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Assessing the Information Content of Short Time Series Expression Eric H. Yang and Ioannis P. Androulakis*
 

Summary: Assessing the Information Content of Short Time Series Expression
Data
Eric H. Yang and Ioannis P. Androulakis*
Department of Biomedical Engineering
Rutgers University, Piscataway, NJ 08854
Abstract-- 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.
I. INTRODUCTION
The advent of the micro-array has been hailed as a revo-
lution in molecular biology[1]. It ushered in the era of high
throughput gene expression analysis, allowing researchers to
interrogate the expression levels of many genes at once. The
next step in this revolution is temporal expression profiling

  

Source: Androulakis, Ioannis (Yannis) - Biomedical Engineering Department & Department of Chemical and Biochemical Engineering, Rutgers University

 

Collections: Engineering; Biology and Medicine