Brief. Bioinformatics - A primer to frequent itemset mining for bioinformatics.

Tópicos

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Resumo

Over the past two decades, pattern mining techniques have become an integral part of many bioinformatics solutions. Frequent itemset mining is a popular group of pattern mining techniques designed to identify elements that frequently co-occur. An archetypical example is the identification of products that often end up together in the same shopping basket in supermarket transactions. A number of algorithms have been developed to address variations of this computationally non-trivial problem. Frequent itemset mining techniques are able to efficiently capture the characteristics of (complex) data and succinctly summarize it. Owing to these and other interesting properties, these techniques have proven their value in biological data analysis. Nevertheless, information about the bioinformatics applications of these techniques remains scattered. In this primer, we introduce frequent itemset mining and their derived association rules for life scientists. We give an overview of various algorithms, and illustrate how they can be used in several real-life bioinformatics application domains. We end with a discussion of the future potential and open challenges for frequent itemset mining in the life sciences.

Resumo Limpo

past two decad pattern mine techniqu becom integr part mani bioinformat solut frequent itemset mine popular group pattern mine techniqu design identifi element frequent cooccur archetyp exampl identif product often end togeth shop basket supermarket transact number algorithm develop address variat comput nontrivi problem frequent itemset mine techniqu abl effici captur characterist complex data succinct summar owe interest properti techniqu proven valu biolog data analysi nevertheless inform bioinformat applic techniqu remain scatter primer introduc frequent itemset mine deriv associ rule life scientist give overview various algorithm illustr can use sever reallif bioinformat applic domain end discuss futur potenti open challeng frequent itemset mine life scienc

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