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Molecular Genetics and Genomics
Spring Semester 2005
Course Call Number 15280
Time TR 2:45pm--4:15pm
Location Dept Room/HSC Lib 226
Website http://www.stat.unm.edu/~erike/courses/bms516/
Syllabus doc
Textbook Johnathon Pevsner
(2003), Bioinformatics and
functional genomics. Wiley-Liss Press.
Other course materials on
reserve in the HSC library and/or at the
class website:
research articles
supplementary text "The Cell
Cycle by A.W. Murray and T. Hunt, Freeman and Co., 1993
Other suggested materials You
may want to bring in a CD or
flashdrive for each lab if you wish to back up your work.
Course Director
Stephanie Ruby e-mail,
272-5830, CRTC 330
Instructors
Susan Atlas e-mail web, 277-1509,
Physics 1105
Scott Ness e-mail web, 272-9883,
CRF 125
Mary Ann Osley e-mail,
272-4839, CRF
123.
Marianne Berwick (Guest lecturer) e-mail, 272- , RIB
Teaching Assistant
Erik Barry Erhardt e-mail web, 272-4813, Humanities
346
Students
Jennifer Buntz e-mail
Leyma Deharo e-mail
Rafael Medina e-mail (audit)
(David Davis e-mail) (drop
3/26/05)
Grading
3 lab projects: 15% each
(45%)
3 lab problems: 5% each
(15%)
2 exams: 10% each (20%)
2 paper presentations: 10% each (20%)
credit/nocredit for some labs
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Catalog Description
Genetic and genomic approaches in model organisms and humans to study
biological processes at the molecular, cellular, tissue, organism
population and evolutionary levels. It also provided an introduction to
bioinformatics and computational methods used in such studies.
Prerequisites
BMS507 and BMS 508, or equivalent courses and consent of the course
director Stephanie Ruby e-mail.
Detailed Course Description
Modern biology requires a knowledge of genetics and gene function as
well as a familiarity with the bioinformatic methods necessary to
tackle difficult problems. This course is an introduction for
biologists who need to become familiar with basic computational and
computer methods required for pursuing modern genetic and genomic
problems. The course will build on a basic understanding of genetics
and genomics by focusing on an important but highly relevant topic
regulation of the cell cycle in yeast and mammalian cells. It will
combine lectures with laboratory exercises and instruction on
computer-based methods. Special emphasis will be placed on sequence
analysis, transcription profiling, gene and protein regulatory
networks, signal transduction and regulation. The goal is for students
to develop both an understanding of the cell cycle and the ability to
access and manipulate genetic and genomic information using currently
available computer programs and web-based tools. |
Announcements
1/20/05
Reading:
- Chapters 1-4;
6, 8 of "The Cell Cycle, an Introduction"
2/1/05
Reading:
From textbook (Bioinformatics and Functional Genomics):
- Chapter 7, Gene Expression:
Microarray Data Analysis
Background for in-class/take-home lab (Feb 8):
- EisenCluster.pdf
- Eisen et al., “Cluster analysis
and display of genome-wide expression patterns," PNAS 95:14863-14868
(1998).
- Bittner2000.pdf (supplemental)
- Bittner et al., "Molecular classification of cutaneous
melanoma by gene
expression profiling," Nature 406:536-540 (2000).
On mathematics and computation in biology:
- Bialek_Botstein04.pdf
- Bialek and Botstein, Science
303:788-790 (2004).
Reading assignment (February 15
and 17 lectures; * = required)
- Paper_2-15-05_SimonBJC.pdf
- R. Simon,
Diagnostic and prognostic prediction using gene expression profiles in
high-dimensional microarray data. Br. J. Cancer 89:1599-1604
(2003). [Review]
- *Paper_2-15-05_Simon_JNCI_1999.pdf
- R. Simon et
al., Pitfalls in the use of DNA microarray data for diagnostic and
prognostic classification. J. National Cancer Inst. 95:14-18
(2003).
- Paper_2-15-05_Guyon2002.pdf
- I. Guyon et al. Gene selection for cancer classification
using support vector machines. Machine Learning 46:389422
(2002). [SVM]
- *Paper_2-15-05_Khan2001.pdf
- J. Khan et al.
Classification and diagnostic prediction of cancers using gene
expression profiling and artificial neural networks. Nature Medicine
7:673 (2001). [Neural networks]
- Paper_2-15-05_Dudoit_TR576.pdf
- S. Dudoit et al.
Comparison of discrimination methods for
the classification of tumors using gene expression data. Technical
Report #576, June, 2000, Dept. Statistics, UC Berkeley (Berkeley, CA).
[Discriminant analysis]
- *Paper_2-15-05_Dudoit_JASA_2002.pdf
- S. Dudoit et al. Comparison of discrimination methods
for
the classification of tumors using gene expression data. J. Am.
Stat. Assoc. 97:77-87 (2002) (short/edited version of above technical
report).
