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Mathematical Biosciences and Engineering

2013, Volume 10, Issue 3: 667-690. doi: 10.3934/mbe.2013.10.667
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On the sensitivity of feature ranked lists for large-scale biological data

  • 1.
    Silesian University of Technology, Institute of Automatic Control, Akademicka 16, 44-100 Gliwice
  • Received: 01 June 2012 Accepted: 29 June 2018 Published: 01 April 2013

  • MSC : 92-08.

  • The problem of feature selection for large-scale genomic data, for example from DNA microarray experiments, is one of the fundamental and well-investigated problems in modern computational biology.From the computational point of view, a selected gene list should be characterized by good predictive power and should be understood and well explained from the biological point of view.Recently, another feature of selected gene lists is increasingly investigated, namely their stability which measures how the content and/or the gene order change when the data are perturbed.In this paper we propose a new approach to analysis of gene list stability, termed the sensitivity index, that does not require any data perturbationand allows the gene list that is most reliable in a biological sense to be chosen.

    Citation: Danuta Gaweł, Krzysztof Fujarewicz. On the sensitivity of feature ranked lists for large-scale biological data[J]. Mathematical Biosciences and Engineering, 2013, 10(3): 667-690. doi: 10.3934/mbe.2013.10.667

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  • The problem of feature selection for large-scale genomic data, for example from DNA microarray experiments, is one of the fundamental and well-investigated problems in modern computational biology.From the computational point of view, a selected gene list should be characterized by good predictive power and should be understood and well explained from the biological point of view.Recently, another feature of selected gene lists is increasingly investigated, namely their stability which measures how the content and/or the gene order change when the data are perturbed.In this paper we propose a new approach to analysis of gene list stability, termed the sensitivity index, that does not require any data perturbationand allows the gene list that is most reliable in a biological sense to be chosen.


    [1] Molecular Endocrinology, 25 (2011), 1326-1336.
    [2] Frontiers in Bioscience, 14 (2009), 2829-2844.
    [3] Briefings in Bioinformatics, 10 (2009), 556-568.
    [4] Journal of Clinical Oncology, 25 (2007), 852-861.
    [5] The Journal of Nutritional Biochemistry, 22 (2011), 634-641.
    [6] Critical Reviews in Clinical Laboratory Sciences, 45 (2008), 531-562.
    [7] Computer Methods and Programs in Biomedicine, 93 (2009), 124-139.
    [8] Journal of the American Statistical Association, 97 (2002), 77-87.
    [9] 2003. Available from: http://www.bioconductor.org/help/course-materials/2003/Milan/Lectures/classif.pdf.
    [10] The Biochemical Journal, 345 (2000), 503-509.
    [11] Endocrine - Related Cancer, 14 (2007), 809-826.
    [12] Journal of Medical Informatics and Technologies, 2 (2001), MI9-MI17.
    [13] International Journal of Applied Mathematics and Computer Science, 13 (2003), 327-335.
    [14] AACR Meeting Abstracts, (2005), 217-c-218 .
    [15] 2nd edition, Springer-Verlag, 2009.
    [16] Molecular Cancer, 9 (2010).
    [17] Cancer Research, 65 (2005), 1587-1597.
    [18] Bioinformatics, 24 (2008), 258-264.
    [19] Oncogene, 31 (2012), 3111-3123.
    [20] BMC Bioinformatics, 7 (2006), 235-244.
    [21] Genes Dev., 22 (2008), 308-321.
    [22] Breast Cancer Research, 11 (2009).
    [23] Clin. Cancer Res., 13 (2007), 2471-2478.
    [24] PLoS ONE, 6 (2011), 1-10.
    [25] BMC Clinical Pathology, 12 (2012), 2-14.
    [26] Molecular Cancer, 9 (2010).
    [27] Am. J. Pathol., 156 (2000), 595-605.
    [28] 2010, Patent WO/2010/061996.
    [29] Journal of Biomedicine and Biotechnology, 2010 (2010), 556-568.
    [30] Biology Direct, 7 (2012).
    [31] Cancer Research, 57 (1997), 1776-1784.
    [32] Proceedings of the National Academy of Sciences of the United States of America, 98 (2001), 5116-5121.
    [33] Lung Cancer, 48 (2005), 19-29.
    [34] Journal of Clinical Oncology, 26 (2008), 2952-2958.
    [35] Stanford University, (2007), 1-13.
    [36] World Journal of Surgical Oncology, 9 (2011).
    [37] Available from: http://gedi.ci.uchicago.edu/.
    [38] Available from: http://www.genecards.org/.
    [39] Available from: http://www.malacards.org/.
    [40] Available from: http://www.ncbi.nlm.nih.gov/.
    [41] Available from: http://www.ncbi.nlm.nih.gov/omim.
    [42] 2012. Available from: http://www.globethesis.com/?t=2154330335497716 and http://www.res-medical.com/oncology/93581.
    [43] Available from: https://usgene.sequencebase.com/.
    [44] Available from: http://www.wikigenes.org/.

  • This article has been cited by:

    1. Shuo Wang, Junyan Lu, Detect influential points of feature rankings, 2025, 115, 14769271, 108339, 10.1016/j.compbiolchem.2024.108339
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