Missing value estimation methods for DNA microarrays
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Summary
It is shown that KNNimpute appears to provide a more robust and sensitive method for missing value estimation than SVDimpute, and both SVD Impute and KNN Impute surpass the commonly used row average method (as well as filling missing values with zeros).
- Type
- article
- Published
- 2001-06-01
- Cited by
- 4,348
- References
- 20
- Access
- Open access
- OpenAlex
- https://openalex.org/W2096863518
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1105917
Keywords
Missing data, Imputation (statistics), Data mining, Cluster analysis, Computer science
References
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- The transcriptional program of sporulation in budding yeast.
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- Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
- Singular value decomposition for genome-wide expression data processing and modeling.
- Cluster analysis and display of genome-wide expression patterns.
- Exploring the metabolic and genetic control of gene expression on a genomic scale.
- Estimation of Missing Values for the Analysis of Incomplete Data
- Matrix computations
- The analysis of replicated experiments when the field results are incomplete
- Principal components analysis to summarize microarray experiments: application to sporulation time series.
Cited by
- Interpretation of gene expression microarray experiments
- Algorithmes métaheuristiques hybrides pour la sélection de gènes et la classification de données de biopuces. (Hybrid metaheuristics algorithms for gene selection and classification of microarray data)
- Gene expression profiles at diagnosis in de novo childhood AML patients identify FLT3 mutations with good clinical outcomes.
- Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection
- Applications of support vector machines to cancer classification with microarray data
- Inferring missing genotypes in large SNP panels using fast nearest-neighbor searches over sliding windows
- Differential gene expression and lipid metabolism in fatty liver induced by acute ethanol treatment in mice.
- Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient
- Expression profiling analysis for genes related to meat quality and carcass traits during postnatal development of backfat in two pig breeds
- Reconstruction of Gene Regulatory Modules in Cancer Cell Cycle by Multi-Source Data Integration
- Missing data imputation using statistical and machine learning methods in a real breast cancer problem
- Survival dimensionality reduction (SDR): development and clinical application of an innovative approach to detect epistasis in presence of right-censored data
- GC-MS metabolomic analysis reveals significant alterations in cerebellar metabolic physiology in a mouse model of adult onset hypothyroidism.
- Predicting gene function using few positive examples and unlabeled ones
- Improving the efficiency of multidimensional scaling in the analysis of high-dimensional data using singular value decomposition
- WF-MSB: A weighted fuzzy-based biclustering method for gene expression data
- Shared processing of perception and imagery of music in decomposed EEG
- Monitoring of Technical Variation in Quantitative High-Throughput Datasets
- Consensus policies to solve bioinformatic problems through Bayesian network classifiers and estimation of distribution algorithms
- Screening of diagnostic markers for osteosarcoma.
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