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» Mining Quantitative Association Rules in Protein Sequences
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BMCBI
2008
97views more  BMCBI 2008»
13 years 7 months ago
Comparison study on k-word statistical measures for protein: From sequence to 'sequence space'
Background: Many proposed statistical measures can efficiently compare protein sequence to further infer protein structure, function and evolutionary information. They share the s...
Qi Dai, Tian-Ming Wang
KDD
2003
ACM
142views Data Mining» more  KDD 2003»
14 years 8 months ago
Frequent-subsequence-based prediction of outer membrane proteins
A number of medically important disease-causing bacteria (collectively called Gram-negative bacteria) are noted for the extra "outer" membrane that surrounds their cell....
Rong She, Fei Chen 0002, Ke Wang, Martin Ester, Je...
FUZZIEEE
2007
IEEE
14 years 1 months ago
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules
— Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction da...
Rafael Alcalá, Jesús Alcalá-F...
KES
2004
Springer
14 years 27 days ago
Mining Positive and Negative Fuzzy Association Rules
While traditional algorithms concern positive associations between binary or quantitative attributes of databases, this paper focuses on mining both positive and negative fuzzy ass...
Peng Yan, Guoqing Chen, Chris Cornelis, Martine De...
BMCBI
2005
116views more  BMCBI 2005»
13 years 7 months ago
Automating Genomic Data Mining via a Sequence-based Matrix Format and Associative Rule Set
There is an enormous amount of information encoded in each genome
Jonathan D. Wren, David Johnson, Le Gruenwald