Udvidet returret til d. 31. januar 2025

Bøger af Jun Sun

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  • af Jun Sun
    2.208,95 kr.

    This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing. It includes real-world data from the authors¿ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter so that these new methods can be readily applied in their own research. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.

  • af Wei Yan, Jun Sun, Yang Zhao, mfl.
    664,95 - 1.010,95 kr.

  • af Jun Sun, Ding-Geng Chen & Yinglin Xia
    1.396,95 - 1.708,95 kr.

  • - Classical and Quantum Perspectives
    af Jun Sun
    842,95 kr.

    Helping readers numerically solve optimization problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. The authors develop their novel QPSO algorithm, a PSO variant motivated from quantum mechanics, and show how to implement it in real-world applications, including inverse problems, digital filter d

  • - Classical and Quantum Perspectives
    af Jun Sun
    1.835,95 kr.

    Helping readers numerically solve optimization problems, this book focuses on the fundamental principles and applications of PSO and QPSO algorithms. The authors develop their novel QPSO algorithm, a PSO variant motivated from quantum mechanics, and show how to implement it in real-world applications, including inverse problems, digital filter d

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