MAVL/StickWRLD for protein -- visualizing protein sequence families to detect non-consensus features

What you can do:
Visualize and survey the model-training sequences to discover and characterize possible dependencies among protein sequences.
  • A fundamental problem with applying Consensus, Weight-Matrix or hidden Markov models as search tools for biosequences is that there is no way to know, from the model, if the modeled sequences display any dependencies between positional identities. In some instances, these dependencies are crucial in correctly accepting or rejecting other sequences as members of the family.
  • MAVL (multiple alignment variation linker) and StickWRLD provide a web-based method to visually survey the model-training sequences to discover and characterize possible dependencies.
  • The Web server offers a visualization method to support protein alignments, and it is augmented in several ways to enhance protein viewing.
  • For a given set of pre-aligned sequences, MAVL (Multiple Alignment Variation Linker) examines each pair of positions, and determines any pair of identities that occur with greater, or lesser frequency than a simple positional frequency matrix description would predict.
  • The results are returned as a StickWRLD VRML graph, displaying the positional frequency matrix in a graphical form, and providing visual links between positions that have an over, or under-population greater than a user-specified cutoff.
  • protein sequence alignment visualization tool
  • protein homology
  • protein non-consensus features
  • protein sequence similarity analysis tool
This record last updated: 11-14-2005
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