Bioinformatics / Software Engineer at Kforce Technology Staffing (Cambridge, MA)

This candidate will join a Scientific Informatics Systems Group, and work closely with scientists to provide informatics systems to support drug discovery process, specifically in the area of Metabolism and Pharmacokinetics studies.

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Functional Informatics in Drug Discovery

Product Description
Integrating various technologies with informational systems provides vast improvements to the overall research and development that occur in the biopharmaceutical industry. One of the first books to explore this area, Functional Informatics in Drug Discovery examines all aspects of technology integration and information flow in a biopharmaceutical enterprise and outlines the specific technologies used at various stages of drug development.

With contributions from leaders in academia, information technology, and the pharmaceutical industry, each chapter illustrates how a particular area of biological science can benefit from the tools of informatics. The book first looks at intelligent automation, neurally based computational tools, and pharmacodynamic (PD) biomarkers. It then reviews a variety of novel technologies and approaches presently used in drug discovery at Johnson & Johnson. The text also describes how informatics can advance antibody technology and drug development for oncology. After focusing on forward genetic and reverse genetic strategies to identify relevant target genes for drug discovery, the book explains proteomic expression profiling and explores the application of laser microdissection in transcriptomics.

Taking a systematic approach, this volume examines the impact of informatics tools on various areas in biopharmaceuticals by presenting in-depth analyses of emerging trends and future opportunities.

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Chemoinformatics: Theory, Practice, & Products

Product Description

Chemoinformatics: Theory, Practice & Products covers theory, commercially available packages and applications of Chemoinformatics. Chemoinformatics is broadly defined as the use of information technology to assist in the acquisition, analysis and management of data and information relating to chemical compounds and their properties. This ranges from molecular modelling, to reactions, to spectra, to structure-activity relationships associated with chemicals. Computational scientists, chemists, and biologists all rely on the rapidly evolving field of Chemoinformatics. Chemoinformatics: Theory, Practice & Products is an essential handbook for determining the right Chemoinformatics method or technology to use. There has been an explosion of new Chemoinformatics tools and techniques. Each technique has its own utility, scope, and limitations, as well as meeting resistance to use by experimentalists. The purpose of Chemoinformatics: Theory, Practice & Products is to provide computational scientists, medicinal chemists and biologists with unique practical information and the underlying theories relating to modern Chemoinformatics and related drug discovery informatics technologies.

The book also provides a summary of currently available, state-of-the-art, commercial Chemoinformatics products, with a specific focus on databases, toolkits, and modelling technologies designed for drug discovery. It will be broadly useful as a reference text for experimentalists wishing to rapidly navigate the expanding field, as well as the more expert computational scientists wishing to stay up to date.

It is primarily intended for applied researchers from the chemical and pharmaceutical industry, academic investigators, and graduate students.

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A CROC Stronger than ROC: Measuring, Visualizing, and Optimizing Early Retrieval.

Publication Date: 2010 Apr 7 PMID: 20378557
Authors: Swamidass, S. J. – Azencott, C. A. – Daily, K. – Baldi, P.
Journal: Bioinformatics

MOTIVATION: The performance of classifiers is often assessed using ROC (or AC) curves and the corresponding areas under the curves (AUCs). However, in many fundamental problems ranging from information retrieval to drug discovery, only the very top of the ranked list of predictions is of any interest and ROCs and AUCs are not very useful. New metrics, visualizations, and optimization tools are needed to address this “early retrieval” problem. RESULTS: To address the early retrieval problem, we develop the general CROC (Concentrated ROC) framework. In this framework, any relevant portion of the ROC (or AC) curve is magnified smoothly by an appropriate continuous transformation of the coordinates with a corresponding magnification factor. Appropriate families of magnification functions confined to the unit square are derived and their properties are analyzed together with the resulting CROC curves. The area under the CROC curve (AUC[CROC]) can be used to assess early retrieval. The general framework is demonstrated on a drug discovery problem and used to discriminate more accurately the early retrieval performance of five different predictors. From this framework, we propose a novel metric and visualization-the CROC(exp), an exponential transform of the ROC curve-as an alternative to other methods. The CROC(exp) provides a principled, flexible, and effective way for measuring and visualizing early retrieval performance with excellent statistical power. Corresponding methods for optimizing early retrieval are also described in the Appendix. AVAILABILITY: Datasets are publicly available. Python code and command-line utilities implementing CROC curves and metrics is available at http://pypi.python.org/pypi/CROC/. CONTACT: pfbaldi@ics.uci.edu.

post to: CiteULike

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Protein Networks and Pathway Analysis

Product Description

From the beginning of the OMICs biology era, science has been pursuing the reduction of the complex “genome-wide” assays in order to understand the essential biology that lies beneath it. In Protein Networks and Pathway Analysis, expert practitioners present a compilation of methods of functional data analysis, often referred to as “systems biology,” and its applications in drug discovery, medicine and basic disease research. The volume is divided into three convenient sections, covering the elucidation of protein, compound and gene interactions, analytical tools, including networks, interactome and ontologies, and applications of functional analysis. As a volume in the highly successful Methods in Molecular Biology™ series, this work provides detailed descriptions and hands-on implementation advice. Authoritative and cutting-edge, Protein Networks and Pathway Analysis presents both “wet lab” experimental methods and computational tools in order to cover a broad spectrum of issues in this fascinating new field.

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