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Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids Anders Krogh, Graeme Mitchison, Richard Durbin, Sean R. y
Publisher: Cambridge University Press

How can we use PGMs to discover patterns that are .. Cambridge: Cambridge University Press. Probabilistic graphical models (PGMs) have become a popular tool for computational analysis of biological data in a variety of domains. 20) Majoros WH, Pertea M, Salzberg SL(2005). Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. But, what exactly are they and how do they work? Problems and Solutions in Biological Sequence Analysis at camelcamelcamel: Amazon price tracker, Amazon price history charts, price watches, and price drop alerts. Cambridge University Press, Cambridge, UK. Baldi P, Brunak S: Bioinformatics: The Machine Learning Approach. Biological sequence analysis: probabilistic models of proteins and nucleic acids. Xuedong Huang, Alex Acero, and Hsiao-Wuen Hon (2001). Durbin R, Eddy S, Krogh A, Mitchison G (1998) Biological sequence analysis: Probabilistic models of proteins and nucleic acids. Cambridge Univ Pr, reprint edition; 1999. With a total of 66 cells sequenced, 44 single cells from the tumor tissue (hereafter referred to as BC cells) and 11 from the normal adjacent tissue (hereafter referred to as BN cells) were qualified and selected for subsequent analyses . Durbin R: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids.