Hart, R., Royyuru, A., Stolovitzky, G., & Califano, A. (2000). Systematic and Automated Discovery of Patterns in PROSITE Families. In: RECOMB '00 pp. 147-154, ACM-. Proceedings RECOMB'00, Tokyo. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Three Variations on Word Counting - Régnier, Lifanov, Makeev (1 citation) (Correct)
....where statistical signi cance is checked for a huge number of motifs. This part extends to structured motifs [Marsan Sagot, 2000] Bias appears in overrepresentation criteria when a binding site is searched on both strands. Counting scheme should be weighted. Characteristic pro les [Hart et al. 2000, Corpet et al. 2000] for a protein family may be a regular expression, for instance in PROSITE format. All over the paper, we establish a validity domain for some widely used approximations, and discuss sensitivity of statistical tests to Bernoulli approximation to Markov model. This is the ....
....avour remains: we have a rst correcting term at no extra cost, and our algorithm SmartVar for autocorrelation correcting term steadily extends. Pattern pro les Main application here is the automatic discovery of pattern pro les [Jonassen et al. 1999] such as PROSITE regular expressions [Hart et al. 2000]. We focus on the computation of the mean in the Markovian case. We claim a tight bound for approximation V ar(H) E(NH ) can be proved in that case. Intuitively, there are two reasons for that. First, overlapping expressions de ne rather long suxes in this context. Second, amino acid alphabet ....
[Article contains additional citation context not shown here]
Hart, R., Royyuru, A., Stolovitzky, G., & Califano, A. (2000). Systematic and Automated Discovery of Patterns in PROSITE Families. In: RECOMB '00 pp. 147-154, ACM-. Proceedings RECOMB'00, Tokyo.
New Techniques for Extracting Features from Protein Sequences - Wang, Ma, Shasha, Wu (2001) (10 citations) (Correct)
....on M may not be unique. As a consequence, the weight of a motif defined in Equation (14) may not be unique (in which case the proposed heuristic randomly picks one) There are several other approaches for finding motifs of different forms and for calculating their significance values (see, e.g. [7, 8, 16, 36]) However, motifs have relatively little effect on PIR sequence classification and a combination of the proposed techniques already yields a very high precision, as our experimental results show later. 4 The Bayesian Neural Network Classifier We adopt the Bayesian neural network (BNN) ....
R. Hart, A. Royyuru, G. Stolovitzky, and A. Califano. Systematic and automated discovery of patterns in PROSITE families. In Proceedings of the Fourth Annual International Conference on Computational Molecular Biology, 2000.
Three Variations on Word Counting - Régnier, Lifanov, Makeev (1 citation) (Correct)
....for a huge number of motifs. This part extends to structured motifs (Marsan Sagot, 2000) Bias appears in overrepresentation criteria when a binding site is searched on both strands, due to a lack of biological information. Counting scheme should be weighted. Characteristic profiles (Hart et al. 2000; Corpet et al. 2000) for a protein family may be a regular expression, for instance in PROSITE format. All over the paper, we establish a validity domain for some widely used approximations, and discuss sensitivity of statistical tests to Bernoulli approximation to Markov model. This is the ....
....rewrites as: DeltaZ = n(PM (H) Gamma PB (H) p nPB (H) ff p nPB (H) 3) For large sequences, a small error ff can still lead to significant variation in Z score. Pattern profiles Main application here is the automatic discovery of pattern profiles such as PROSITE regular expressions (Hart et al. 2000). We focus on the computation of the mean in the Markovian case. MeanMarkov is described for rigid patterns of length m, and a Markovian model of order 1 with transition matrix P and stationary probability vector q. It takes as an input k specified positions (i l ) 1lk , and associated sets of ....
[Article contains additional citation context not shown here]
Hart, R., Royyuru, A., Stolovitzky, G., & Califano, A. (2000). Systematic and Automated Discovery of Patterns in PROSITE Families. In: RECOMB'00 pp. 147--154, ACM-. Proceedings RECOMB'00, Tokyo.
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