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ArtikelStatistical Practice in High Troughput Screening Data Analysis  
Oleh: Malo, Nathalie ; Hanley, James A. ; Sonia, Cerquozzi ; Pelletier, Jerry ; Nadon, Robert
Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Nature Biotechnology: The Science and Business of Biotechnology vol. 24 no. 2 (Feb. 2006), page 167-176.
Topik: STATISTICALS; statistical; data analysis
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  • Perpustakaan Pusat (Semanggi)
    • Nomor Panggil: NN9.4
    • Non-tandon: 1 (dapat dipinjam: 0)
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Isi artikelHigh throughput screeing is an early critical step in drug discovery. Its aim is to screen a large number of diverse chemical componds to identify candidate hits rapidly and accurately. Few statistical tools are currently available, however to detect quality hits with a high degree of confidence. We examine statistical aspects of tdata preprocessing and hit identification for primary screens. We focus on concerns related to positional effects of wells within plates, choice of hit threshold and the importance of minimizing false positive and false engative rates. We argue that replicate measurements are needed to verufy assumptions of current methods and to suggest data analysis strategies when assumptions are not emt. The integration of replicates with robust statistical methods in primary screens will facilitate the discovery of reliable hits, ultimately improving the sensitivity and specificity of the screening process.
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