%0 Book Section %1 statphys23_0944 %A Joo, K. %A Lee, J. %A Kim, I. %A Lee, S.J. %A Lee, J. %B Abstract Book of the XXIII IUPAP International Conference on Statistical Physics %C Genova, Italy %D 2007 %E Pietronero, Luciano %E Loreto, Vittorio %E Zapperi, Stefano %K alignment annealing conformational consistency-based function global multiple optimization prediction protein score sequence space statphys23 structure topic-10 %T Multiple sequence alignment using the conformational space annealing %U http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=944 %X We present a new method for multiple sequence alignment (MSA), which we call MSACSA. The method is based on the direct and rigorous application of the conformational space annealing (CSA) to a consistency-based score function constructed from pairwise sequence alignments between constituting sequences. The MSACSA is applied to two simple alignment sets as well as to a couple of MSA databases, the 82 families from the Balibase reference set 1 and the 366 families from the Homstrad set. In all 450 cases, the energy of the lowest energy alignment by MSACSA is always less than or equal to the energy of the existing alignments. In addition, when the accuracy of an alignment is measured on the reference alignment provided by the databases, MSACSA provides better alignments on average than the current top methods based on the progressive alignment. Another major advantage of MSACSA is that it provides not just the global minimum alignment but also many distinct low-lying sub-optimal alignments for a given objective function. This is due to the fact that CSA can maintain the conformational diversity while searching low-energy conformational space. This characteristics can help us to alleviate the problem arising from using an inaccurate score function.

@incollection{statphys23_0944, abstract = {We present a new method for multiple sequence alignment (MSA), which we call MSACSA. The method is based on the direct and rigorous application of the conformational space annealing (CSA) to a consistency-based score function constructed from pairwise sequence alignments between constituting sequences. The MSACSA is applied to two simple alignment sets as well as to a couple of MSA databases, the 82 families from the Balibase reference set 1 and the 366 families from the Homstrad set. In all 450 cases, the energy of the lowest energy alignment by MSACSA is always less than or equal to the energy of the existing alignments. In addition, when the accuracy of an alignment is measured on the reference alignment provided by the databases, MSACSA provides better alignments on average than the current top methods based on the progressive alignment. Another major advantage of MSACSA is that it provides not just the global minimum alignment but also many distinct low-lying sub-optimal alignments for a given objective function. This is due to the fact that CSA can maintain the conformational diversity while searching low-energy conformational space. This characteristics can help us to alleviate the problem arising from using an inaccurate score function.}, added-at = {2007-06-20T10:16:09.000+0200}, address = {Genova, Italy}, author = {Joo, K. and Lee, J. and Kim, I. and Lee, S.J. and Lee, J.}, biburl = {https://www.bibsonomy.org/bibtex/2f9b9fe057499ea49ab5606a4530a6f89/statphys23}, booktitle = {Abstract Book of the XXIII IUPAP International Conference on Statistical Physics}, editor = {Pietronero, Luciano and Loreto, Vittorio and Zapperi, Stefano}, interhash = {cc8704e7a77d692606d2a8af40aafc2b}, intrahash = {f9b9fe057499ea49ab5606a4530a6f89}, keywords = {alignment annealing conformational consistency-based function global multiple optimization prediction protein score sequence space statphys23 structure topic-10}, month = {9-13 July}, timestamp = {2007-06-20T10:16:35.000+0200}, title = {Multiple sequence alignment using the conformational space annealing}, url = {http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=944}, year = 2007 }