Algorithms in Bioinformatics

Algorithms in Bioinformatics

An improved model for statistical alignment (I. Mikls, Z. Toroczkai). Improving profile-profile alignments via log average scoring (N. von ohsen, R. Zimmer). False positive s in genomic map assembly and sequence validation (T. Anantharaman, B. Mishra). Boosting EM for radiation hybrid and genetic mapping (T. Schiex, P. Chabrier, M. Bouchez, D. Milan). Placing probes along the genome using pairwise distance data (W. Casey, B. Mishra, M. Wigler). Comparing a Hidden Markov model and a stochastic context-free grammar (A. Jagota, R. B. Lyngso, C. N. S. Pedersen). Assessing the statistical significance of overrepresented oligonucleotides (A. Denise, M. Rgnier, M. vandenbogaert). Pattern matching and pattern discovery algorithms for protein topologies (J. Viksna, D. Gilbert). Computing linking numbers of a filtration (H. Edelsbrusnner, A. Zomorodian). Side chain-positioning as an integer programming problem (O. Eriksson, Y. Zhou, A. Elofsson). A chemical-distance-based test for positive darwinian selection (T. Pupko, R. Sharan, M. Hasegawa, R. Shamir, D. Graur). Finding a maximum compatible tree for a bounded number of trees with bounded degree is solvable in polynominal time (G. Ganapathysaravanabavan, T. Warnow). Experiments in computing sequences of reversals (A. Bergeron, Franois Strasbourg). Exact-IEBP: a new technique for estimating evolutionary distances between whole genomes (Li-San Wang). Finding an optimal inversion median: experimental results (A. C. Siepel, B. M. E. Moret). Analytic solutions for three-taxon MLMC trees with variable rates across sites (B. Chor, M. Hendy, D. Penny). The performance of phylogenetic methods on trees of bounded diameter (L. nakhleh, U. Roshan, K. St. John, J. Sun, T. Warnow). (1+E)- approximation of sorting by reversals and transpositions (N. Eriksen). On the practical solution of the reversal median problem (A. Caprara). Algorithms for finding gene clusters (S. Heber, J. Stoye). Determination of binding amino acids based on random peptide array screening data (P. J. van der Veen, L. F. A. Wessels, J. W. Sloostra, R. H. Meloen, M. J. T. Reinders, J. Hellendoorn). A simple hyper-geometric approach for discovering putative transcription factor binding sites (Y. Barash, G. Bejerano, N. Friedman). Comparing assemblies using fragments and mate-pairs (D. H. Huson, A. L. Halpern, Z. Lai, E. W. myers, K. Reinert, G. G. Sutton). Author index.

Algorithms in Bioinformatics

Probabilistic Modeling in Bioinformatics and Medical Informatics

Probabilistic Modeling in Bioinformatics and Medical Informatics

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields – the methodology of probabilistic modeling, bioinformatics, and medical informatics – are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies.

Probabilistic Modeling in Bioinformatics and Medical Informatics

Genome Informatics 2010

Genome Informatics 2010

This volume contains 18 peer-reviewed papers based on the presentations at the 10th Annual International Workshop on Bioinformatics and Systems Biology (IBSB 2010) held at Kyoto University from July 26 to July 28, 2010. This workshop started in 2001 as an event for doctoral students and young researchers to present and discuss their research results and approaches in bioinformatics and systems biology. It is part of a collaborative educational program involving leading institutions and leaders committed to the following programs:

Genome Informatics 2010

13th International Conference on Biomedical Engineering

13th International Conference on Biomedical Engineering

This volume presents the proceedings of the13th International Conference on Biomedical Engineering (ICBME2008), help from the 3rd to 6th December 2008 in Singapore. The presented papers reflect the broad scope of the conference including topics like: Artificial Organs, Bioengineering Education, Bioinformatics and Digital Medicine, Biomaterials, Biomechanics, Biomedical Imaging, Biomedical Instrumentation, Biosensors, BioMEMs and Lab-on-Chip, Biosignal Processing, Cardiovascular Bioengineering, Cell and Biomolecular Mechanics, Cellular and Biomolecular Engineering, Clinical Engineering, Computational Bioengineering, Computer-Integrated and Computer-Assisted Surgery, Controlled Drug Delivery, Mechanobiology, Medical Robotics, Micro Nano Biomedical devices and systems, Nanobiotechnology, Neural Systems Engineering, Orthopaedics, Prosthetics and Orthotics, Rehabilitation Engineering and Assistive Technology, Pharmaceutical Sciences and Engineering, Physiological System Modeling, Regenerative Medicine and Tissue Engineering, Telemedicine and Healthcare.

13th International Conference on Biomedical Engineering

Bioinformatics Programming Using Python

Bioinformatics Programming Using Python

Powerful, flexible, and easy to use, Python is an ideal language for building software tools and applications for life science research and development. This unique book shows you how to program with Python, using code examples taken directly from bioinformatics. In a short time, you’ll be using sophisticated techniques and Python modules that are particularly effective for bioinformatics programming.

Bioinformatics Programming Using Python

Applications of Fuzzy Logic in Bioinformatics

Applications of Fuzzy Logic in Bioinformatics

Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques.

Applications of Fuzzy Logic in Bioinformatics

Python Algorithms

Python Algorithms

Python Algorithms explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.,

The book is intended for Python programmers who need to learn about algorithmic problem-solving, or who need a refresher. Students of computer science, or similar programming-related topics, such as bioinformatics, may also find the book to be quite useful.

Python Algorithms