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    BMCBI
    2006
    148views more  BMCBI 2006»
    Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of m
    14 years 9 months ago
    Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of m
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    Background: The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Mo...
    Veronica Vinciotti, Xiaohui Liu, Rolf Turk, Emile ...
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    GFKL
    2007
    Springer
    184views Data Mining» more  GFKL 2007»
    FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns
    15 years 1 months ago
    FSMTree: An Efficient Algorithm for Mining Frequent Temporal Patterns
    Download  fuzzy.cs.uni-magdeburg.de
    Research in the field of knowledge discovery from temporal data recently focused on a new type of data: interval sequences. In contrast to event sequences interval sequences contai...
    Steffen Kempe, Jochen Hipp, Rudolf Kruse
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    BMCBI
    2008
    132views more  BMCBI 2008»
    Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of
    14 years 9 months ago
    Computational cluster validation for microarray data analysis: experimental assessment of Clest, Consensus Clustering, Figure of
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    Background: Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analys...
    Raffaele Giancarlo, Davide Scaturro, Filippo Utro
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    SIGMOD
    2004
    ACM
    143views Database» more  SIGMOD 2004»
    Joining Interval Data in Relational Databases
    15 years 9 months ago
    Joining Interval Data in Relational Databases
    Download  www-i9.informatik.rwth-aachen.de
    The increasing use of temporal and spatial data in presentday relational systems necessitates an efficient support of joins on interval-valued attributes. Standard join algorithms...
    Jost Enderle, Matthias Hampel, Thomas Seidl
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    BMCBI
    2007
    157views more  BMCBI 2007»
    Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
    14 years 9 months ago
    Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
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    Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
    Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...
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