Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison
High Throughput Screening has been used in drug discovery to screen large numbers of potential compounds against a biological target by making it possible to screen tens of thousands to hundreds of thousands of compounds at the early stage of drug design. However, it is impractical to test eve...
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| Format: | Thesis |
| Language: | English |
| Published: |
2004
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| Online Access: | http://eprints.uthm.edu.my/7414/ http://eprints.uthm.edu.my/7414/1/24p%20RAHAYU%20A.%20HAMID.pdf |
| _version_ | 1848889094387531776 |
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| author | A. Hamid, Rahayu |
| author_facet | A. Hamid, Rahayu |
| author_sort | A. Hamid, Rahayu |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | High Throughput Screening has been used in drug discovery to screen large numbers
of potential compounds against a biological target by making it possible to screen
tens of thousands to hundreds of thousands of compounds at the early stage of drug
design. However, it is impractical to test every available compound against every
biological target. Classification is an approach in classifYing the compounds into
active and inactive based on already known actives. In this study, Neural Network
and Support Vector Machines (SVM) are used to classify AIDS data represented as
2D descriptors. Selection of compounds used is based on the most diverse
compounds. The classification models will be tested using different ratios of the data
set to identify whether the size of data would affect the rate of classification. Besides
th~t, the study also analyses the effects of dimensional reduction towards the results
of the two teclmiques. Final results indicate that SVM produces better classification
results for both the original data and the reduced dimension data. |
| first_indexed | 2025-11-15T20:20:43Z |
| format | Thesis |
| id | uthm-7414 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T20:20:43Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-74142022-07-21T07:20:20Z http://eprints.uthm.edu.my/7414/ Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison A. Hamid, Rahayu QA Mathematics QA76 Computer software QA71-90 Instruments and machines High Throughput Screening has been used in drug discovery to screen large numbers of potential compounds against a biological target by making it possible to screen tens of thousands to hundreds of thousands of compounds at the early stage of drug design. However, it is impractical to test every available compound against every biological target. Classification is an approach in classifYing the compounds into active and inactive based on already known actives. In this study, Neural Network and Support Vector Machines (SVM) are used to classify AIDS data represented as 2D descriptors. Selection of compounds used is based on the most diverse compounds. The classification models will be tested using different ratios of the data set to identify whether the size of data would affect the rate of classification. Besides th~t, the study also analyses the effects of dimensional reduction towards the results of the two teclmiques. Final results indicate that SVM produces better classification results for both the original data and the reduced dimension data. 2004-10 Thesis NonPeerReviewed text en http://eprints.uthm.edu.my/7414/1/24p%20RAHAYU%20A.%20HAMID.pdf A. Hamid, Rahayu (2004) Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison. Masters thesis, Universiti Teknologi Malaysia. |
| spellingShingle | QA Mathematics QA76 Computer software QA71-90 Instruments and machines A. Hamid, Rahayu Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| title | Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| title_full | Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| title_fullStr | Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| title_full_unstemmed | Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| title_short | Bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| title_sort | bioactivity classification of anti aids compounds using neural network and support vector machine: a comparison |
| topic | QA Mathematics QA76 Computer software QA71-90 Instruments and machines |
| url | http://eprints.uthm.edu.my/7414/ http://eprints.uthm.edu.my/7414/1/24p%20RAHAYU%20A.%20HAMID.pdf |