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Examples

We tested the new tree construction method on two protein families. We also constructed the trees with two other methods, the Fitch algorithm of the PHYLIP package [12] and the ProbModel [13]. In all cases all the three algorithms agreed on the tree topology. We only took 9 and 15 proteins for drawing reasons, but the algorithm allows any number of sequences. The first one is the IA1 and IA2 subunit of Cytochrome P450 (see Figure 10). In this example you can clearly see a gene duplication (symmetry). The upper half is the IA1 subunit, the lower half is the IA2 subunit.
  
Figure 9: Cytochrome P450 tree constructed with new method
\begin{figure}
\begin{center}
\mbox{\psfig{file=CP450.ps,height=0.25\textheight,angle=0} }
\end{center}
\end{figure}

The second example is the Hemoglobin alpha-I chain from 15 species. The MSA below was calculated using the ProbModel and gap heuristics [26]. The score is the CS measure as described in [15]. This alignment is the optimal alignment, as the maximum possible score is equal to the score.

Multiple sequence alignment:
----------------------------
Score of the alignment: 7089.83
Maximum possible score: 7089.83

2       _VLSAADKGNVKAAWGKVGGHAAEYGAEALER__MFLSFPTTKTYFPHF_DLSQGSAQVKGHGAKVAAALTKAVEHLDDLPGALSELSDLHAHKLRVDPVNFKLLSHSLLVTLASHLPSDFTPAVHASLDKFLANVSTVLTSKYR
11      _VLSPEDKNNVKAAWSKVGGQAGDYGAEALER__MFLSFPTTKTYFPHF_DLSHGSAQVKGHGKKVGEALTTAVNHMDDLPGALSTLSDLHAYKLRVDPVNFKLLSHCLLVTLACHNPGEFTPAVHASLDKFLASVSTVLTSKYR
3       _VLSPTDKSIVKAAWEKVGAHAGDYGAEALER__MFLSFPTTKTYFPQF_DLSHGSAQVKGHGKKVADALTNAVLHVDDMPSALSALSDLHAHKLTVDPVNFKLLSHCLLVTLACHLPAEFTPAVHASLDKFMASVSTVLTSKYR
5       _VLSPADKNNVKSAWNAIGSHAGEHGAEALER__MFLSFPPTKTYFPHF_DLSHGSAQIKTHGKKVADALTNAVNHIDDMPGALSALSDLHAHKLRVDPVNFKLLSHCLLVTLASHHPAEFTPAVHASLDKFFAAVSTVLTSKYR
1       _VLSPADKTNIKTTWDKLGGHAGEYGGEALER__TFMSFPTTKTYFPHF_DLSPGSAQVKAHGKKVADALTTAVAHMDDLPKALSALSDLHAYKLRVDPVNFKLLSHCLLVTLACHHPAEFTPAVHASLDKFFSTVSTVLTSKYR
10      _VLTDAEKKEVTSLWGKASGHAEEYGAEALER__LFLSFPTTKTYFSHM_DLSKGSAQVKAHGKRVADALTTAAGHFNDMDSALSALSDLHAHKLRVDPVNFKLLAHCFLVVLARHHPAEFTPSAHAAMDKFLSRVATVLTSKYR
4       _VLTEDDKNHIRAIWGHVDNNPEAFGVEALTR__LFLAYPATKTYFAHF_DLNPGSAQIKAHGKKVVDALTQAVNNLDDIPDALAKLADLHAEKLRVDPVNFGLLGHCILVTIAAHNHGPLKADVALSMDKFLTKVAKTLVAHYR
15      _VLTDDDKNHVRAIWGHVSNNPEAFGAEALYR__LFTAHPASKTYFSHF_DLHENSAQIRXXXXKVVDALTQAVNNLDDLSGAISKLSDLHAEK___________________________________________________
14      MKLSADDKHNVKAIWEHVKGHEEAIGAEALCR__MFTSLPTTRTYFPTK_DIKEGSSFLHSHGKKVMGALSNAVAHIDDIDGALSKLSDKHAEELMVDPANFPKLAHNILVVLGIHLKPHLTYSVHSSVDKFLATVGYVLASKYR
8       _KLTAEDKHNVKAIWDHVKGHEEAIGAEALYR__MFCCMPTTRIYFPAK_DLSERSSYLHSHGKKVVGALTNAVAHIDDIDTAFSKLSDKHAEELMVDPANFPKLAHNILVVLGIHLKPHFTYSVHRSVDKFLSTVAYVLASKYR
12      _VLSEGNKKAIKNLLQKIHSQTEVLGAEALAR__LFECHPQTKSYFPKFSGFSANDKRVKHHGALVLKALVDTNKHLDDLPHHLNKLAEKHGKGLLVDPHNFKLFSDCIAVTLAAHLQ_EFSPETHCAVDKFLEEVTYQLSSLYR
7       _SLSDKDKAAVKALWSKIGKSADAIGNDALSR__MIVVYPQTKTYFSHWPSVTPGHPDIKAHGKKVMGGLAIAVSKINDLKAGLSNLSQQHAYKLRVDPANFKILNHCILVVISTMFPKNFTPQAHVSLNKFLSGVALALAQRYR
6       _SLSDKDKAAVRALWSKIGKSADAIGNDALSR__MIVVYPQTKTYFSHWPDVTPGSAHIKAHGKKVMGGIALAVSKIDDLKAGLSDLSEQHAYKLRVDPANFKILNHCILVVISTMFPKDFTPEAHVSLDKFLSGVALALAERYR
13      _SLSDKDKAAVRALWSKIGKSSDAIGNDALSR__MIVVYPQTKIYFSHWPDVTPGSPNIKAHGKKVMGGIALAVSKIDDLKTGLMELSEQHAYKLRVDPSNFKILNHCILVVISTMFPKEFTPEAHVSLDKFLSGVALALAERYR
9       _SLTAKDKSVVKAFWGKISGKADVVGAEALGRDKMLTAYPQTKTYFSHWADLSPGSGPVKKHGGIIMGAIGKAVGLMDDLVGGMSALSDLHAFKLRVDPGNFKILSHNILVTLAIHFPSDFTPEVHIAVDKFLAAVSAALADKYR

   1 -> HBA1_ARCGA      2 -> HBA1_BOSMU      3 -> HBA1_GALCR      4 -> HBA1_IGUIG
   5 -> HBA1_LEMVA      6 -> HBA1_NOTAN      7 -> HBA1_NOTCO      8 -> HBA1_PLEWA
   9 -> HBA1_SALIR     10 -> HBA1_TACAC     11 -> HBA1_TADBR     12 -> HBA1_TORMA
  13 -> HBA1_TRENE     14 -> HBA1_TRICR     15 -> HBA1_UROHA

  
Figure 10: Hemoglobin alpha 1 constructed with new method
\begin{figure}
\begin{center}
\mbox{\psfig{file=HBA1.ps,height=0.25\textheight,angle=0} }
\end{center}
\end{figure}


next up previous
Next: Discussion Up: Using Traveling Salesman Problem Previous: Algorithm
Chantal Korostensky
1999-07-14