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  • CPTI eProtein Newsletter Researcher Spotlight feature

    November 9th, 2010, 11:30 am

    My work, and links to my tools, have been featured in the clinical proteomics technology initiative (CPTI) eProtein newsletter, “Researcher Spotlight: Enabling the Search for Novel Cancer Protein Variants.” Check it out, and give the Peptide Sequence Database (PepSeqDB), Peptide Arbiter by Machine Learning (PepArML) Meta-Search Engine, and PeptideMapper tools a try.

    The PepSeqDB fasta sequence databases provide a comprehensive enumeration of (putative) peptide sequences from ESTs, mRNAs, and protein sequence databases for human, mouse, rat, and zebra-fish.

    The PepArML meta-search engine searches tandem mass-spectra against protein sequence databases (including PepSeqDB) using seven search engines (Mascot, Tandem, Tandem with K-Score and S-Score scoring plugins, OMSSA, Myrimatch, and InsPecT) and combines the search results using unsupervised machine-learning. This infrastructure typically identifies two-to-three times more spectra than individual search engines at 10% FDR.

    The PeptideMapper web-service provides real-time, one-click mapping of peptide sequences for human, mouse, or rat, to a genome annotation track of the UCSC genome browser, and onto their protein, mRNA, and genomic evidence. Peptides containing (coding) single nucleotide polymorphisms (SNPs) at also mapped, making it possible to evaluate cSNPs by their mass-delta, amino-acid substitution, and genomic context.

     

     


    New Peptide Sequence Database release (v1.5)

    July 30th, 2010, 9:36 am

    The latest build of the compressed peptide sequence database for human, mouse, rat, and zebrafish has been released, and can be downloaded via SFTP or SCP from anonsftp@edwardslab.bmcb.georgetown.edu:/pub/nedwards/PepSeqDB (password: anonsftp) or using the SFTP java applet here.

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    USHUPO 2010 Poster

    March 8th, 2010, 11:10 am

    Poster at 2010 USHUPO Annual Conference in Denver, CO.

    Boosting Peptide Identification Performance by Combining Many Search Engines, Spectral Matching, and Proteotypic and Physicochemical Peptide Properties.

    Prabhakar Gubbala; Nathan Edwards
    Georgetown University Medical Center, Washington, DC

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    PepArML Meta-Search Tutorial and Worked Example

    October 10th, 2009, 12:06 am

    This post provides a tutorial and worked example in the use of the PepArML meta-search engine for peptide identification from tandem mass spectra using sequence database search.

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    CPTC 2009 Annual Meeting

    October 6th, 2009, 9:17 am

    Meeting program is here for future reference. My talk and poster are available on the Edwards Lab publications page.


    NIH Proteomics Interest Group Talk

    September 21st, 2009, 3:31 pm

    I gave a talk in the NIH Proteomics Interest Group seminar series on Friday (9/18).

    Improved Peptide Identification Sensitivity using Meta-Search, Grid-Computing, and Machine-Learning, with Application to Genome Annotation

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    PepArML Meta-Search Engine

    June 1st, 2009, 12:01 pm

    The PepArML meta-search engine is open-for-business. New users can register for free, upload their spectra, submit large-scale meta-searches, monitor the search jobs, combine the completed searches using PepArML, and download the results, all via on-line PepArML meta-search engine site.

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    Meta-search, Grid-Computing, and Machine-Learning – ASMS 2009 Poster

    June 1st, 2009, 11:25 am

    I’ll be presenting my ASMS 2009 poster “Improving the Sensitivity of Peptide Identification from Tandem Mass Spectra using Meta-Search, Grid-Computing, and Machine-Learning” on Wednesday, June 3, 10:30 – 2:30. This poster describes the use of, you guessed it, meta-search (many search engines via a single user-interface), grid-computing (lots of heterogeneous computers), and machine-learning (to reconcile the peptide identification results). The poster is available on the Edwards Lab publications page.

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    PepArML manuscript published

    June 1st, 2009, 11:08 am

    The PepArML unsupervised, model-free, machine-learning, peptide identification result combiner has been published in Clinical Proteomcis and is available via Springer’s Open Choice open access option.

    N. Edwards, X. Wu, and C.-W. Tseng. “An Unsupervised, Model-Free, Machine-Learning Combiner for Peptide Identifications from Tandem Mass Spectra.” Clinical Proteomics 5.1 (2009). Final submitted manuscript.

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    New Peptide Sequence Database release (v1.4)

    May 15th, 2009, 9:16 am

    The latest build of the compressed peptide sequence database for human, mouse, rat, and zebrafish has been released, and can be downloaded via SFTP or SCP from anonsftp@edwardslab.bmcb.georgetown.edu:/pub/nedwards/PepSeqDB (password: anonsftp) or using the SFTP java applet here.

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