Showing 4 open source projects for "image analysis algorithm"

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  • 1
    Interactome  Transcriptome Integration
    The Interactome-Transcriptome Integration (ITI) algorithm allows the analysis of gene expression data by superimposition of a large scale protein-protein interaction data (human interactome) over several gene expression datasets. ITI extracts regions in the interactome with differentiating expression over two conditions. These subnetworks can that be used to build a generalizable and stable genomic signature for genomic/cancer classification.
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  • 2

    ModST

    A tool to search post-translational modifications in a blind mode

    ModST (pronounced as modest) is a tool to search post-translational modifications (PTMs) in mass spectrometry data in an unrestrictive manner. It can search for hundreds of modification without any user provided information for variable modifications. Due to data level parallelization implemented through perl it is fast, portable and easy to use to identify and analyse PTMs in MS/MS data.
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  • 3

    COHCAP

    City of Hope CpG Island Analysis Pipeline

    COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub. 2) In addition to the original NAR paper, please see the following links: Benchmarks: http://www.nature.com/protocolexchange/protocols/2965#/introduction Protocol Exchange Files: http://sourceforge.net/projects/cohcap/files/Protocol_Exchange_Example.zip 3) Custom Annotation Files (including EPIC Array): https://sourceforge.net/projects/cohcap/files/additional_Bioconductor_annotations.zip/download
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  • 4

    Digital Expression on the Web

    DEW is a platform that allows users to explore RNA-Seq data

    DEW is a platform that allows users to explore RNA-Seq data. A web-based Graphical User Interface is included. The analysis proceeds as such: gapped alignments are performed and corrected for length, PCR and fragment bias so that a Fragment Per (effective) Kilobase per Million of reads (FPKM) is estimated as well as the simpler Reads Per Kb per Million of reads (RPKM). When provided with multiple isoforms and in the ‘contextual’ mode, corrections include a expectation maximization algorithm estimates effective expression profiles and a corrected alignment is produced. ...
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