A tabu search algorithm for maximum parsimony phylogeny inference

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This digital document is a journal article from European Journal of Operational Research, published by Elsevier in 2007. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
Phylogeny reconstruction is too complex a combinatorial problem for an exhaustive search, because the number of possible solutions increases exponentially with the number of taxa involved. In this paper, we adopt the parsimony principle and design a tabu search algorithm for finding a most parsimonious phylogeny tree. A special array structure is employed to represent the topology of trees and to generate the neighboring trees. We test the proposed tabu search algorithm on randomly selected data sets obtained from nuclear ribosomal DNA sequence data. The experiments show that our algorithm explores fewer trees to reach the optimal one than the commonly used program ”dnapenny” (branch-and-bound based) while it generates much more accurate results than the default options of the program ”dnapars” (heuristic search based). The percentage of search space needed to find the best solution for our algorithm decreased rapidly as the number of taxa increased. For a 20-taxon phylogeny problem, it needs on average to examine only 3.92×10^-^1^5% of the sample space.

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Bioinformatics: Tools and Applications

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Bioinformatics is a relatively new field of research. It evolved from the requirement to process, characterize, and apply the information being produced by DNA sequencing technology. The production of DNA sequence data continues to grow exponentially. At the same time, improved bioinformatics such as faster DNA sequence search methods have been combined with increasingly powerful computer systems to process this information. Methods are being developed for the ever more detailed quantification of gene expression, providing an insight into the function of the newly discovered genes, while molecular genetic tools provide a link between these genes and heritable traits. Genetic tests are now available to determine the likelihood of suffering specific ailments and can predict how plant cultivars may respond to the environment. The steps in the translation of the genetic blueprint to the observed phenotype is being increasingly understood through proteome, metabolome and phenome analysis, all underpinned by advances in bioinformatics. Bioinformatics is becoming increasingly central to the study of biology, and a day at a computer can often save a year or more in the laboratory.

The volume is intended for graduate-level biology students as well as researchers who wish to gain a better understanding of applied bioinformatics and who wish to use bioinformatics technologies to assist in their research. The volume would also be of value to bioinformatics developers, particularly those from a computing background, who would like to understand the application of computational tools for biological research. Each chapter would include a comprehensive introduction giving an overview of the fundamentals, aimed at introducing graduate students and researchers from diverse backgrounds to the field and bring them up-to-date on the current state of knowledge. To accommodate the broad range of topics in applied bioinformatics, chapters have been grouped into themes: gene and genome analysis, molecular genetic analysis, gene expression analysis, protein and proteome analysis, metabolome analysis, phenome data analysis, literature mining and bioinformatics tool development. Each chapter and theme provides an introduction to the biology behind the data describes the requirements for data processing and details some of the methods applied to the data to enhance biological understanding.

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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