IMPROVED BREAST CANCER PROGNOSIS BASED ON A HYBRID MARKER SELECTION APPROACH

L. Hedjazi, M.-V. Le Lann, T. Kempowsky-Hamon, F. Dalenc, G. Favre

2011

Abstract

Clinical factors, such as patient age and histo-pathological state, are still the basis of day-to-day decision for cancer management. However, with the high throughput technology, gene expression profiling and proteomic sequences have known recently a widespread use for cancer and other diseases management. We aim through this work to assess the importance of using both types of data to improve the breast cancer prognosis. Nevertheless, two challenges are faced for the integration of both types of information: high-dimensionality and heterogeneity of data. The first challenge is due to the presence of a large amount of irrelevant genes in microarray data whereas the second is related to the presence of mixed-type data (quantitative, qualitative and interval) in the clinical data. In this paper, an efficient fuzzy feature selection algorithm is used to alleviate simultaneously both challenges. The obtained results prove the effectiveness of the proposed approach.

Paper Citation

in Harvard Style

Hedjazi L., Le Lann M., Kempowsky-Hamon T., Dalenc F. and Favre G. (2011). IMPROVED BREAST CANCER PROGNOSIS BASED ON A HYBRID MARKER SELECTION APPROACH . In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2011) ISBN 978-989-8425-36-2, pages 159-164. DOI: 10.5220/0003152301590164

in Bibtex Style

@conference{bioinformatics11,
author={L. Hedjazi and M.-V. Le Lann and T. Kempowsky-Hamon and F. Dalenc and G. Favre},
title={IMPROVED BREAST CANCER PROGNOSIS BASED ON A HYBRID MARKER SELECTION APPROACH},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2011)},
year={2011},
pages={159-164},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003152301590164},
isbn={978-989-8425-36-2},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms - Volume 1: BIOINFORMATICS, (BIOSTEC 2011)
TI - IMPROVED BREAST CANCER PROGNOSIS BASED ON A HYBRID MARKER SELECTION APPROACH
SN - 978-989-8425-36-2
AU - Hedjazi L.
AU - Le Lann M.
AU - Kempowsky-Hamon T.
AU - Dalenc F.
AU - Favre G.
PY - 2011
SP - 159
EP - 164
DO - 10.5220/0003152301590164