Showing 5 open source projects for "gene prediction"

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  • 1
    DACO-algorithm

    DACO-algorithm

    A novel transcription factor complex prediction algorithm.

    Eukaryotic gene expression is controlled through molecular logic circuits that combine regulatory signals of many different factors. Complexation of transcription factors and other regulatory proteins is a prevailing and highly conserved mechanism of signal integration within critical regulatory pathways and enable to infer controlled genes as well as the exerted regulatory mechanism. We developed DACO (domain-aware cohesiveness optimization), a novel algorithm that combines...
    Downloads: 0 This Week
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  • 2
    SILA

    SILA

    Automated bacterial and archaeal genome annotation system

    SILA is a system for automated annotation of bacterial and archaeal genomes. It provides accurate gene prediction using a combination of tools (Prodigal and HGF) and a web site for task management and visualization of annotation. This project is in alpha stage. Please use the online service available at: http://www.bioinfo.ufpr.br/SILA/login.jsp Documentation (portuguese only): http://hdl.handle.net/1884/34801
    Downloads: 0 This Week
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  • 3
    GESPA

    GESPA

    Accurately predicts disease association of single nucleotide mutations

    GESPA (GEnomic Single nucleotide Polymorphism Analyzer) is a bioinformatics tool for classifying Nonsynonymous Single Nucleotide Polymorphisms (nsSNPs). GESPA predicts if a nsSNP is pathogenic using reports from literature and various algorithms to assess conservation in orthologous and paralogous protein alignments. Using reports from literature, GESPA is also able to predict the phenotype of a nsSNP with high accuracy. The software can be used clinically to determine if observed nsSNPs are...
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  • 4
    AnnaF is an automatic gene annotation framework, that is used to do some automatic annotation for C. higginsianum. It was also tested on F. graminearum and should work well for fungi in general. AnnaF was build upon the pipeline framework Anna.
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  • 5
    Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.
    Downloads: 0 This Week
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