REACTION KERNELS - Structured Output Prediction Approaches for Novel Enzyme Function

Katja Astikainen, Esa Pitkänen, Juho Rousu, Liisa Holm, Sándor Szedmák

2010

Abstract

Enzyme function prediction problem is usually solved using annotation transfer methods. These methods are suitable in cases where the function of the new protein is previously characterized and included in the taxonomy such as EC hierarchy. However, given a new function that is not previously described, these approaches arguably do not offer adequate support for the human expert. In this paper, we explore a structured output learning approach, where enzyme function—an enzymatic reaction—is described in fine-grained fashion with so called reaction kernels which allow interpolation and extrapolation in the output (reaction) space. Two structured output models are learned via Kernel Density Estimation and Maximum Margin Regression to predict enzymatic reactions from sequence motifs. We bring forward two choices for constructing reaction kernels and experiment with them in the remote homology case where the functions in the test set have not been seen in the training phase. Our experiments demonstrate the viability of our approach.

Paper Citation

in Harvard Style

Astikainen K., Pitkänen E., Rousu J., Holm L. and Szedmák S. (2010). REACTION KERNELS - Structured Output Prediction Approaches for Novel Enzyme Function . In Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010) ISBN 978-989-674-019-1, pages 48-55. DOI: 10.5220/0002741700480055

in Bibtex Style

@conference{bioinformatics10,
author={Katja Astikainen and Esa Pitkänen and Juho Rousu and Liisa Holm and Sándor Szedmák},
title={REACTION KERNELS - Structured Output Prediction Approaches for Novel Enzyme Function},
booktitle={Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)},
year={2010},
pages={48-55},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002741700480055},
isbn={978-989-674-019-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Bioinformatics - Volume 1: BIOINFORMATICS, (BIOSTEC 2010)
TI - REACTION KERNELS - Structured Output Prediction Approaches for Novel Enzyme Function
SN - 978-989-674-019-1
AU - Astikainen K.
AU - Pitkänen E.
AU - Rousu J.
AU - Holm L.
AU - Szedmák S.
PY - 2010
SP - 48
EP - 55
DO - 10.5220/0002741700480055