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Genome Mining Using Machine Learning Techniques
A major milestone in modern biology was the complete sequencing of the human genome. But it produced a whole set of new challenges in exploring the functions and interactions of different parts of the genome. One application is predicting disorders based on mining the genotype and understanding how the interactions between genetic loci lead to certain human diseases.
However, typically disease phenotypes are genetically complex. They are characterized by large, high-dimensional data sets. Also, usually the sample size is small.
Recently machine learning and predictive modeling approaches have been successfully applied to understand the genotype-phenotype relations and link them to human diseases. They are well suited to overcome the problems of the large data sets produced by the human genome and its high-dimensionality. Machine learning techniques have been applied in virtually all data mining domains and have proven to be effective in BioData mining as well.
This paper describes some of the techniques that have been adopted in recent studies in human genome analysis.
Genome Mining Using Machine Learning Techniques
A major milestone in modern biology was the complete sequencing of the human genome. But it produced a whole set of new challenges in exploring the functions and interactions of different parts of the genome. One application is predicting disorders based on mining the genotype and understanding how the interactions between genetic loci lead to certain human diseases.
However, typically disease phenotypes are genetically complex. They are characterized by large, high-dimensional data sets. Also, usually the sample size is small.
Recently machine learning and predictive modeling approaches have been successfully applied to understand the genotype-phenotype relations and link them to human diseases. They are well suited to overcome the problems of the large data sets produced by the human genome and its high-dimensionality. Machine learning techniques have been applied in virtually all data mining domains and have proven to be effective in BioData mining as well.
This paper describes some of the techniques that have been adopted in recent studies in human genome analysis.
Genome Mining Using Machine Learning Techniques
Lect.Notes Computer
Geissbühler, Antoine (editor) / Demongeot, Jacques (editor) / Mokhtari, Mounir (editor) / Abdulrazak, Bessam (editor) / Aloulou, Hamdi (editor) / Wlodarczak, Peter (author) / Soar, Jeffrey (author) / Ally, Mustafa (author)
International Conference on Smart Homes and Health Telematics ; 2015 ; Geneva, Switzerland
2015-05-30
6 pages
Article/Chapter (Book)
Electronic Resource
English
Genome wide prediction , Machine learning , Cross validation , Predictive medicine Computer Science , Special Purpose and Application-Based Systems , User Interfaces and Human Computer Interaction , Information Systems Applications (incl. Internet) , Artificial Intelligence , Image Processing and Computer Vision , Information Storage and Retrieval
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