Browsing Hungarian translation

204.

Here the recursive parallelism paradigm is applied to the linear space profile-profile alignment algorithm. This approach is more time efficient on computers with distributed memory architecture. Traditional approach that relies on precomputing the profile-profile score matrix has also been implemented. Results shown the latter is indeed more appropriate for shared memory multiprocessor computer.

205.

ClustalX is suggested for its support for local realignments, seaview is a versatile editor of alignments.

206.

The original ClustalW/ClustalX can be found at URL: http://www.clustal.org/download/pre-2/

207.

Multiple alignment of nucleic acid and protein sequences (graphical interface)

208.

This package offers a GUI interface for the Clustal multiple sequence alignment program. It provides an integrated environment for performing multiple sequence- and profile-alignments to analyse the results. The sequence alignment is displayed in a window on the screen. A versatile coloring scheme has been incorporated to highlight conserved features in the alignment. For professional presentations, one should use the texshade LaTeX package or boxshade.

209.

The pull-down menus at the top of the window allow you to select all the options required for traditional multiple sequence and profile alignment. You can cut-and-paste sequences to change the order of the alignment; you can select a subset of sequences to be aligned; you can select a sub-range of the alignment to be realigned and inserted back into the original alignment.

210.

An alignment quality analysis can be performed and low-scoring segments or exceptional residues can be highlighted.

211.

Reimplementation of the Eisen-clustering software

212.

The open source clustering software available here contains clustering routines that can be used to analyze gene expression data. Routines for hierarchical (pairwise simple, complete, average, and centroid linkage) clustering, k-means and k-medians clustering, and 2D self-organizing maps are included. The routines are available in the form of a C clustering library, an extension module to Python, a module to Perl, as well as an enhanced version of Cluster, which was originally developed by Michael Eisen of Berkeley Lab. The C clustering library and the associated extension module for Python was released under the Python license. The Perl module was released under the Artistic License. Cluster 3.0 is covered by the original Cluster/TreeView license.

213.

This package only contains the command line and motif gui versions of Cluster 3.0.