The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTERS
Transactions ID Number: 89-530
Full Name: Aboubekeur Hamd-cherif
Position: Associate Professor
Age: ON
Sex: Male
Address: Qassim University, Computer College, PO Box 6688, 51452 Buraydah
Country: SAUDI ARABIA
Tel: +966557840413
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Fax:
E-mail address: elhamdi62@gmail.com
Other E-mails: elhamdi62@hotmail.com,shrief@qu.edu.sa
Title of the Paper: Integrating machine learning in intelligent bioinformatics
Authors as they appear in the Paper: Aboubekeur Hamdi-cherif
Email addresses of all the authors: elhamdi62@gmail.com
Number of paper pages: 12
Abstract: Machine learning is the adaptive process that makes computers improve from experience, by example, and by analogy. Learning capabilities are essential for automatically enhancing the performance of a computational system over time on the basis of previous history. Bioinformatics is the interdisciplinary science of interpreting biological data using information technology and computer science. The field of bioinformatics main objective is to develop relevant computational systems for biological purposes. In this paper, we study how machine learning can help in developing better bioinformatics methods and tools in a coherent manner. We attempt to integrate the multitude of existing methods and tools in a unifying framework as a prelude to showing how machine learning can uncover even more useful structures hidden in biological sequences.
Keywords: Intelligent Bioinformatics, Machine learning, Soft computing, Data mining, Grammatical inference.
EXTENSION of the file: .pdf
Special (Invited) Session: Machine learning for intelligent bioinformatics – part 1 machine Learning intergration
Organizer of the Session: 640-840
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