NDLI: Systematic Evaluation of Scaling Methods for Gene Expression Data

Content Provider	IEEE Xplore Digital Library
Author	Pandey, G. Ramakrishnan, L.N. Steinbach, M. Kumar, V.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Univ. of Minnesota, Minneapolis, MN (Pandey, G.; Ramakrishnan, L.N.; Steinbach, M.; Kumar, V.)
Abstract	Even after an experimentally prepared gene expression data set has been pre-processed to account for variations in the microarray technology, there may be inconsistencies between the scales of measurements in different conditions. This may happen for reasons such as the accumulation of gene expression data prepared by different laboratories into a single data set. A variety of scaling and transformation methods have been used for addressing these scale inconsistencies in different studies on the analysis of gene expression data sets. However, a quantitative estimation of their relative performance has been lacking. In this paper, we report an extensive evaluation of scaling and transformation methods for their effectiveness with respect to the important problem of protein function prediction. We consider several such commonly used methods for gene expression data, such as z-score scaling, quantile normalization, diff transformation, and two new scaling methods, sigmoid and double sigmoid, that have not been used previously in this domain to the best of our knowledge. We show that the performance of these methods can vary significantly across data sets, but Dsigmoid scaling and z-score transformation generally perform well for the two types of gene expression data, namely temporal and non-temporal, respectively.
Starting Page	376
Ending Page	381
File Size	1573212
Page Count	6
File Format	PDF
ISBN	9780769534527
DOI	10.1109/BIBM.2008.33
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-11-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laboratories Data engineering Biomedical measurements Gene expression data Gene expression systematic evaluation Proteins Computer science scaling methods USA Councils protein function prediction Cities and towns Bioinformatics Biomedical engineering
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Bioinformatics Tools Enabling U-Statistics for Microarrays

Sample Scale-Free Gene Regulatory Network Using Gene Ontology

Discovering Frequent Patterns of Functional Associations in Protein Interaction Networks for Function Prediction

Detecting artifacts on SNP chips

Counting Heartbeats at a Distance

Correlated Discretized Expression Score: A Method for Identifying Gene Interaction Networks from Time Course Microarray Expression Data

Applications of Nonlinear System Identification in Molecular Biology

Reconstructing Signal Transduction from Raw Genomic Data

Gene selection for Brain Cancer Classification

Systematic Evaluation of Scaling Methods for Gene Expression Data

Similar Documents

Bioinformatics Tools Enabling U-Statistics for Microarrays

Sample Scale-Free Gene Regulatory Network Using Gene Ontology

Discovering Frequent Patterns of Functional Associations in Protein Interaction Networks for Function Prediction

Detecting artifacts on SNP chips

Counting Heartbeats at a Distance

Correlated Discretized Expression Score: A Method for Identifying Gene Interaction Networks from Time Course Microarray Expression Data

Applications of Nonlinear System Identification in Molecular Biology

Reconstructing Signal Transduction from Raw Genomic Data

Gene selection for Brain Cancer Classification

Systematic Evaluation of Scaling Methods for Gene Expression Data