Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.
BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.
Tra
Yolande V
YV
Schools of Mathematical Sciences and Biological and Medical Sciences, College of Sciences Rochester Institute of Technology, Rochester, NY 14623-5603, USA. yvtsma@rit.edu
Evans
Irene M
IM
D001695:Biology / Q000193:education*; D003479:Curriculum; D003625:Data Collection; D006801:Humans; D058025:Interdisciplinary Studies; D008433:Mathematics / Q000193:education*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D013223:Statistics as Topic; D013334:Students
Nat Rev Drug Discov. 2002 Dec;1(12):951-60
12461517
Cell Biol Educ. 2004 Summer;3(2):88-90
15257335
Nucleic Acids Res. 2003 Jan 1;31(1):68-71
12519949
Genome Biol. 2004;5(10):R80
15461798
Science. 2004 Feb 6;303(5659):790-3
14764866
Nat Rev Mol Cell Biol. 2006 Apr;7(4):290-6
16482092
CBE Life Sci Educ. 2009 Spring;8(1):15-28
19255133
Genome Res. 2000 Dec;10(12):2022-9
11116096
Cell Biol Educ. 2002 Aug 08;1(3):70-2
12459791
Science. 1997 Oct 24;278(5338):680-6
9381177
BMC Genomics. 2004 Nov 08;5:87
15533245
Science. 2006 Feb 24;311(5764):1103-4
16497918
CBE Life Sci Educ. 2008 Winter;7(4):382-93
19047425
Cell Biol Educ. 2003 Winter;2(4):233-47
14673489
Br J Cancer. 2003 Nov 3;89(9):1599-604
14583755
CBE Life Sci Educ. 2007 Summer;6(2):109-18
17548873
Science. 2004 Feb 6;303(5659):788-90
14764865
Science. 2009 Jul 31;325(5940):541-2
19644094
Nat Rev Genet. 2004 Jan;5(1):11-22
14708012
Cell Biol Educ. 2003 Summer;2(2):87-91
12888841
Bioinformatics. 2005 May 1;21(9):2114-5
15647303
Nat Rev Genet. 2002 Sep;3(9):653-61
12209140
Biochem Mol Biol Educ. 2004 Jul;32(4):217-27
21706728
Brief Bioinform. 2007 Mar;8(2):88-95
17077138
Anal Chem. 2003 Sep 1;75(17):4672-5
14632079
Science. 2004 Apr 23;304(5670):521-2
15105480
J Microbiol Biol Educ. 2009 Dec 17;8(1):3-12
23653814
Nucleic Acids Res. 2000 Jan 1;28(1):27-30
10592173
Nature. 2003 Aug 7;424(6949):610-2
12904757