Identification of donor splice sites using support vector machine: a computational approach based on positional, compositional and dependency features.
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Title |
Identification of donor splice sites using support vector machine: a computational approach based on positional, compositional and dependency features.
Not Available |
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Creator |
Prabina Kumar Meher
Tanmaya Kumar Sahu A R Rao S D Wahi |
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Subject |
Hsplice
Hybrid approach Machine learning Sequence encoding |
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Description |
Not Available
Identification of splice sites is essential for the annotation of genes. Though existing approaches have achieved an acceptable level of accuracy, still there is a need for further improvement. Besides, most of the approaches are species-specific and hence it is required to develop approaches compatible across species. Not Available |
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Date |
2022-08-07T07:12:07Z
2022-08-07T07:12:07Z 2016-06-01 |
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Type |
Research Paper
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Identifier |
Meher, P.K., Sahu, T.K., Rao, A.R. et al. Identification of donor splice sites using support vector machine: a computational approach based on positional, compositional and dependency features. Algorithms Mol Biol 11, 16 (2016). https://doi.org/10.1186/s13015-016-0078-4
Not Available http://krishi.icar.gov.in/jspui/handle/123456789/73736 |
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Language |
English
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Relation |
Not Available;
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Publisher |
Not Available
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