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.
read more
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.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity
Nathalie Perrot,Cédric Baudrit,Jean Marie Brousset,Philippe Abbal,Hervé Guillemin,Bruno Perret,Etienne Goulet,Laurence Guérin,Gérard Barbeau,Daniel Picque +9 more
TL;DR: A decision support system so called FGRAPEDBN is proposed able to capitalize the heterogeneous fragmented knowledge available including data and expertise and predict the sugar concentrations with a relevant RMSE of 7 g/l (resp. the acidity).
18
Prediction of protein subcellular localization using deep learning and data augmentation
TL;DR: A Deep learning technique is proposed to enhance the precision of the analytical engine of one of these tools called PSORTb v3.0 by replacing its conventional SVM machine learning model with the state-of-the-art DL method (BiLSTM) and a Data augmentation measure (SeqGAN).
18
On the generalisation capabilities of Fisher vector-based face presentation attack detection
TL;DR: This work uses a new feature space based on Fisher Vectors, computed from compact Binarised Statistical Image Features histograms, which allow discovering semantic feature subsets from known samples in order to enhance the detection of unknown attacks.
Performance evaluation of BGP anomaly classifiers
Marijana Cosovic,Slobodan Obradovic,Ljiljana Trajkovic +2 more
- 05 Mar 2015
TL;DR: This paper evaluated performance of several machine learning algorithms for detecting Internet anomalies using RIB using Naive Bayes, Support Vector Machine, and Decision Tree classifiers using three data sets of known Internet anomalies.
Particle Filter Methods for Space Object Tracking
James S. McCabe,Kyle J. DeMars +1 more
- 04 Aug 2014
TL;DR: An approach for space object tracking utilizing particle filters is presented, and new methods are developed and used to construct a robust constrained admissible region given a set of angles-only measurements, which is then approximated by a finite mixture distribution.
18