Location: EU Supported » PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning » MLG - 2008: 6th International Workshop on Mining and Learning with Graphs

Markov Logic Improves Protein β-Partners Prediction

author:Marco Lippi, Dipartimento di Sistemi e Informatica, University of Firenze
published: Aug. 25, 2008,   recorded: July 2008,   views: 72
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Slides

Slides
0:00 Markov Logic Improves Protein β-Partners Prediction
0:16 3D Protein Structure Prediction
1:38 β-Partners: A Link Prediction Task - 1
2:25 β-Partners: A Link Prediction Task - 2
3:11 State-of-the-art Architecture: BetaPro
4:19 β-Partners: A Link Prediction Task - 3
5:53 Markov Logic - 1
6:35 Markov Logic - 2
7:26 Markov Logic - 3
8:06 Curse of Dimensionality
9:39 Expressivity of the Model
10:03 Markov Logic Networks with Grounding-Specific Weights - 1
10:53 Markov Logic Networks with Grounding-Specific Weights - 2
11:58 Markov Logic Networks with Grounding-Specific Weights - 3
13:03 Markov Logic Networks with Grounding-Specific Weights - 2
13:27 Markov Logic Networks with Grounding-Specific Weights - 3
13:28 The Data Set
14:34 The Model: Hard Rules
15:33 The Model: More Complex Rules - 1
17:08 The Model: More Complex Rules - 2
17:47 Plugging in BetaPro Probabilities
18:58 The Model: A Second-Stage MLN
20:07 Results Obtained on 10-Fold Cross Validation - 1
21:02 Results Obtained on 10-Fold Cross Validation - 2
21:54 Examples: Comparison with BetaPro - 1
23:18 Examples: Comparison with BetaPro - 3
23:45 Conclusions and Future Work
25:25 - Questions

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Description

Protein β-partners prediction is an important problem in protein structure that can be naturally formulated as supervised link prediction. We show that prediction performance can be improved using a hybrid solution based on Markov logic networks with grounding-specific weights.

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