By Mitra Basu, Yi Pan, Jianxin Wang
This publication constitutes the refereed court cases of the tenth overseas Symposium on Bioinformatics examine and functions, ISBRA 2014, held in Zhangjiajie, China, in June 2014. The 33 revised complete papers and 31 one-page abstracts integrated during this quantity have been conscientiously reviewed and chosen from 119 submissions. The papers disguise a variety of subject matters in bioinformatics and computational biology and their purposes together with the improvement of experimental or advertisement systems.
Read Online or Download Bioinformatics Research and Applications: 10th International Symposium, ISBRA 2014, Zhangjiajie, China, June 28-30, 2014. Proceedings PDF
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Additional info for Bioinformatics Research and Applications: 10th International Symposium, ISBRA 2014, Zhangjiajie, China, June 28-30, 2014. Proceedings
Deﬁnition 4. The similarity measure between two aligned substructures of proteins P and Q of length k can be deﬁned as follows dRM SD = 2 k2 − k k−1 k ( piu − piv − ( qju − qjv )2 ; and (1) u=1 v=u+1 cRM SD = 1 k k 2 piu − t(qju ) . (2) u=1 Since the similarity measures, cRM SD and dRM SD, are in terms of absolute distances, a small presence of outliers may result in a poor RM SD even if the two structures are globally similar. A similar observation has been made by other researchers [12, 26, 31, 32].
Note that, if the sequence alignment is 100 times as long (which is common in studies with supermatrices), the difference in lnL between T1 and T2 would be about 40, which is often greater than the difference between the best and the second best trees in a typical ML reconstruction. This rejection of topologies T2 and T3 in favor of T1 is not expected from the data in Fig. 1c because each pair of sequences differs by exactly one transition and two transversions. Why is topology T1 strongly favored by the likelihood method over T2 and T3?
Maximum-likelihood and minimum-steps methods for estimating evolutionary trees from data on discrete characters. Syst. Zool. 22, 240–249 (1973) 13. : Evolutionary trees from DNA sequences: a maximum likelihood approach. J. Mol. Evol. 17, 368–376 (1981) 14. : Inferring phylogenies. Sinauer, Sunderland (2004) 15. : Evolution of protein molecules. N. ) Mammalian Protein Metabolism, pp. 21–123. Academic Press, New York (1969) 16. : Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in Hominoidea.