TY - GEN
T1 - On finding and interpreting patterns in gene expression data from time course experiments
AU - Pittelkow, Yvonne E.
AU - Wilson, Susan R.
PY - 2008
Y1 - 2008
N2 - Microarrays are being widely used for studying gene activity throughout a cell cycle. A common aim is to find those genes that are expressed during specific phases in the cycle. The challenges lie in the extremely large number of genes being measured simultaneously, the relatively short length of the time course studied and the high level of noise in the data. Using a well-known yeast cell cycle data set, we compare a method being used for finding genes following a periodic time series pattern with a method for finding genes having a different phase pattern during the cell cycle. Application of two visualisation tools gives insight into the interpretation of the patterns for the genes selected by the two approaches. It is recommended that (i) more than a single approach be used for finding patterns in gene expression data from time course experiments, and (ii) visualisation be used simultaneously with computational and statistical methods to interpret as well as display these patterns.
AB - Microarrays are being widely used for studying gene activity throughout a cell cycle. A common aim is to find those genes that are expressed during specific phases in the cycle. The challenges lie in the extremely large number of genes being measured simultaneously, the relatively short length of the time course studied and the high level of noise in the data. Using a well-known yeast cell cycle data set, we compare a method being used for finding genes following a periodic time series pattern with a method for finding genes having a different phase pattern during the cell cycle. Application of two visualisation tools gives insight into the interpretation of the patterns for the genes selected by the two approaches. It is recommended that (i) more than a single approach be used for finding patterns in gene expression data from time course experiments, and (ii) visualisation be used simultaneously with computational and statistical methods to interpret as well as display these patterns.
UR - http://www.scopus.com/inward/record.url?scp=57049126165&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-88436-1_24
DO - 10.1007/978-3-540-88436-1_24
M3 - Conference contribution
SN - 3540884343
SN - 9783540884347
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 276
EP - 287
BT - 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008
PB - Springer Verlag
T2 - 3rd IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2008
Y2 - 15 October 2008 through 17 October 2008
ER -