000			01657nam a22003257a 4500
999			_c51433 _d52980
003			ISURa
008			190617b xxu||||| |||| 00| 0 eng d
020			_a9780521540797
020			_a0521540798
041			_aEnglish
082			_a572.8633 _bBIO
100			_aDurbin, Richard _972493
245			_aBiological sequence analysis _b probabalistic models of proteins and nucleic acids
260			_aCambridge, Angleterre _bCambridge University Press _c1998
300			_axi, 356 p. _bill. _c24 cm.
500			_aProbabilistic methods are assuming greater significance in the analysis of nucleotide sequence data. This book provides the first unified, up-to-date and self-contained account of such methods, and more generally of probabilistic methods of sequence analysis, presented in a Bayesian framework.
520			_a 1. Introduction; 2. Pairwise sequence alignment; 3. Multiple alignments; 4. Hidden Markov models; 5. Hidden Markov models applied to biological sequences; 6. The Chomsky hierarchy of formal grammars; 7. RNA and stochastic context-free grammars; 8. Phylogenetic trees; 9. Phylogeny and alignment; Index.
650			_aAmino acid sequence--Data processing _972494
650			_aNucleotide sequence--Data processing _972495
650			_aMarkov processes _972496
650			_aAmino acid sequence--Statistical methods _972497
650			_aProbabilities _9675
655			_aNumerical analysis _972498
655			_aNucleotide sequence--Statistical methods _972499
655			_a _972500
700			_aEddy, Sean R. _972501
700			_aKrogh, Anders _972502
700			_aMitchison, Graeme _972503
942			_2ddc _cLN