gain the essential skills necessary to work on sequenced data from NGS platforms; hence, making themselves more attractive to employers who need skilled bioinformaticians"--
_cPublisher's website.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat reader.
650 0 _aBioinformatics.
655 0 _aElectronic books.
856 4 0 _uhttps://www.worldscientific.com/worldscibooks/10.1142/12908#t=toc
942 _cE-BOOK
999 _c49744
_d49744