An event-covering method for effective probabilistic inference
Pattern Recognition
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
APACS: a system for the automatic analysis and classification of conceptual patterns
Computational Intelligence
From contingency tables to various forms of knowledge in databases
Advances in knowledge discovery and data mining
High-Order Pattern Discovery from Discrete-Valued Data
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Attribute Clustering for Grouping, Selection, and Classification of Gene Expression Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An efficient algorithm for mining frequent inter-transaction patterns
Information Sciences: an International Journal
Multipattern consensus regions in multiple aligned protein sequences and their segmentation
EURASIP Journal on Bioinformatics and Systems Biology
Inferring the association network from p53 sequence alignment using granular evaluations
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
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Pattern discovery from a data set can be intractable because both the detection and the interpretation of the patterns can be ill-posed and combinatorically explosive. This paper presents a knowledge exploratory method using multiple pattern associations to conjecture structural and functional characteristics of biomolecules. We first consider each site from an ensemble of aligned biomolecules as an attribute and the observed unit at the site as its value. Our method identifies those consistently observed attribute values whose associations with others deviate significantly from their null hypothesis. In addition, variables (representing molecular sites) with the detected attribute values as outcomes can be further analyzed. By integrating these associations, exploratory knowledge for interpreting the detected patterns could be discovered. During the interpretation phase, consistent and relevant descriptions of the data are searched. From the experiments using cytochrome c sequences, the discovered statistical patterns are found to be significant in relating to the location of a site with respect to its molecular structural characteristics and stability of functionality.