- Paper_2-15-05_Multiclass_PNAS_2001.pdf
- S. Ramaswamy et al. Multiclass cancer diagnosis using tumor
gene expression signatures. Proc. Natl. Acad. Sci. USA
98:15149-15154 (2001).
- Paper_2-15-05_Friedman_2000.pdf
- A. Ben-Dor et al. Tissue classification with gene
expression profiles. J. Comp. Biol. 7(3,4):559-584 (2000).
[Highly technical, but important paper; ROC, TNoM]
- Paper_2-15-05_Helman_etal_JCompBiol2004.pdf
- P. Helman et al. Bayesian networks for classification of
gene expression data. J. Comp. Biol 2004. [Highly technical, but
gives a sense of the application of Bayesian networks to microarray
classification problem].
Background
References and Further Reading (optional)
Pattern Recognition,
general
- C. M. Bishop. Neural Networks for Pattern Recognition.
(Oxford, New York, 1995).
- R. O. Duda, P. E. Hart, and D. G. Stork. Pattern
Classification, Second Edition. (Wiley, New York, 2000).
- Paper_2-15-05_Jain_1999.pdf
- A. K. Jain, R. P. W. Duin, and J. Mao. Statistical Pattern
Recognition: A Review. Preprint, November, 1999.
(posted on website)
Statistical Analysis and Learning
(with varied emphasis on microarray data)
- T. Hastie, R. Tibshirani, and J. Friedman. The
Elements of Statistical Learning: Data Mining, Inference, and
Prediction. (Springer, New York, 2001).
- T. Speed, ed. Statistical Analysis of Gene Expression
Microarray Data. (Chapman and Hall/CRC, 2003).
- S. Draghici. Data Analysis Tools for DNA Microarrays.
(Chapman and Hall/CRC, 2003).
2/17/05
Reading:
- Quackenbush.pdf
- J. Quackenbush, Computational analysis of microarray data.
Nature Rev. 2: 418-427 (2001) [Review]
Reading assignment (February 22
lecture and 24 lab; * = required)
- *Khan et al. - (previously posted)
- *Ramaswamy et al. - (previously posted)
- *GAKNN.pdf - L. Li et al,
Bioinformatics 17:1131-1142 (2001)
- MIT-leukemia.pdf - T. R.
Golub et al., Science 286:531-537 (1999)
- Alizadeh2000.pdf - Alizadeh
et al., Nature 403:503-511 (2000)
- AlonPNAS.pdf - Alon et al., PNAS
96:6745-6750 (1999)
Suggested Reading
- AKT_regul_p27_NatMed02.pdf
- AKTphosphoryl_p27_NatMed02.pdf
- estrogens_p27_JBC03.pdf
- LongLiveFKHDs.pdf
- LymphomaCellCycle.pdf
- p27Haploinsuff.pdf
- p27Review_Science.pdf
- p27Review_Trends.pdf
- p57_SCF_PNAS03.pdf
3/8/05
Reading:
- Textbook, chapter 18, pages 647-696.
Additional Resources:
On-line glossaries:
- See page 734 of your textbook
Book:
- “Bioinformatics for Geneticists” by Michael R. Barnes and
Ian C. Gray, 2003, John Wiley & Sons, Inc., Hoboken, NJ, 408 pp.
Exam on March 10.
Papers for presentations on March 24 will be available on March 10.
3/10/05
Papers for selection for
presentations (part 1).
Please email to sruby@unm.edu
(by Monday, March 14, 5 pm)
your first and second choice of the article that you wish to present
for the week of March 21, 2005.
- Bond_et_al_04.pdf -
Bond, G.L., et al. A single nucleotide polymorphism in the MDM2
promoter attenuates the p53 tumor suppressor pathway and accelerates
tumor formation in humans. 2004. Cell 119, pp. 591–602.
- Sweet-Cordaro_et_al_04.pdf -
A. Sweet-Cordero et al An oncogenic KRAS2 expression signature
identified by cross-species gene-expression analysis. Nature
Genetics 37, 48 - 55 (2004).
- Roepman_et_al_05.pdf -
Roepman et al. An expression profile for diagnosis of lymph node
metastases from primary head and neck squamous cell carcinomas. Nature
Genetics 37, 182 - 186 (2005)
- Lee_et_al_04.pdf - Lee
et al. Evidence for nucleosome depletion at active regulatory
regions genome-wide. Nature Genetics 36, 900 (2004)
- Rustici_et_al_04.pdf -
Rustici et al. Periodic gene expression program of the fission
yeast cell cycle. Nature Genetics 36, 810 (2004)
- Shyamsundar_et_al_05.pdf -
Shyamsundar at al. A DNA microarray survey of gene expression in
normal human tissues. Genome Biology 2005 6:R22
Reading:
- Chapter 2 (pp 15-39)
Reading:
- Chapters 4 and 5 of textbook
Lab problem will be handed out this Thursday and due Thursday, April 7.
YFG/P sequence handed out on Thursday, March 31.
3/31/05
4/7/04
Reading for labs on 04-07-05 and
04-14-05:
- Chapters 8 and 9
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