Bioinformatics Research Software Developer at Huttenhower Lab, Harvard University (Boston, MA)

and software development broadly in the areas of bioinformatics, statistical genetics/genomics, and … Bachelor’s or Master’s degree in Computer Science or Bioinformatics or related disciplines; proficient in C/C++…

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DETECT – A Density Estimation Tool for Enzyme ClassificaTion and its application to Plasmodium falciparum.

Publication Date: 2010 May 30 PMID: 20513663
Authors: Hung, S. – Wasmuth, J. – Sanford, C. – Parkinson, J.
Journal: Bioinformatics

MOTIVATION: A major challenge in genomics is the accurate annotation of component genes. Enzymes are typically predicted using homology-based search methods, where the membership of a protein to an enzyme family is based on single-sequence comparisons. As such, these methods are often error prone and lack useful measures of reliability for the prediction. RESULTS: Here we present DETECT, a probabilistic method for enzyme prediction that accounts for the sequence diversity across enzyme families. By comparing the global alignment scores of an unknown protein to those of all known enzymes, an integrated likelihood score (ILS) can be readily calculated, ranking the reaction classes relevant for that protein. Comparisons to BLAST reveal significant improvements in enzyme annotation accuracy. Applied to Plasmodium falciparum, we identify potential annotation errors and predict novel enzymes of therapeutic interest. AVAILABILITY: A standalone application is available from the website: http://www.compsysbio.org/projects/DETECT/. CONTACT: john.parkinson@utoronto.ca Supplmentary information: Supplementary data are available at Bioinformatics online.

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Bioinformatics Research Software Developer – Huttenhower Lab, Harvard University – Boston, MA

in the areas of bioinformatics, statistical genetics… be part of a team of developers in the HSPH Bioinformatics Core and the Program in Quantitative Genomics…

From PhDs.org – 03 Jun 2010 02:22:27 GMT
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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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Software Engineer – Bioinformatics at Edpsi (New York, NY)

clinical applications. * Prior involvement or interest in bioinformatics or cancer genomics domain a plus. * Must be … Must have biology, bioinformatics experience Java, SQL, HTML, bioinformatics…

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