کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1993242 1541243 2015 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Measuring the quality of linear patterns in biclusters
موضوعات مرتبط
علوم زیستی و بیوفناوری بیوشیمی، ژنتیک و زیست شناسی مولکولی زیست شیمی
پیش نمایش صفحه اول مقاله
Measuring the quality of linear patterns in biclusters
چکیده انگلیسی


• We propose a coherence measurement MMSE for the general linear patterns.
• MMSE can evaluate biclusters with any types of linear correlations.
• The widely used MSR measure is actually the optimal value of MMSE on a shifting pattern.
• The experiments show that MMSE is more robust than the compared measurements.
• MMSE based biclustering is superior to most of other methods in terms of the number of significant biclusters.

In microarray analysis, biclustering is used to find the maximal subsets of rows and columns satisfying some coherence criteria. The found submatrices are usually called as biclusters. On one hand, different criteria would help to find different types of biclusters, thus the definition of coherence criterion is critical to the biclustering method. On the other hand, qualitative criteria result to qualitative biclustering methods that cannot evaluate the qualities of the biclusters, while quantitative criteria can numerically show how well the mined biclusters and are more useful in real applications. In bioinformatics communities, there are several quantitative coherence measurements for linear patterns proposed. However, they face the problem of weakness in finding all subtypes of linear patterns or sensitivity to the noise. In this work, we introduce a coherence measurement for the general linear patterns, the minimal mean squared error (MMSE), which is designed to handle the evaluation of biclusters with shifting, scaling and the general linear (the mixed form of shifting and scaling) correlations. The experiments on synthetic and real data sets show that the proposed methods is appropriate for identifying significant general linear biclusters.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Methods - Volume 83, 15 July 2015, Pages 18–27
نویسندگان
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