title: Visual exploration of parameter influence on phylogenetic trees.
abstract: Evolutionary relationships between organisms are frequently derived as phylogenetic trees inferred from multiple sequence alignments (MSAs). The MSA parameter space is exponentially large, so tens of thousands of potential trees can emerge for each dataset. A proposed visual-analytics approach can reveal the parameters' impact on the trees. Given input trees created with different parameter settings, it hierarchically clusters the trees according to their structural similarity. The most important clusters of similar trees are shown together with their parameters. This view offers interactive parameter exploration and automatic identification of relevant parameters. Biologists applied this approach to real data of 16S ribosomal RNA and protein sequences of ion channels. It revealed which parameters affected the tree structures. This led to a more reliable selection of the best trees.
authors.forename: Martin
authors.initials: M
authors.lastname: Hess
authors.forename: Sebastian
authors.initials: S
authors.lastname: Bremm
authors.forename: Stephanie
authors.initials: S
authors.lastname: Weissgraeber
authors.forename: Kay
authors.initials: K
authors.lastname: Hamacher
authors.forename: Michael
authors.initials: M
authors.lastname: Goesele
authors.forename: Josef
authors.initials: J
authors.lastname: Wiemeyer
authors.forename: Tatiana
authors.initials: T
authors.lastname: von Landesberger
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods*; D003196:Computer Graphics; D030541:Databases, Genetic; D019143:Evolution, Molecular; D010802:Phylogeny; D012329:RNA, Bacterial / Q000235:genetics; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D016415:Sequence Alignment / Q000379:methods*
chemical_list: D012329:RNA, Bacterial; D012336:RNA, Ribosomal, 16S