Scientific Computation

Product Description
Using real-life applications, this graduate-level textbook introduces different mathematical methods of scientific computation to solve minimization problems using examples ranging from locating an aircraft, finding the best time to replace a computer, analyzing developments on the stock market, and constructing phylogenetic trees. The textbook focuses on several methods, including nonlinear least squares with confidence analysis, singular value decomposition, best basis, dynamic programming, linear programming, and various optimization procedures. Each chapter solves several realistic problems, introducing the modeling optimization techniques and simulation as required. This allows readers to see how the methods are put to use, making it easier to grasp the basic ideas. There are also worked examples, practical notes, and background materials to help the reader understand the topics covered. Interactive exercises are available at www.cambridge.org/9780521849890.

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Combinatorial Pattern Matching: 17th Annual Symposium, CPM 2006, Barcelona, Spain, July 5-7, 2006, Proceedings

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This book constitutes the refereed proceedings of the 17th Annual Symposium on Combinatorial Pattern Matching, CPM 2006, held in Barcelona, Spain in July 2006.

The 33 revised full papers presented together with 3 invited talks were carefully reviewed and selected from 88 submissions. The papers are organized in topical sections on data structures, indexing data structures, probabilistic and algebraic techniques, applications in molecular biology, string matching, data compression, and dynamic programming.

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Structural Bioinformatics: An Algorithmic Approach

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The Beauty of Protein Structures and the Mathematics behind Structural Bioinformatics
Providing the framework for a one-semester undergraduate course, Structural Bioinformatics: An Algorithmic Approach shows how to apply key algorithms to solve problems related to macromolecular structure.

Helps Students Go Further in Their Study of Structural Biology
Following some introductory material in the first few chapters, the text solves the longest common subsequence problem using dynamic programming and explains the science models for the Nussinov and MFOLD algorithms. It then reviews sequence alignment, along with the basic mathematical calculations needed for measuring the geometric properties of macromolecules. After looking at how coordinate transformations facilitate the translation and rotation of molecules in a 3D space, the author introduces structural comparison techniques, superposition algorithms, and algorithms that compare relationships within a protein. The final chapter explores how regression and classification are becoming more useful in protein analysis and drug design.

At the Crossroads of Biology, Mathematics, and Computer Science
Connecting biology, mathematics, and computer science, this practical text presents various bioinformatics topics and problems within a scientific methodology that emphasizes nature (the source of empirical observations), science (the mathematical modeling of the natural process), and computation (the science of calculating predictions and mathematical objects based on mathematical models).

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Job Posting – Systems and Algorithms Engineer at DNA startup – Palo Alto, CA

Does building great things run in your DNA?

DNAnexus is a start-up in biocomputation aiming to transform the future of genomic analysis. The rapid advancement of DNA sequencing technologies will one day enable one of the holy grails of medicine: the personal genome. But it is also unleashing a torrent of data that needs to be managed and analyzed. DNAnexus is leveraging modern web technologies on a cloud computing infrastructure to create a compute platform for the genome era. We are backed by a collection of leading investors, including early-stage VC First Round Capital.

DNAnexus comprises a team of individuals that include MIT alumni, Stanford PhDs in computational genomics, and Professors in Computer Science, Genetics, and Pathology, and we’re passionate about changing the future of DNA analysis and genetics.

Interested in joining in our effort? We’re currently looking for individuals that fit the following profiles:

Systems and Algorithms Genius

DNAnexus is recruiting an exceptional developer to join the team in designing and implementing methods for large scale analysis of DNA sequence data. The ideal candidate would be extremely strong in building complex models for deciphering noisy datasets, and be comfortable with the idea of channeling Petabytes of data and distributing workloads onto 1000s of machines. Also, the following should resonate with you:

- You are fluent in C/C++ and understand the implications of your coding style down to the level of machine code.
- You are comfortable with distributed systems, from consistency and synchronization in multi-threaded applications to concurrent database design, cluster computing, and distributed file systems.
- You could write your own generic balanced binary trees and suffix trees. Dynamic programming and divide and conquer come easily to you. You understand the intricacies of dynamic hash table design.
- You have practical experience with Bayesian modeling and inference, machine learning, statistics, and optimization.

A background in bioinformatics or DNA sequence analysis is a plus, not a necessity, but you must be comfortable learning a new domain quickly. If you enjoy working in a fast-moving startup environment and want to apply your talent to an area of great significance, DNAnexus is for you!

Location: Palo Alto, CA
More info: http://dnanexus.com/careers