Assessing the information content of short time series expression data

Eric H Yang; Ioannis P Androulakis

doi:10.1109/IEMBS.2006.259573

Back

Journal article

Assessing the information content of short time series expression data

Eric H Yang and Ioannis P Androulakis

Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), Vol.2006, pp.5535-5538

2006

DOI: https://doi.org/10.1109/IEMBS.2006.259573

PMID: 17945907

Abstract

Models, Theoretical

Computational Biology - methods

Data Interpretation, Statistical

Gene Expression

Oligonucleotide Array Sequence Analysis

Humans

Gene Expression Regulation

Gene Expression Profiling

Models, Statistical

Algorithms

Time Factors

Computer Simulation

Software

Pattern Recognition, Automated

Cluster Analysis

Due to experimental constraints, the sampling of biological system with microarray data is severely constrained. In similar fashion to sampling theory of signals, the under-sampling of a system oftentimes leads to sub-optimal results from which it is difficult to draw proper conclusions. In our work we create a mathematical framework which will show that the sampling methodology for short time series microarray data may lead to data whose ability to distinguish non-random behavior within the biological system is severely constrained.

Metrics

8 Record Views

Details

Title: Assessing the information content of short time series expression data
Creators: Eric H Yang - Rutgers University, Piscataway, NJ 08845, USA
Ioannis P Androulakis
Publication Details: Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.), Vol.2006, pp.5535-5538
Date published: 2006
Academic Unit: Biomedical Engineering (SOE); New Brunswick Summer Session
Language: English
Resource Type: Journal article
Identifiers: 991031654768704646