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In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology. The book has a substantial "computational biology without formulas" component that presents the biological and computational ideas in a relatively simple manner. This makes the material accessible to computer scientists without biological training, as well as to biologists with limited background in computer science. Computational Molecular Biology series Computer science and mathematics are transforming molecular biology from an informational to a computational science. Drawing on computational, statistical, experimental, and technological methods, the new discipline of computational molecular biology is dramatically increasing the discovery of new technologies and tools for molecular biology. The new MIT Press Computational Molecular Biology series provides a unique venue for the rapid publication of monographs, textbooks, edited collections, reference works, and lecture notes of the highest quality.
Biomathematics. Biometry. Biostatistics --- Molecular biology --- DNA microarrays. --- Algorithms. --- Mathematical models. --- DNA microarrays --- Puces à ADN --- Algorithms --- Molecular biochemistry --- Molecular biophysics --- Biochemistry --- Biophysics --- Biomolecules --- Systems biology --- DNA biochips --- Microarrays, DNA --- Biochips --- Immobilized nucleic acids --- Algorism --- Algebra --- Arithmetic --- Mathematical models --- Foundations --- Molecular biology - Mathematical models --- BIOMEDICAL SCIENCES/Quantitative Biology
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Cet ouvrage est la traduction française d'un texte désormais considéré comme une référence dans le domaine émergent de la bio-informatique moléculaire. Pavel A. Pevzner y traite des cartes génétiques, du problème de comparaison de séquences et d'alignement en passant par les puces à ADN et le réarrangement génomique. Il couvre ainsi une grande variété de thèmes relatifs aux traitements algorithmiques et combinatoires de questions issues de la bioinformatique moléculaire et de la biotechnologie. Évitant, dans la mesure du possible, les considérations théoriques et les formules complexes, l'exposé privilégie la présentation des notions de biologie et d'algorithmique qui interviennent de manière fondamentale dans les méthodes étudiées. Le contenu de cet ouvrage devient donc accessible aux spécialistes de l'informatique qui n'ont pas de formation spécifique en biologie comme aux biologistes ayant des connaissances limitées en informatique.
Computational biology --- Bioinformatics --- Bio-informatique --- Chemistry. --- Biotechnology. --- Genetic engineering. --- Data structures (Computer science). --- Computer software. --- Bioinformatics. --- Biology --- Genetic Engineering. --- Data Structures. --- Algorithm Analysis and Problem Complexity. --- Computer Appl. in Life Sciences. --- Mechanical Engineering --- Health & Biological Sciences --- Engineering & Applied Sciences --- Biophysics --- Bioengineering --- Data processing. --- Molecular biology. --- Biology. --- EPUB-LIV-FT LIVCHIMI SPRINGER-B --- Computational Biology. --- Life sciences --- Life (Biology) --- Natural history --- Molecular biochemistry --- Molecular biophysics --- Biochemistry --- Biomolecules --- Systems biology
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"The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors - each a leading scientist - engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers"--
Biomathematics. Biometry. Biostatistics --- Bioinformatique --- Bioinformatics, --- Bioinformatics --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Data processing --- biology --- genomes --- Phylogeny --- Évolution --- evolution --- Transcription --- transcription --- Bioinformatics. --- evolution. --- transcription. --- Computational biology.
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Basic Sciences. Bioinformatics -- Bioinformatics (General). --- Bioinformatics --- Computational biology --- Computer algorithms --- Computational Biology --- Algorithms --- 57.087 --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Systems biology --- Algorithm --- Bio-Informatics --- Biology, Computational --- Computational Molecular Biology --- Molecular Biology, Computational --- Bio Informatics --- Bio-Informatic --- Bioinformatic --- Biologies, Computational Molecular --- Biology, Computational Molecular --- Computational Molecular Biologies --- Molecular Biologies, Computational --- Genomics --- 57.087 Methods and techniques for parameter estimation. Recording of biological data --- Methods and techniques for parameter estimation. Recording of biological data --- Mathematics --- Data processing --- Computational Chemistry --- Computational biology. --- Computer algorithms. --- Computational Biology. --- Algorithms. --- Mathematics. --- Cluster Analysis --- Sequence Analysis, DNA. --- Bioinformatique --- Algorithmes
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The computational education of biologists is changing to prepare students for facing the complex datasets of today's life science research. In this concise textbook, the authors' fresh pedagogical approaches lead biology students from first principles towards computational thinking. A team of renowned bioinformaticians take innovative routes to introduce computational ideas in the context of real biological problems. Intuitive explanations promote deep understanding, using little mathematical formalism. Self-contained chapters show how computational procedures are developed and applied to central topics in bioinformatics and genomics, such as the genetic basis of disease, genome evolution or the tree of life concept. Using bioinformatic resources requires a basic understanding of what bioinformatics is and what it can do. Rather than just presenting tools, the authors - each a leading scientist - engage the students' problem-solving skills, preparing them to meet the computational challenges of their life science careers.
