Search Results for "level set methods"

...Its architecture is both extensible and flexible using data structures that are intuitive to the biologist while transparently translating these into the underlying mathematical structures. . CBMPy implements popular analyses such as FBA, FVA, element/charge balancing, network analysis and model editing as well as advanced methods developed for the ecosystem modelling. CBMPy supports user interaction via: - interactive console or as a library for advanced use - GUI, visual representation of the model, analysis methods - a SOAP based webAPI exposes high level functionality via web services

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. ...

...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.

...We intend to extend the system from gene-level to variant-level prioritization, by exploiting the variant data in the MSV3D database. Contact: bmhoan@gmail.com or walter.vincent.fr@gmail.com

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. ...