Searching databases of conserved sequence regions by aligning protein multiple-alignments.

By Shmuel Pietrokovski. 1996

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Citations in the corpus

MRFalign: Protein Homology Detection through Alignment of Markov Random Fields (2014, methodology): “Quite a few PSSM-based profile comparison methods for homology detection have been developed, including [11, 18-23].”
Comparative Protein Structure Modeling Using MODELLER (2007, methodology): “There are a number of variants of proﬁle-proﬁle alignment methods that differ in the scoring functions they use (Pietrokovski, 1996; Rychlewski et al., 1998; Yona and Levitt, 2002; Panchenko, 2003; Sadreyev and Grishin, 2003; von Ohsen et al., 2003; Edgar and Sjolander, 2004; Marti-Renom et al.,…”
Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae. (2000, methodology): “To compare motifs, we chose a scoring method based on the Pearson correlation coef®cient between the nucleotide base frequencies of two motif alignments (Pietrokovski, 1996).”
Comparative Protein Structure Modeling Using Modeller (2006, methodology): “There are a number of variants of profile-profile alignment methods that differ in the scoring functions they use (Pietrokovski, 1996; Rychlewski et al., 1998; Yona and Levitt, 2002; Panchenko, 2003; Sadreyev and Grishin, 2003; von Ohsen et al., 2003; Edgar, 2004; Marti-Renom et al., 2004; Zhou and…”
COMPASS: a tool for comparison of multiple protein alignments with assessment of statistical significance. (2003, background): “Presenting two profiles as two sequences of columns, we can find lu as the unique positive equation of ( 13 ) in the form:”
Homology Modeling a Fast Tool for Drug Discovery: Current Perspectives (2012, methodology): “The LAMA[38] program aligns two multiple sequence alignments, first by transforming them into profiles and then comparing these two with each other by the Pearson correlation coefficient.”
Natural similarity measures between position frequency matrices with an application to clustering (2008, methodology): “The Pearson correlation coefficient which has been shown to be more effective than other methods ( Pietrokovski, 1996 ) is widely used.”
STAMP: a web tool for exploring DNA-binding motif similarities (2007, methodology): “Two motifs can be aligned using Needleman–Wunsch (global) or Smith–Waterman (local) alignment methods, based on column comparison scores calculated by one of the five supported distance metrics: (i) Pearson’s correlation coefficient ( 9 ), (ii) Kullback–Leibler information content (3), b sum of squa”
Detection of distant evolutionary relationships between protein families using theory of sequence profile-profile comparison (2010, unknown): “Hidden Markov Models (HMMs) [1-7].”
MUSCLE: a multiple sequence alignment method with reduced time and space complexity (2004, methodology): “This is illustrated in Figure 14, in which the discrimination plot for LE on PP2 is compared with several other functions: PSP, LA, Yona and Levitt's [46], LAMA [47].”
FFAS03: a server for profile–profile sequence alignments (2005, methodology): “Profile–profile scoring was used earlier to align short blocks ( 4 ), and FFAS extended this approach to allow for gaps and align entire proteins.”