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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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Main Authors: Hashemi, Farahnaz Sadat Golestan, Ismail, Mohd Razi, Yusop, Mohd Rafii, Hashemi, Mahboobe Sadat Golestan, Shahraki, Mohammad Hossein Nadimi, Rastegari, Hamid, Miah, Gous, Aslani, Farzad
Format: Article
Language:English
Published: Taylor & Francis 2017
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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spelling 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
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description 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.
format Article
author Hashemi, Farahnaz Sadat Golestan
Ismail, Mohd Razi
Yusop, Mohd Rafii
Hashemi, Mahboobe Sadat Golestan
Shahraki, Mohammad Hossein Nadimi
Rastegari, Hamid
Miah, Gous
Aslani, Farzad
spellingShingle 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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score 13.211869

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