Ameliorative missing value imputation for robust biological knowledge inference
نویسندگان
چکیده
منابع مشابه
Ameliorative missing value imputation for robust biological knowledge inference
Gene expression data is widely used in various post genomic analyses. The data is often probed using microarrays due to their ability to simultaneously measure the expressions of thousands of genes. The expression data, however, contains significant numbers of missing values, which can impact on subsequent biological analysis. To minimize the impact of these missing values, several imputation a...
متن کاملBIOINFORMATICS Collateral Missing Value Imputation: A New Robust Missing Value Estimation Algorithm For Microarray Data
Motivation: Microarray data is used in a range of application areas in biology, though often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible prior to using these algorithms. While many imputation algo...
متن کاملCollateral missing value imputation: a new robust missing value estimation algorithm for microarray data
MOTIVATION Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algo...
متن کاملHeuristic Non Parametric Collateral Missing Value Imputation: A Step Towards Robust Post-genomic Knowledge Discovery
Microarrays are able to measure the patterns of expression of thousands of genes in a genome to give profiles that facilitate much faster analysis of biological processes for diagnosis, prognosis and tailored drug discovery. Microarrays, however, commonly have missing values which can result in erroneous downstream analysis. To impute these missing values, various algorithms have been proposed ...
متن کاملA Robust Missing Value Imputation Method MifImpute For Incomplete Molecular Descriptor Data And Comparative Analysis With Other Missing Value Imputation Methods
Missing data imputation is an important research topic in data mining. Large-scale Molecular descriptor data may contains missing values (MVs). However, some methods for downstream analyses, including some prediction tools, require a complete descriptor data matrix. We propose and evaluate an iterative imputation method MiFoImpute based on a random forest. By averaging over many unpruned regres...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Biomedical Informatics
سال: 2008
ISSN: 1532-0464
DOI: 10.1016/j.jbi.2007.10.005