Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/546888
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Detection of autism risk gene subsets from multi omic microarray data using metaheuristic algorithms | |
dc.date.accessioned | 2024-02-22T10:40:39Z | - |
dc.date.available | 2024-02-22T10:40:39Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/546888 | - |
dc.format.extent | xviii,132p. | |
dc.language | English | |
dc.relation | p.123-131 | |
dc.rights | university | |
dc.title | Detection of autism risk gene subsets from multi omic microarray data using metaheuristic algorithms | |
dc.title.alternative | ||
dc.creator.researcher | Anurekha G | |
dc.subject.keyword | Autism Spectrum Disorder | |
dc.subject.keyword | Deep Neural Network | |
dc.subject.keyword | Optimized Relieff | |
dc.description.note | ||
dc.contributor.guide | Geetha P | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | 21cm. | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 48.77 kB | Adobe PDF | View/Open |
02_prelimpage.pdf | 2.12 MB | Adobe PDF | View/Open | |
04_abstracts.pdf | 91.79 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 448.21 kB | Adobe PDF | View/Open | |
06_chapter2.pdf | 168.57 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 311.02 kB | Adobe PDF | View/Open | |
08_chapter4.pdf | 926.74 kB | Adobe PDF | View/Open | |
09_chapter5.pdf | 479.85 kB | Adobe PDF | View/Open | |
10_chapter6.pdf | 719.99 kB | Adobe PDF | View/Open | |
11_annexure.pdf | 124.6 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 100.48 kB | Adobe PDF | View/Open |
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