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
Application of the rule extraction method to evaluate seismicity of Iran
Marziyeh Khalili,Ahmad Zamani +1 more
- 01 Jul 2016
TL;DR: In this article, a data-driven rule-extraction method called the Classification and Regression Tree (CART) was used to find the rules governing the earthquakes that occur, which produces Predictive Rule Based Seismicity Map (PRBSM) of Iran that shows regions with high earthquake hazards.
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•Book
Journeys to Data Mining: Experiences from 15 Renowned Researchers
Mohamed Medhat Gaber
- 21 Jul 2012
TL;DR: This narrative presentation style provides PhD students and novices who are eager to find their way to successful research in data mining with valuable insights into career planning with stunning successes and possible failures computer science careers have to offer.
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Graph constrained discriminant analysis: a new method for the integration of a graph into a classification process.
TL;DR: This work presents a method called graph-constrained discriminant analysis (gCDA), which aims to integrate the information contained in one or several GRNs into a classification procedure, and shows robustness to misspecifications in the given GRNs.
A study of particle swarm optimization in gene regulatory networks inference
Rui Xu,Ganesh K. Venayagamoorthy,Donald C. Wunsch +2 more
- 28 May 2006
TL;DR: The experimental results on a synthetic data set are presented to show the parameter effects of PSO on RNN training and the effectiveness of the proposed method in revealing the gene relations.
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A Method of Barkhausen Noise Feature Extraction Based on an Adaptive Threshold
Cheng Hang,Wenbo Liu,Ping Wang +2 more
TL;DR: The results obtained have proven that adaptive threshold features can effectively distinguish between different stress conditions compared with traditional MBN features.
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