Feature selection methods and genomic big data: a systematic review
Abstract In the era of accelerating growth of genomic data, feature-selection techniques are believed to become a game changer that can help substantially reduce the complexity of the data, thus making it easier to analyze and translate it into useful information. It is expected that within the next...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2019-08-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s40537-019-0241-0 |
| _version_ | 1818145148861677568 |
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| author | Khawla Tadist Said Najah Nikola S. Nikolov Fatiha Mrabti Azeddine Zahi |
| author_facet | Khawla Tadist Said Najah Nikola S. Nikolov Fatiha Mrabti Azeddine Zahi |
| author_sort | Khawla Tadist |
| collection | DOAJ |
| description | Abstract In the era of accelerating growth of genomic data, feature-selection techniques are believed to become a game changer that can help substantially reduce the complexity of the data, thus making it easier to analyze and translate it into useful information. It is expected that within the next decade, researchers will head towards analyzing the genomes of all living creatures making genomics the main generator of data. Feature selection techniques are believed to become a game changer that can help substantially reduce the complexity of genomic data, thus making it easier to analyze it and translating it into useful information. With the absence of a thorough investigation of the field, it is almost impossible for researchers to get an idea of how their work relates to existing studies as well as how it contributes to the research community. In this paper, we present a systematic and structured literature review of the feature-selection techniques used in studies related to big genomic data analytics. |
| first_indexed | 2024-12-11T11:58:51Z |
| format | Article |
| id | doaj.art-d19a93d6974d4a53a92efab2bad8fd23 |
| institution | Directory Open Access Journal |
| issn | 2196-1115 |
| language | English |
| last_indexed | 2024-12-11T11:58:51Z |
| publishDate | 2019-08-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj.art-d19a93d6974d4a53a92efab2bad8fd232022-12-22T01:08:07ZengSpringerOpenJournal of Big Data2196-11152019-08-016112410.1186/s40537-019-0241-0Feature selection methods and genomic big data: a systematic reviewKhawla Tadist0Said Najah1Nikola S. Nikolov2Fatiha Mrabti3Azeddine Zahi4Laboratory of Signals, Systems and Components, Laboratory of Intelligent Systems and Applications, Faculty of Sciences and Technologies, Sidi Mohammed Ben Abdellah UniversityLaboratory of Intelligent Systems and Applications, Faculty of Sciences and Technologies, Sidi Mohammed Ben Abdellah UniversityDepartment of Computer Science and Information Systems (CSIS) at the University of LimerickLaboratory of Signals, Systems and Components Faculty of Sciences and Technologies, Sidi Mohammed Ben Abdellah UniversityLaboratory of Intelligent Systems and Applications, Faculty of Sciences and Technologies, Sidi Mohammed Ben Abdellah UniversityAbstract In the era of accelerating growth of genomic data, feature-selection techniques are believed to become a game changer that can help substantially reduce the complexity of the data, thus making it easier to analyze and translate it into useful information. It is expected that within the next decade, researchers will head towards analyzing the genomes of all living creatures making genomics the main generator of data. Feature selection techniques are believed to become a game changer that can help substantially reduce the complexity of genomic data, thus making it easier to analyze it and translating it into useful information. With the absence of a thorough investigation of the field, it is almost impossible for researchers to get an idea of how their work relates to existing studies as well as how it contributes to the research community. In this paper, we present a systematic and structured literature review of the feature-selection techniques used in studies related to big genomic data analytics.http://link.springer.com/article/10.1186/s40537-019-0241-0Systematic reviewMapping processGenomic big dataFeature selection |
| spellingShingle | Khawla Tadist Said Najah Nikola S. Nikolov Fatiha Mrabti Azeddine Zahi Feature selection methods and genomic big data: a systematic review Journal of Big Data Systematic review Mapping process Genomic big data Feature selection |
| title | Feature selection methods and genomic big data: a systematic review |
| title_full | Feature selection methods and genomic big data: a systematic review |
| title_fullStr | Feature selection methods and genomic big data: a systematic review |
| title_full_unstemmed | Feature selection methods and genomic big data: a systematic review |
| title_short | Feature selection methods and genomic big data: a systematic review |
| title_sort | feature selection methods and genomic big data a systematic review |
| topic | Systematic review Mapping process Genomic big data Feature selection |
| url | http://link.springer.com/article/10.1186/s40537-019-0241-0 |
| work_keys_str_mv | AT khawlatadist featureselectionmethodsandgenomicbigdataasystematicreview AT saidnajah featureselectionmethodsandgenomicbigdataasystematicreview AT nikolasnikolov featureselectionmethodsandgenomicbigdataasystematicreview AT fatihamrabti featureselectionmethodsandgenomicbigdataasystematicreview AT azeddinezahi featureselectionmethodsandgenomicbigdataasystematicreview |