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Using randomised vectors in transcription factor binding site predictions

Using randomised vectors in transcription factor binding site predictions
Using randomised vectors in transcription factor binding site predictions

Finding the location of binding sites in DNA is a difficult problem. Although the location of some binding sites have been experimentally identified, other parts of the genome may or may not contain binding sites. This poses problems with negative data in a trainable classifier. Here we show that using randomized negative data gives a large boost in classifier performance when compared to the original labeled data.

Binding site, Classification, Genes, Support, Vector machines
523-527
Rezwan, Faisal
203f8f38-1f5d-485b-ab11-c546b4276338
Sun, Yi
52b4df91-6eec-4c04-8106-7cd195f1d0a6
Davey, Neil
45038a2a-60fa-475b-be2b-72b23c97bb0c
Adams, Rod
aba52023-234f-464a-b86f-504b200dc950
Rust, Alistair G.
27e6975d-abef-4037-a8ff-74b2a18cb687
Robinson, Mark
0191ef40-12cc-4b4d-9bcd-5547087add95
Rezwan, Faisal
203f8f38-1f5d-485b-ab11-c546b4276338
Sun, Yi
52b4df91-6eec-4c04-8106-7cd195f1d0a6
Davey, Neil
45038a2a-60fa-475b-be2b-72b23c97bb0c
Adams, Rod
aba52023-234f-464a-b86f-504b200dc950
Rust, Alistair G.
27e6975d-abef-4037-a8ff-74b2a18cb687
Robinson, Mark
0191ef40-12cc-4b4d-9bcd-5547087add95

Rezwan, Faisal, Sun, Yi, Davey, Neil, Adams, Rod, Rust, Alistair G. and Robinson, Mark (2010) Using randomised vectors in transcription factor binding site predictions. In Proceedings - 9th International Conference on Machine Learning and Applications, ICMLA 2010. pp. 523-527 . (doi:10.1109/ICMLA.2010.82).

Record type: Conference or Workshop Item (Paper)

Abstract

Finding the location of binding sites in DNA is a difficult problem. Although the location of some binding sites have been experimentally identified, other parts of the genome may or may not contain binding sites. This poses problems with negative data in a trainable classifier. Here we show that using randomized negative data gives a large boost in classifier performance when compared to the original labeled data.

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More information

Published date: 2010
Venue - Dates: 9th International Conference on Machine Learning and Applications, ICMLA 2010, , Washington, DC, United States, 2010-12-12 - 2010-12-14
Keywords: Binding site, Classification, Genes, Support, Vector machines

Identifiers

Local EPrints ID: 414015
URI: http://eprints.soton.ac.uk/id/eprint/414015
PURE UUID: c7b78983-38c6-4aa8-a813-d60622d4a481
ORCID for Faisal Rezwan: ORCID iD orcid.org/0000-0001-9921-222X

Catalogue record

Date deposited: 12 Sep 2017 16:31
Last modified: 20 Feb 2024 02:51

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Contributors

Author: Faisal Rezwan ORCID iD
Author: Yi Sun
Author: Neil Davey
Author: Rod Adams
Author: Alistair G. Rust
Author: Mark Robinson

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