Showing 4 open source projects for "level set method"

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  • 1

    GASiC

    Genome Abundance Similarity Correction

    One goal of sequencing based metagenomic analysis is the quantitative taxonomic assessment of microbial community compositions. However, the majority of approaches either quantify at low resolution (e.g. at phylum level) or have severe problems discerning highly similar species. Yet, accurate quantification on species level is desirable in applications such as metagenomic diagnostics or community comparison. GASiC is a method to correct read alignment results for the ambiguities imposed by similarities of genomes. It has superior performance over existing methods. ...
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  • 2

    CDSbank

    multi-sequence extraction, filtering & formatting

    ...CDSbank also stores Genbank feature annotation, a flag to indicate incomplete 5’ and 3’ ends, full taxonomic data, and a heuristic to rank the scientific interest of a species. This rich information allows fully automated data set preparation with a level of sophistication that meets or exceeds manual processing. Defaults ensure ease of use for typical scenarios while allowing great flexibility when needed. Access is via a free web service at http://hazeslab.med.ualberta.ca/CDSbank/. SourceForge code can be used to build a local installation.
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  • 3

    AMBIENT

    Find active modules in metabolic networks using high-throughput data

    ...For example, scores for reactions based on transcriptional data of their annotated encoding genes can be used in the network and modules of coordinated expression changes can be found. This provides an alternative to pathway/gene set enrichment analyses which is simultaneously more flexible and more specific.
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  • 4
    trimAl can consider several parameters, alone or in multiple combinations, in order to select the most-reliable positions in the alignment. These include the proportion of sequences with a gap, the level of residue similarity and, if several alignments for the same set of sequences are provided, the consistency level of columns among alignments. Moreover, trimAl allows to manually select a set of columns and sequences to be removed from the alignment. trimAl implements a series of automated algorithms that trim the alignment searching for optimum thresholds based on inherent characteristics of the input alignment, to be used so that the signal-to-noise ratio after alignment trimming phase is increased. ...
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