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Authors: Giacomo Domeniconi 1 ; Marco Masseroli 2 ; Gianluca Moro 1 and Pietro Pinoli 2

Affiliations: 1 Università degli Studi di Bologna, Italy ; 2 Politecnico di Milano, Italy

ISBN: 978-989-758-048-2

Keyword(s): Gene Ontology, Biomolecular Annotation Prediction, Bioinformatics, Knowledge Discovery, Supervised Learning, Data Representation.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; BioInformatics & Pattern Discovery ; Computational Intelligence ; Evolutionary Computing ; Information Extraction ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Soft Computing ; Symbolic Systems

Abstract: Genomic annotations describing functional features of genes and proteins through controlled terminologies and ontologies are extremely valuable, especially for computational analyses aimed at inferring new biomedical knowledge. Thanks to the biology revolution led by the introduction of the novel DNA sequencing technologies, several repositories of such annotations have becoming available in the last decade; among them, the ones including Gene Ontology annotations are the most relevant. Nevertheless, the available set of genomic annotations is incomplete, and only some of the available annotations represent highly reliable human curated information. In this paper we propose a novel representation of the annotation discovery problem, so as to enable applying supervised algorithms to predict Gene Ontology annotations of different organism genes. In order to use supervised algorithms despite labeled data to train the prediction model are not available, we propose a random perturbation me thod of the training set, which creates a new annotation matrix to be used to train the model to recognize new annotations. We tested the effectiveness of our approach on nine Gene Ontology annotation datasets. Obtained results demonstrated that our technique is able to improve novel annotation predictions with respect to state of the art unsupervised methods. (More)

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Paper citation in several formats:
Domeniconi G., Masseroli M., Moro G. and Pinoli P. (2014). Discovering New Gene Functionalities from Random Perturbations of Known Gene Ontological Annotations.In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014) ISBN 978-989-758-048-2, pages 107-116. DOI: 10.5220/0005087801070116

@conference{kdir14,
author={Giacomo Domeniconi and Marco Masseroli and Gianluca Moro and Pietro Pinoli},
title={Discovering New Gene Functionalities from Random Perturbations of Known Gene Ontological Annotations},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)},
year={2014},
pages={107-116},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005087801070116},
isbn={978-989-758-048-2},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2014)
TI - Discovering New Gene Functionalities from Random Perturbations of Known Gene Ontological Annotations
SN - 978-989-758-048-2
AU - Domeniconi G.
AU - Masseroli M.
AU - Moro G.
AU - Pinoli P.
PY - 2014
SP - 107
EP - 116
DO - 10.5220/0005087801070116

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