Systems Biology: The Next Frontier for Bioinformatics

Biochemical systems biology augments more traditional disciplines, such as genomics, biochemistry and molecular biology, by championing (i) mathematical and computational modeling; (ii) the application of traditional engineering practices in the analysis of biochemical systems; and in the past decade increasingly (iii) the use of near-comprehensive data sets derived from ‘omics platform technologies, in particular “downstream” technologies relative to genome sequencing, including transcriptomics, proteomics and metabolomics. The future progress in understanding biological principles will increasingly depend on the development of temporal and spatial analytical techniques that will provide high-resolution data for systems analyses. To date, particularly successful we…
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Bioinformatics: Methods Express

Bioinformatics: Methods Express

Bioinformatics: Methods Express is unique . It is a book on bioinformatics that makes sense to non-bioinformaticians.
Bioinformatics: Methods Express helps you answer common questions such as:
*what else is similar to my gene?
*does this protein have any transmembrane regions?
*how do I visualize an alignment between these DNAs?
*where can I find specific transcription factor sequences?

The book provides the clear advice and explicit protocols that non-bioinformaticians need in order to understand what to do – and how to avoid common pitfalls. Each chapter guides you through the major databases and tools with worked examples – all accompanied by sample data files available online.

Topics covered include:
*data access
*sequence searches and alignments
*identification and annotation of features
*the transcriptome
*protein structure and function
*comparisons and phylogeny

Bioinformatics: Methods Express is a comprehensive manual for all wet-bench scientists who need to use bioinformatics – from postgraduate student to principal investigator.

www.scionpublishing.com/bioinformatics contains comprehensive datasets which allow the reader to practise the techniques described in the book.

List Price: $ 125.00

Price: $ 120.77

Analysis of Phylogenetics and Evolution with R (Use R)

The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification.

This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists’ data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments.

Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R’s powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author’s favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters.

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Price: $ 47.25

Probabilistic analysis of gene expression measurements from heterogeneous tissues

Motivation: Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in experiments that focus on studying cell types, e.g. their expression profiles, in isolation. Although sample heterogeneity can be addressed by manual microdissection, prior to conducting experiments, computational treatment on heterogeneous measurements have become a reliable alternative to perform this microdissection in silico. Favoring computation over manual purification has its advantages, such as time consumption, measuring responses of multiple cell types simultaneously, keeping samples intact of external perturbations and unaltered yield of molecular content.

Results: We formalize a probabilistic model, DSection, and show with simulations as well as with real microarray data that DSection attains increased modeling accuracy in terms of (i) estimating cell-type proportions of heterogeneous tissue samples, (ii) estimating replication variance and (iii) identifying differential expression across cell types under various experimental conditions. As our reference we use the corresponding linear regression model, which mirrors the performance of the majority of current non-probabilistic modeling approaches.

Availability and Software: All codes are written in Matlab, and are freely available upon request as well as at the project web page http://www.cs.tut.fi/~erkkila2/. Furthermore, a web-application for DSection exists at http://informatics.systemsbiology.net/DSection.

Bioinformatics – recent issues

An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)

An Introduction to Bioinformatics Algorithms (Computational Molecular Biology)

This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems.

The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively.

An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.

PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Authors’ website.

Rating: (out of 9 reviews)

List Price: $ 63.00

Price: $ 35.99

geWorkbench: an open source platform for integrative genomics.

Publication Date: 2010 May 28 PMID: 20511363
Authors: Floratos, A. – Smith, K. – Ji, Z. – Watkinson, J. – Califano, A.
Journal: Bioinformatics

SUMMARY: geWorkbench (genomics Workbench) is an open source Java desktop application that provides access to an integrated suite of tools for the analysis and visualization of data from a wide range of genomics domains (gene expression, sequence, protein structure, systems biology). More than 70 distinct plug-in modules are currently available implementing both classical analyses (several variants of clustering, classification, homology detection etc) as well as state of the art algorithms for the reverse engineering of regulatory networks and for protein structure prediction, among many others. geWorkbench leverages standards-based middleware technologies to provide seamless access to remote data, annotation and computational servers thus enabling researchers with limited local resources to benefit from available public infrastructure. AVAILABILITY: The project site (http://www.geworkbench.org) includes links to self extracting installers for most OS platforms as well as instructions for building the application from scratch using the source code (which is freely available from the project’s SVN repository). CONTACT: geWorkbench support is available through the end-user and developer forums of the caBIG((R)) Molecular Analysis Tools Knowledge Center, https://cabig-kc.nci.nih.gov/Molecular/forums/.

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