Efficient Mining of Interesting Patterns in Large Biological Sequences
Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology,...
Main Authors: | Md. Mamunur Rashid, Md. Rezaul Karim, Byeong-Soo Jeong, Ho-Jin Choi |
---|---|
Format: | Article |
Language: | English |
Published: |
BioMed Central
2012-03-01
|
Series: | Genomics & Informatics |
Subjects: | |
Online Access: | http://genominfo.org/upload/pdf/gni-10-44.pdf |
Similar Items
-
An Efficient Approach to Mining Maximal Contiguous Frequent Patterns from Large DNA Sequence Databases
by: Md. Rezaul Karim, et al.
Published: (2012-03-01) -
Extending Association Rule Mining to Microbiome Pattern Analysis: Tools and Guidelines to Support Real Applications
by: Agostinetto Giulia, et al.
Published: (2022-01-01) -
Review on the Application of Machine Learning Algorithms in the Sequence Data Mining of DNA
by: Aimin Yang, et al.
Published: (2020-09-01) -
Applying GIS and Text Mining Methods to Twitter Data to Explore the Spatiotemporal Patterns of Topics of Interest in Kuwait
by: Muhammad G. Almatar, et al.
Published: (2020-11-01) -
Mining High Utility Time Interval Sequences Using MapReduce Approach: Multiple Utility Framework
by: Sumalatha Saleti, et al.
Published: (2022-01-01)