Open AccessBook
Analyzing Microarray Gene Expression Data
Geoffrey J. McLachlan,Kim Anh Do,Christophe Ambroise +2 more
- 04 Aug 2004
875
TL;DR: In this article, the authors proposed a supervised classification of Tissue Samples and linked the supervised classification with survival analysis, and showed that the classification of tissue samples is more accurate than that of microarray data.
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Abstract: Preface. 1. Microarrays in Gene Expression Studies. 2. Cleaning and Normalization. 3. Some Cluster Analysis Methods. 4. Clustering of Tissue Samples. 5. Screening and Clustering of Genes. 6. Discriminant Analysis. 7. Supervised Classification of Tissue Samples. 8. Linking Microarray Data with Survival Analysis. References. Author Index. Subject Index.
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Citations
Legal requirements metrics for compliance analysis
Ana I. Anton,Aaron K. Massey +1 more
- 01 Jan 2012
TL;DR: This dissertation examines how software engineers can evaluate software requirements for compliance with laws and regulations by developing empirically validated techniques for determining which requirements are legally implementation ready and a prototype tool that supports identifying LIR requirements using legal requirements metrics.
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SHADuDT: Secure hypervisor-based anomaly detection using danger theory
Reza Azmi,Boshra Pishgoo +1 more
TL;DR: This work proposed SHADuDT, a secure and robust hypervisor-based architecture for system call intercepting and information gathering that utilizes the second generation of Artificial Immune Systems (AIS) as intrusion detection method and compared its detection method with classic AIS methods for anomaly detection.
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Latent class distributional regression for the estimation of non-linear reference limits from contaminated data sources.
TL;DR: Latent class distributional regression models represent the first method to estimate indirect non-linear reference limits from a single model fit, but the general scope of applications can be extended to other scenarios with latent heterogeneity.
Data visualization and data mining of continuous numerical and discrete nominal‐valued microarray databases for bioinformatics
Richard S. Segall,Qingyu Zhang +1 more
TL;DR: This paper illustrates the useful information that can be obtained using data mining for evolutionary algorithms specifically as those for neural networks, genetic algorithms, regression analysis, and discriminant analysis.
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Development of intelligent model for personalized guidance on wheelchair tilt and recline usage for people with spinal cord injury: methodology and preliminary report.
TL;DR: Experimental results demonstrated that the feasibility of using machine learning techniques to construct an intelligent model to provide personalized guidance to individuals with spinal cord injury (SCI) held the promise: they could effectively construct the Intelligent model, evaluate its performance, and refine the participant model so that the intelligent model's prediction accuracy was significantly improved.
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