Amanote Research

Amanote Research

  • Register
  • Sign In

Robust Imputation Method for Missing Values in Microarray Data

BMC Bioinformatics- United Kingdom

doi 10.1186/1471-2105-8-s2-s6

Full Text

Abstract

Available in

Categories

BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology

Date

January 1, 2007

Authors

Dankyu YoonEun-Kyung LeeTaesung Park

Publisher

Springer Science and Business Media LLC


Related search

Robust Regression Imputation for Analyzing Missing Data

2012English

Missing Data Imputation Method for Autism Prediction

International Journal of Recent Technology and Engineering
EngineeringManagement of TechnologyInnovation
2020English

Missing Data Imputation for Ordinal Data

International Journal of Computer Applications
2018English

Missing Value Imputation for Microarray Data: A Comprehensive Comparison Study and a Web Tool

BMC Systems Biology
Molecular BiologyApplied MathematicsStructural BiologySimulationComputer Science ApplicationsModeling
2013English

Multiple Imputation of Missing Values: New Features for Mim

Stata Journal
Mathematics
2009English

Robust Principal Component Analysis of Data With Missing Values

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2015English

Contributions to Imputation for Missing Survey Data

English

Microarray Missing Value Imputation by Iterated Local Least Squares

2005English

Comparative Analysis of Different Imputation Methods to Treat Missing Values in Data Mining Environment

International Journal of Computer Applications
2013English

Amanote Research

Note-taking for researchers

Follow Amanote


© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy