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Introduction to Computational Biology: Maps, Sequences and Genomes Chapman & HallCRC Interdisciplinary Statistics 1st Edition
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Introduction to Computational Biology: Maps, Sequences and Genomes Chapman & HallCRC Interdisciplinary Statistics 1st Edition
Introduction to Computational Biology explores a new area of expertise that emerged from the combination of biological and information sciences, exposing the reader to the fascinating structure of biological data and explaining how to treat related combinatorial and statistical problems.
Introduction to Computational Biology: Maps, Sequences and Genomes Chapman & HallCRC Interdisciplinary Statistics 1st Edition
Item #: 47487296

Introduction to Computational Biology: Maps, Sequences and Genomes Chapman & HallCRC Interdisciplinary Statistics 1st Edition

Item #: 47487296

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Introduction to Computational Biology explores a new area of expertise that emerged from the combination of biological and information sciences, exposing the reader to the fascinating structure of biological data and explaining how to treat related combinatorial and statistical problems.
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What Stands Out

Interdisciplinary Approach
Combines statistics, biology, and computer science, making it ideal for students and professionals looking to understand complex biological data analysis.
Comprehensive Coverage
Thoroughly addresses maps, sequences, and genomes, providing a well-rounded foundation for tackling various computational biology challenges.
Practical Insights
Offers real-world applications and case studies, enhancing the learning experience and equipping readers with practical skills for research or industry roles.

Product Details

Discover a wide selection of Introduction to Computational Biology: Maps, Sequences and Genomes books at Ubuy Réunion. Shop now and explore the world of computational biology!
Item Weight3 lbs (1.36 kg)

Who Should Buy?

Suitable For
  • Students of Biology

    Ideal for biology students interested in computational techniques and their applications in biological data analysis and research.

  • Data Scientists

    Suitable for data scientists looking to expand their knowledge in biological data modeling and computational biology techniques.

  • Researchers

    Beneficial for researchers in genomics and bioinformatics needing a solid foundation in computational biology principles.

Not Suitable For
  • Beginners in Biology

    Not suitable for complete beginners in biology as it assumes some prior knowledge of biological concepts and terminology.

  • Casual Readers

    This book is technical and may not satisfy casual readers looking for light reading on biology topics.

  • Experienced Statisticians

    Advanced statisticians may find the content too basic and not sufficiently challenging for their expertise level.

Product Description

Introduction to Computational Biology: Maps, Sequences and Genomes Chapman & HallCRC Interdisciplinary Statistics 1st Edition

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Customer Questions & Answers

  • Question: What topics are covered in 'Introduction to Computational Biology: Maps, Sequences and Genomes'?

    Answer: This book delves into various essential topics within computational biology, including genomic mapping, sequence alignment, evolutionary biology, and the analysis of biological data. It serves as an introduction to the computational techniques used in modern biology, making it ideal for students and professionals alike. Readers can expect to gain insights into how algorithms and statistical methods are applied in biological research and genetic analysis.
  • Question: Who is the target audience for this book?

    Answer: 'Introduction to Computational Biology' is primarily aimed at undergraduate and graduate students in the fields of biology, bioinformatics, and statistics. However, it is also suitable for researchers and professionals looking to enhance their understanding of computational methods in biology. Its interdisciplinary approach makes it a valuable resource for a wide range of audiences interested in the integration of technology and biological sciences.
  • Question: Is this book suitable for beginners in computational biology?

    Answer: Yes, the book is designed to be accessible even for readers who are new to computational biology. It starts with fundamental concepts and gradually introduces more complex topics, ensuring a steady learning curve. Beginners can benefit from clear explanations and illustrative examples, allowing them to build a solid foundation in both biology and computational methods.
  • Question: How does this book incorporate statistical methods into computational biology?

    Answer: The text effectively integrates statistical concepts to analyze biological data, which is a critical aspect of computational biology. It covers statistical models, hypothesis testing, and data visualization techniques tailored for biological datasets. By applying these statistical methods, readers learn how to interpret research findings and make informed conclusions in their studies and work.
  • Question: Does the Kindle edition offer any interactive features?

