Graphs are most often visualized in the two dimensional Euclidean plane, but spherical space offers several advantages when visualizing graphs. First, some graphs such as skeletons of three dimensional polytopes (tetrahedron, cube, icosahedron) have spherical realizations that capture their 3D structure, which cannot be visualized as well in the Euclidean plane. Second, the sphere makes possible a natural "focus + context visualization with more detail in the center of the view and less details away from the center. Finally, whereas layouts in the Euclidean plane implicitly define notions of "central and "peripheral nodes, this issue is reduced on the sphere, where the layout can be centered at any node of interest.

MOTIVATION: Aligning protein sequences with the best possible accuracy requires sophisticated algorithms. Since the optimal alignment is not guaranteed to be the correct one, it is expected that even the best alignment will contain sites that do not respect the assumption of positional homology. Because formulating rules to identify these sites is difficult, it is common practice to manually remove them. Although considered necessary in some cases, manual editing is time consuming and not reproducible. We present here an automated editing method based on the classification of 'valid' and 'invalid' sites. RESULTS: A support vector machine (SVM) classifier is trained to reproduce the decisions made during manual editing with an accuracy of 95.0%. This implies that manual editing can be made reproducible and applied to large-scale analyses. We further demonstrate that it is possible to retrain/extend the training of the classifier by providing examples of multiple sequence alignment (MSA) annotation. Near optimal training can be achieved with only 1000 annotated sites, or roughly three samples of protein sequence alignments. AVAILABILITY: This method is implemented in the software MANUEL, licensed under the GPL. A web-based application for single and batch job is available at http://fester.cs.dal.ca/manuel. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.