Bioinformatics. The Machine Learning Approach.pdf

Bioinformatics. The Machine Learning Approach

Soren Brunak

An unprecedented wealth of data is being generated by genome sequencing projects and other experimental efforts to determine the structure and function of biological molecules. The demands and opportunities for interpreting these data are expanding more than ever. Bioinformatics is the development and application of computer methods for management, analysis, interpretation, and prediction, as well as for the design of experiments. Machine learning approaches (e.g., neural networks, hidden Markov models, and belief networks) are ideally suited for areas in which there is a lot of data but little theory, as in molecular biology. The goal in machine learning is to extract useful information from a body by building good probabilistic models - and to automate the process as much as possible.Pierre Baldi and Soren Brunak present the key machine learning approaches and apply them to the computational problems encountered in the analysis of biological data. This book is aimed both at biologists and biochemists who need to understand new data-driven algorithms and at those with a primary background in physics, mathematics, statistics, or computer science who need to know more about applications in molecular biology. This edition contains expanded coverage of probabilistic graphical models and the applications of neural networks, as well as a new chapter on microarrays and gene expression. The entire text has been extensively revised.

Bioinformatics, second edition: The Machine …

6.51 MB Taille du fichier
9780262025065 ISBN
Bioinformatics. The Machine Learning Approach.pdf

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Sofya Voigtuh

[PDF] Bioinformatics The Machine Learning …

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Mattio Müllers

Machine Learning in Bioinformatics | Bioinformatics ... Machine learning techniques are increasingly being used to address problems in computational biology and bioinformatics. Novel computational techniques to analyze high throughput data in the form of sequences, gene and protein expressions, pathways, and images are becoming vital for understanding diseases and future drug discovery. Machine learning techniques such as Markov models, support

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Noels Schulzen

Bioinformatics: The Machine Learning Approach …

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Jason Leghmann

This workshop is intended to provide an introduction to machine learning and its application to bioinformatics. This workshop is not intended for machine learning experts. Instead it targets biologists or other life scientists who are wanting to understand what machine learning, what it can do and how it can be used for a variety of bioinformatic or medical informatics applications. Students Machine Learning in Bioinformatics | Bioinformatics ...

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Jessica Kolhmann

Dec 14, 2019 ... Here we would use machine learning to classify genes of E. Coli bacteria. Let us understand the basics of Genetics. DNA or deoxyribonucleic ...