In this tutorial chapter, we review basics about frequent pattern mining algorithms, including itemset mining, association rule mining and graph mining. These algorithms can find frequently appearing substructures in discrete data. They can discover structural motifs, for example, from mutation data, protein structures and chemical compounds. As they have been primarily used for business data, biological applications are not so common yet, but their potential impact would be large. Recent advances in computers including multicore machines and ever increasing memory capacity support the application of such methods to larger datasets. We explain technical aspects of the algorithms, but do not go into details. Current biological applications a...
Bio-inspired methods which include evolutionary algorithms are currently widely used to solve very d...
The discovery of motifs in biological sequence is a much explored and still exploring area of resear...
The emergence of automated high-throughput sequencing technologies has resulted in a huge increase o...
In this tutorial chapter, we review basics about frequent pattern mining algorithms, including items...
In this tutorial article, the author reviews basics about frequent pattern mining algorithms, includ...
In this tutorial article, the author reviews basics about frequent pattern mining algorithms, includ...
Over the past two decades, pattern mining techniques have become an integral part of many bioinforma...
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously...
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously...
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously...
Database mining is the process of extracting interesting and previously unknown patterns and correla...
Abstract Searching for interesting common subgraphs in graph data is a well-studied problem in data ...
Searching for interesting common subgraphs in graph data is a well-studied problem in data mining. S...
Data mining is the semi-automatic discovery of patterns, associations, changes, anomalies, and stati...
Data mining is the semi-automatic discovery of patterns, associations, changes, anomalies, and stati...
Bio-inspired methods which include evolutionary algorithms are currently widely used to solve very d...
The discovery of motifs in biological sequence is a much explored and still exploring area of resear...
The emergence of automated high-throughput sequencing technologies has resulted in a huge increase o...
In this tutorial chapter, we review basics about frequent pattern mining algorithms, including items...
In this tutorial article, the author reviews basics about frequent pattern mining algorithms, includ...
In this tutorial article, the author reviews basics about frequent pattern mining algorithms, includ...
Over the past two decades, pattern mining techniques have become an integral part of many bioinforma...
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously...
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously...
Pattern detection is an inherent task in the analysis and interpretation of complex and continuously...
Database mining is the process of extracting interesting and previously unknown patterns and correla...
Abstract Searching for interesting common subgraphs in graph data is a well-studied problem in data ...
Searching for interesting common subgraphs in graph data is a well-studied problem in data mining. S...
Data mining is the semi-automatic discovery of patterns, associations, changes, anomalies, and stati...
Data mining is the semi-automatic discovery of patterns, associations, changes, anomalies, and stati...
Bio-inspired methods which include evolutionary algorithms are currently widely used to solve very d...
The discovery of motifs in biological sequence is a much explored and still exploring area of resear...
The emergence of automated high-throughput sequencing technologies has resulted in a huge increase o...