The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Data Mining for Biologists
|
|
Author(s): Koji Tsuda (Max Planck Institute for Biological Cybernetics, Germany)
Copyright: 2009
Pages: 14
Source title:
Biological Data Mining in Protein Interaction Networks
Source Author(s)/Editor(s): Xiao-Li Li (Institute for Infocomm Research, A* STAR, Singapore)and See-Kiong Ng (Institute for Infocomm Research, A* STAR, Singapore)
DOI: 10.4018/978-1-60566-398-2.ch002
Purchase
|
Abstract
In this tutorial chapter, the author reviews 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. The author explains technical aspects of the algorithms, but do not go into details. Current biological applications are summarized and possible future directions are given.
Related Content
|
Rahul Kumar, Devvret Verma, Bahman Khoshru, Adeyemi Nurudeen Olatunbosun.
© 2026.
36 pages.
|
|
S. Ida Evangeline.
© 2026.
34 pages.
|
|
Rahul Kumar, Rachan Karmakar, Sanja Živković, Tanja Vasić.
© 2026.
42 pages.
|
|
Poonam K. Verma, Nisha Chandran.
© 2026.
20 pages.
|
|
Odangowei Inetiminebi Ogidi, Shoheb Shakil Shaikh, Mukul Machhindra Barwant.
© 2026.
42 pages.
|
|
Harsh Virendrabhai Purohit, Veda Pandya.
© 2026.
30 pages.
|
|
Rachan Karmakar, Divya Gunsola, Debasis Mitra, Viralkumar B. Mandaliya, Arti Thakur, Addisu Assefa, Sourav Chattaraj, Mukul Machhindra Barwant, Uma Eswaranpillai, Ponmurugan Karuppiah.
© 2026.
28 pages.
|
|
|