Intelligent mining of large-scale bio-data: bioinformatics applications
Today, there is a collection of a tremendous amount of bio-data because of the computerized applications worldwide. Therefore, scholars have been encouraged to develop effective methods to extract the hidden knowledge in these data. Consequently, a challenging and valuable area for research in artif...
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Taylor & Francis
2017
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Online Access: | http://psasir.upm.edu.my/id/eprint/74710/1/Intelligent%20mining.pdf http://psasir.upm.edu.my/id/eprint/74710/ https://www.tandfonline.com/doi/full/10.1080/13102818.2017.1364977 |
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my.upm.eprints.747102019-11-28T03:47:18Z http://psasir.upm.edu.my/id/eprint/74710/ Intelligent mining of large-scale bio-data: bioinformatics applications Hashemi, Farahnaz Sadat Golestan Ismail, Mohd Razi Yusop, Mohd Rafii Hashemi, Mahboobe Sadat Golestan Shahraki, Mohammad Hossein Nadimi Rastegari, Hamid Miah, Gous Aslani, Farzad Today, there is a collection of a tremendous amount of bio-data because of the computerized applications worldwide. Therefore, scholars have been encouraged to develop effective methods to extract the hidden knowledge in these data. Consequently, a challenging and valuable area for research in artificial intelligence has been created. Bioinformatics creates heuristic approaches and complex algorithms using artificial intelligence and information technology in order to solve biological problems. Intelligent implication of the data can accelerate biological knowledge discovery. Data mining, as biology intelligence, attempts to find reliable, new, useful and meaningful patterns in huge amounts of data. Hence, there is a high potential to raise the interaction between artificial intelligence and bio-data mining. The present paper argues how artificial intelligence can assist bio-data analysis and gives an up-to-date review of different applications of bio-data mining. It also highlights some future perspectives of data mining in bioinformatics that can inspire further developments of data mining instruments. Important and new techniques are critically discussed for intelligent knowledge discovery of different types of row datasets with applicable examples in human, plant and animal sciences. Finally, a broad perception of this hot topic in data science is given. Taylor & Francis 2017-08 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/74710/1/Intelligent%20mining.pdf Hashemi, Farahnaz Sadat Golestan and Ismail, Mohd Razi and Yusop, Mohd Rafii and Hashemi, Mahboobe Sadat Golestan and Shahraki, Mohammad Hossein Nadimi and Rastegari, Hamid and Miah, Gous and Aslani, Farzad (2017) Intelligent mining of large-scale bio-data: bioinformatics applications. Biotechnology & Biotechnological Equipment, 32 (1). pp. 10-29. ISSN 1310-2818; ESSN: 1314-3530 https://www.tandfonline.com/doi/full/10.1080/13102818.2017.1364977 10.1080/13102818.2017.1364977 |
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Today, there is a collection of a tremendous amount of bio-data because of the computerized applications worldwide. Therefore, scholars have been encouraged to develop effective methods to extract the hidden knowledge in these data. Consequently, a challenging and valuable area for research in artificial intelligence has been created. Bioinformatics creates heuristic approaches and complex algorithms using artificial intelligence and information technology in order to solve biological problems. Intelligent implication of the data can accelerate biological knowledge discovery. Data mining, as biology intelligence, attempts to find reliable, new, useful and meaningful patterns in huge amounts of data. Hence, there is a high potential to raise the interaction between artificial intelligence and bio-data mining. The present paper argues how artificial intelligence can assist bio-data analysis and gives an up-to-date review of different applications of bio-data mining. It also highlights some future perspectives of data mining in bioinformatics that can inspire further developments of data mining instruments. Important and new techniques are critically discussed for intelligent knowledge discovery of different types of row datasets with applicable examples in human, plant and animal sciences. Finally, a broad perception of this hot topic in data science is given. |
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Article |
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Hashemi, Farahnaz Sadat Golestan Ismail, Mohd Razi Yusop, Mohd Rafii Hashemi, Mahboobe Sadat Golestan Shahraki, Mohammad Hossein Nadimi Rastegari, Hamid Miah, Gous Aslani, Farzad |
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Hashemi, Farahnaz Sadat Golestan Ismail, Mohd Razi Yusop, Mohd Rafii Hashemi, Mahboobe Sadat Golestan Shahraki, Mohammad Hossein Nadimi Rastegari, Hamid Miah, Gous Aslani, Farzad Intelligent mining of large-scale bio-data: bioinformatics applications |
author_facet |
Hashemi, Farahnaz Sadat Golestan Ismail, Mohd Razi Yusop, Mohd Rafii Hashemi, Mahboobe Sadat Golestan Shahraki, Mohammad Hossein Nadimi Rastegari, Hamid Miah, Gous Aslani, Farzad |
author_sort |
Hashemi, Farahnaz Sadat Golestan |
title |
Intelligent mining of large-scale bio-data: bioinformatics applications |
title_short |
Intelligent mining of large-scale bio-data: bioinformatics applications |
title_full |
Intelligent mining of large-scale bio-data: bioinformatics applications |
title_fullStr |
Intelligent mining of large-scale bio-data: bioinformatics applications |
title_full_unstemmed |
Intelligent mining of large-scale bio-data: bioinformatics applications |
title_sort |
intelligent mining of large-scale bio-data: bioinformatics applications |
publisher |
Taylor & Francis |
publishDate |
2017 |
url |
http://psasir.upm.edu.my/id/eprint/74710/1/Intelligent%20mining.pdf http://psasir.upm.edu.my/id/eprint/74710/ https://www.tandfonline.com/doi/full/10.1080/13102818.2017.1364977 |
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1651869165790691328 |
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13.18916 |