    Answer: The Kindle edition of 'Introduction to Computational Biology' includes features such as text searching, adjustable font sizes, and note-taking functionalities, enhancing the reading experience. These features allow readers to easily navigate through content and highlight key information, making study sessions more efficient and enjoyable.
  • Question: Are there exercises or practical applications included in the book?

    Answer: Yes, the book contains exercises and examples that allow readers to apply the concepts they learn. These practical applications encourage active engagement with the material and facilitate a deeper understanding of computational techniques in biology. Readers can work through these exercises to solidify their knowledge and enhance their problem-solving skills in real-world scenarios.
  • Question: What is the significance of genomic mapping discussed in the book?

    Answer: Genomic mapping is crucial as it lays the foundation for understanding the structure and function of genomes. The book discusses various mapping techniques that help identify genes and their locations, which is essential for genetic research and biotechnology applications. By mastering genomic mapping, readers can contribute to advancements in personalized medicine, agriculture, and more.
  • Question: How does the book address the topic of sequence alignment?

    Answer: Sequence alignment is a significant topic covered extensively in the book. It discusses various algorithms and methods used to compare DNA, RNA, and protein sequences, which is essential for evolutionary studies and genomic analysis. Mastering sequence alignment techniques allows researchers to infer evolutionary relationships and identify functional motifs in genes, providing critical insights in biological research.
  • Question: Can this book be used as a reference guide for research projects?

    Answer: Absolutely, 'Introduction to Computational Biology' serves as an excellent reference guide for research projects. Its comprehensive coverage of computational techniques and statistical methods provides valuable insights for data analysis and interpretation in biological research. Researchers can refer to specific chapters or sections to enhance their methodologies and support their findings with solid theoretical backing.
  • Question: Where can I buy 'Introduction to Computational Biology: Maps, Sequences and Genomes' in Réunion?

    Answer: You can purchase 'Introduction to Computational Biology: Maps, Sequences and Genomes' on Ubuy in Réunion. Ubuy offers a wide range of books and ensures easy access to academic resources like this. Their platform is designed to cater to the needs of readers looking for specialized literature in various fields, including computational biology.

Probability & Statistics Editorial Review

**** "Introduction to Computational Biology: Maps, Sequences and Genomes" by Waterman is highly regarded as a foundational text for anyone delving into the field of bioinformatics. Originally published in 1995, it has stood the test of time, offering a comprehensive discussion on essential topics that remain relevant today, such as the Smith-Waterman algorithm, DNA sequence reConstruction from digest problems, and the transition into shotgun sequencing. Readers appreciate Waterman's ability to interweave theory with practical applications, presenting mathematical concepts like dynamic programming and multiple alignments in an articulate manner. The logical flow of the chapters facilitates an understanding of complex algorithms and their interconnections, making each topic accessible without becoming overwhelmingly detailed. However, the review points out that some sections, particularly those on RNA structure and phylogenetic trees, lack the continuity and depth found in earlier chapters. Despite this, Waterman’s emphasis on mathematical rigor and his way of framing the subject matter ensure that readers can engage critically with the content, asking the right questions as they advance in the field. Additionally, the book’s bibliography is lauded for not just listing sources but for contextualizing their contributions to the subject matter, a feature that enhances its value as a reference. Overall, the text is recommended for its thorough coverage of computational biology techniques, making it a valuable resource for both learning and research purposes. **

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Pros

  • Comprehensive discussion of foundational bioinformatics topics.
  • Clear and logical progression through complex algorithms.
  • Strong emphasis on the application of mathematics in biology.
  • Well-written sections on critical concepts such as dynamic programming.
  • Useful bibliography that provides context for further reading.

Cons

  • Some chapters, particularly on RNA structure, lack continuity.

Product Price History

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€ 79

Order now and get it around Thursday, July 02

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Features & Benefits

  • Exponential growth in information-packed databases has led to the emergence of computational biology.
  • The book describes mathematical structure of biological data such as sequences and chromosomes.
  • It covers topics like DNA sequencing, comparison of sequences, pattern counts, RNA secondary structure, and evolutionary history.
  • Written to describe mathematical formulation and development.
  • Sets the stage for interdisciplinary work in biology.
  • Great resource for those interested in exploring the intersection of biology and information sciences.