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Complex analysis --- Biomathematics. Biometry. Biostatistics --- Molecular biology --- Biology --- Biotechnology --- Computer science --- Computer. Automation --- complexe analyse (wiskunde) --- bio-informatica --- biologie --- informatica --- biotechnologie --- genetische manipulatie --- biometrie --- database management --- programmatielogica --- moleculaire biologie
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Computer science --- Bioinformatics --- Algorithms --- Bio-informatique --- Algorithmes --- Bioinformatics. --- Algorithms. --- 577.2 --- 681.3*J3 <043> --- Molecular bases of life. Molecular biology --- Life and medical sciences (Computer applications)--Dissertaties --- 681.3*J3 <043> Life and medical sciences (Computer applications)--Dissertaties --- 577.2 Molecular bases of life. Molecular biology --- Bio-informatics --- Biological informatics --- Biology --- Information science --- Computational biology --- Systems biology --- Algorism --- Algebra --- Arithmetic --- Data processing --- Foundations
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Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed MOOC on Coursera, this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of both biology and computer science. Each chapter begins with a central biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on the Rosalind Bioinformatics Textbook Track. A website augments the textbook by providing additional educational materials, including video lectures and PowerPoint slides. -- Book website.
Bioinformatics --- Bioinformatics. --- Computational biology. --- Computer algorithms. --- Mathematics.
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Bioinformatics Algorithms: an Active Learning Approach is one of the first textbooks to emerge from the recent Massive Open Online Course (MOOC) revolution. A light-hearted and analogy-filled companion to the authors' acclaimed MOOC on Coursera, this book presents students with a dynamic approach to learning bioinformatics. It strikes a unique balance between practical challenges in modern biology and fundamental algorithmic ideas, thus capturing the interest of students of both biology and computer science. Each chapter begins with a central biological question, such as "Are There Fragile Regions in the Human Genome?" or "Which DNA Patterns Play the Role of Molecular Clocks?" and then steadily develops the algorithmic sophistication required to answer this question. Hundreds of exercises are incorporated directly into the text as soon as they are needed; readers can test their knowledge through automated coding challenges on the Rosalind Bioinformatics Textbook Track. A website augments the textbook by providing additional educational materials, including video lectures and PowerPoint slides. -- Book website.
Bioinformatics. --- Computational biology. --- Computer algorithms.
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Cet ouvrage est la traduction française d'un texte désormais considéré comme une référence dans le domaine émergent de la bio-informatique moléculaire. Pavel A. Pevzner y traite des cartes génétiques, du problème de comparaison de séquences et d'alignement en passant par les puces à ADN et le réarrangement génomique. Il couvre ainsi une grande variété de thèmes relatifs aux traitements algorithmiques et combinatoires de questions issues de la bioinformatique moléculaire et de la biotechnologie. Évitant, dans la mesure du possible, les considérations théoriques et les formules complexes, l'exposé privilégie la présentation des notions de biologie et d'algorithmique qui interviennent de manière fondamentale dans les méthodes étudiées. Le contenu de cet ouvrage devient donc accessible aux spécialistes de l'informatique qui n'ont pas de formation spécifique en biologie comme aux biologistes ayant des connaissances limitées en informatique.
Complex analysis --- Biomathematics. Biometry. Biostatistics --- Molecular biology --- Biology --- Biotechnology --- Computer science --- Computer. Automation --- complexe analyse (wiskunde) --- bio-informatica --- biologie --- informatica --- biotechnologie --- genetische manipulatie --- biometrie --- database management --- programmatielogica --- moleculaire biologie
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