Sir Francis Crick would undoubtedly be at the front of the line ordering this fascinating book. Being one of the discoverers of DNA, he would be amazed at how his work has been applied to mankind's most important invention, the computer. In this excellent text, the reader is given a comprehensive introduction to the field of DNA computing. The book emphasizes computational methods to tackle central problems of DNA computing, such as controlling living cells, building patterns, and generating nanomachines. It also includes laboratory-scale human-operated models of computation, as well as a description of the first experiment of DNA computation conducted by Adleman in 1994.

Sir Francis Crick would undoubtedly be at the front of the line ordering this fascinating book. Being one of the discoverers of DNA, he would be amazed at how his work has been applied to mankind's most important invention, the computer. In this excellent text, the reader is given a comprehensive introduction to the field of DNA computing. The book emphasizes computational methods to tackle central problems of DNA computing, such as controlling living cells, building patterns, and generating nanomachines. It also includes laboratory-scale human-operated models of computation, as well as a description of the first experiment of DNA computation conducted by Adleman in 1994.

Protein informatics is a newer name for an already existing discipline. It encompasses the techniques used in bioinformatics and molecular modeling that are related to proteins. While bioinformatics is mainly concerned with the collection, organization, and analysis of biological data, molecular modeling is devoted to representation and manipulation of the structure of proteins.

Protein informatics requires substantial prerequisites on computer science, mathematics, and molecular biology. The approach chosen here, allows a direct and rapid grasp on the subject starting from basic knowledge of algorithm design, calculus, linear algebra, and probability theory.

An Introduction to Protein Informatics, a professional monograph will provide the reader a comprehensive introduction to the field of protein informatics. The text emphasizes mathematical and computational methods to tackle the central problems of alignment, phylogenetic reconstruction, and prediction and sampling of protein structure.

An Introduction to Protein Informatics is designed for a professional audience, composed of researchers and practitioners within bioinformatics, molecular modeling, algorithm design, optimization, and pattern recognition. This book is also suitable as a graduate-level text for students in computer science, mathematics, and biomedicine.

Protein informatics is a newer name for an already existing discipline. It encompasses the techniques used in bioinformatics and molecular modeling that are related to proteins. While bioinformatics is mainly concerned with the collection, organization, and analysis of biological data, molecular modeling is devoted to representation and manipulation of the structure of proteins. Protein informatics requires substantial prerequisites on computer science, mathematics, and molecular biology. The approach chosen here, allows a direct and rapid grasp on the subject starting from basic knowledge of algorithm design, calculus, linear algebra, and probability theory. An Introduction to Protein Informatics, a professional monograph will provide the reader a comprehensive introduction to the field of protein informatics. The text emphasizes mathematical and computational methods to tackle the central problems of alignment, phylogenetic reconstruction, and prediction and sampling of protein structure. An Introduction to Protein Informatics is designed for a professional audience, composed of researchers and practitioners within bioinformatics, molecular modeling, algorithm design, optimization, and pattern recognition. This book is also suitable as a graduate-level text for students in computer science, mathematics, and biomedicine.

Im Mittelpunkt dieses essentials steht eine Einfuhrung in ein bekanntes statistisches Modell, das Hidden-Markov-Modell.Damit koennen Probleme bewaltigt werden, bei denen aus einer Folge von Beobachtungen auf die wahrscheinlichste zustandsspezifische Beschreibung geschlossen werden soll.Die Anwendungen des Hidden-Markov-Modells liegen hauptsachlich in den Bereichen Bioinformatik, Computerlinguistik, maschinelles Lernen und Signalverarbeitung.In diesem Buchlein werden die beiden zentralen Problemstellungen in HMMs behandelt.Das Problem der Inferenz wird mit dem beruhmten Viterbi-Algorithmus geloest, und das Problem der Parameterschatzung wird mit zwei bekannten Methoden angegangen (Erwartungsmaximierung und Baum-Welch).

In diesem essential werden wesentliche Konzepte der Berechenbarkeitstheorie eroertert. Zunachst werden unterschiedliche Modelle der Berechenbarkeit eingefuhrt und ihre semantische Gleichwertigkeit gezeigt. Dieses Resultat steht in Einklang mit der Church-Turing-These, nach der jede intuitiv berechenbare Funktion partiell-rekursiv ist. Neben zentralen Instrumenten der Berechenbarkeit, wie etwa der Goedelisierung von berechenbaren Funktionen und der Existenz universeller berechenbarer Funktionen, stehen unentscheidbare Probleme im Fokus, wie etwa das Halteproblem sowie das Wortproblem fur die Term-Ersetzung. Semi-entscheidbare Mengen werden beleuchtet und die zentralen Satze von Rice und Rice-Shapiro werden skizziert.

Die algebraische Codierungstheorie ist ein neues Teilgebiet der diskreten Mathematik, dessen Ergebnisse bei der sicheren Datenubermittlung angewandt werden. Das Buch stellt im ersten Teil ausfuhrlich die Grundlagen der algebraischen Codierungstheorie dar. Im zweiten Teil untersuchen die Autoren lineare Codes. Dabei legen sie besonderen Wert auf die Decodierung der behandelten Codes anhand eines effizienten Mehrheitsentscheidungsverfahrens.