PH296, Section 33
Fall 2002
Class presentations
N. B. Contact me (sandrine@stat.berkeley.edu) by October 21st to discuss your project and schedule your class presentation.
Guidelines for preparing your
presentation (pdf)
Suggested references
N.B. This list is still being updated and is obviously
incomplete. The references below are simply starting points to guide your
search of presentation topic. Feel free to suggest other topics and
papers.
Landmark papers and related discussions
Mendel's experiments
-
G. Mendel (1865). Experiments in plant hybridization. Read at the
February 8 and March 8, 1865 meetings of the Naturforschedenden
Vereins (the Natural History Society) of Brunn (now Brno, in the Czech
Republic). MendelWeb
-
R. A. Fisher (1936). Has Mendel's work been rediscoveed?
Ann. Sci. , 1: 115--137.
-
See also discussion in D. Freedman, R. Pisani, and R. Purves
(1998). Statistics, Norton.
Linkage analysis
-
T. H. Morgan (1911). Random segregation versus coupling in Mendelian inheritance.
Science, 34: 384.
-
A. H. Sturtevant (1913). The linear arrangement of six sex--linked factors in Drosophila, as shown by their mode of association.
J. Exp. Zool., 14: 43--59.
-
J. B. S. Haldane (1919). The combination of linkage values, and the
calculation of distances between the loci of linked factors.
J. Genetics, 8: 299--309.
-
See also discussion in M. S. McPeek (1996). An introduction to
recombination and linkage analysis. In T. P. Speed and M. S. Waterman
(eds), Genetic Mapping and DNA Sequencing, Vol. 81 of
IMA Volumes in Mathematics and its Applications, Springer-Verlag, New York.
DNA structure and replication
-
J. D. Watson and F. H. C. Crick (1953). Molecular structure of nucleic
acids.
Nature, 171:737--738
-
M. Meselson and F. W. Stahl (1958). The replication of DNA in
Escherichia coli. Proceedings of the National Academy of Sciences, USA
, 44: 671--682. (JSTOR)
Protein structure and synthesis
*** ADD
Microarray data analysis
Genetic
Epidemiology and Microarrays
Special issue of Genetic Epidemiology, Vol 23., Issue 1, 2002.
Pre-processing
-
W. Huber, A.
von Heydebreck, H. Sultmann, A. Poustka, and M. Vingron (2002). Variance
stabilization applied to microarray data calibration and to the quantification
of differential expression. Bioinformatics, 18 (suppl. 1).
-
R.A. Irizarry,
B. Hobbs, F. Collin, Y. D. Beazer-Barclay, K. J. Antonellis, U. Scherf,
and T. P. Speed (2002). Exploration, Normalization, and Summaries of High
Density Oligonucleotide Array Probe Level Data. Biostatistics
(To
appear).
Differential expression, clustering, classification
-
J. H. Friedman and
J. J. Meulman (2002). Clustering Objects on Subsets of Attributes.
-
R. Jorsten
and B. Yu (Submitted). Simultaneous Gene Clustering and Subset Selection
for Classification via MDL.
-
M. K. Kerr and G.
A Churchill (2001). Experimental design for gene expression microarrays.
Biostatistics,
2:183--201.
-
M. A. Newton, C.M. Kendziorski,
C.S. Richmond, F.R. Blattner, and K.W. Tsui (2001). On differential variability
of expression ratios: Improving statistical inferenceabout gene expression
changes from microarray data. Journal of Computational Biology,
8:37--52.
-
R.D. Wolfinger, G. Gibson, E.D. Wolfinger, L. Bennett, H. Hamadeh, P. Bushel,
C. Afshari, and R.S. Paules (2001). Assessing gene significance from cDNA
microarray expression data via mixed models. Journal of Computational
Biology, 8(6):625-637.
Comparative genomic hybridization
-
J. R. Pollack, C. M. Perou, A. A. Alizadeh, M. B. Eisen,
A. Pergamenschikov, C. F. Williams, S. S. Jeffrey, D. Botstein, and
P. O. Brown (1999). Genome-wide analysis of DNA copy-number changes
using cDNA microarrays. Nature Genetics,
23(1):41--46. (Stanford Genomic Resources).
-
A. M. Snijders, N. Nowak, R. Segraves, S. Blackwood, N. Brown,
J. Conroy, G. Hamilton, A. K. Hindle, B. Huey, K. Kimura, S. Law,
K. Myambo, J. Palmer, B. Ylstra, J. P. Yue, J. W. Gray, A. N. Jain,
D. Pinkel, and D. G. Albertson (2001). Assembly of microarrays for
genome-wide measurement of DNA copy number. Nature Genetics,
29: 263--264. (Main article + supplements).
Combined sequence and microarray data analysis
-
H. J. Bussemaker, H. Li, and E. D. Siggia (2001). Regulatory element
detection using correlation with expression. Nature genetics, 27(2):167-171.
-
I. Holmes and W. J. Bruno (2000). Finding regulatory elements using joint
likelihoods for sequence and expression profile data. In
Proc. ISMB, AAAI Press, San Diego, 8:202--210.
-
L. J. Jensen and S. Knudsen (2000). Automatic discovery of regulatory patterns in
promoter regions based on whole cell expression data and functional
annotation. Bioinformatics, 16(4):326-333.
-
S. Keles, M.J.
van der Laan, and M. B. Eisen (2002). Identification of Regulatory
Elements Using A Feature Selection Method. Bioinformatics (To
appear).
Sequence analysis
-
I. Dubchak and L. Pachter (2002). The computational challenges of
applying comparative-based computational methods to whole genomes. Briefings
in Bioinformatics, 3(1):18-22.
-
R. Durbin, S. Eddy, A. Krogh, and G. Mitchison (1998). Biological
sequence analysis: Probabilistic models of proteins and nucleic acids. Cambridge University Press.
- S. R. Eddy (1998). Profile hidden Markov models. Bioinformatics, 14:755--763, 1998.
A review of the profile HMM literature from 1996-1998.
-
L. Pachter, M. Alexandersson, S. Cawley (2002). Applications of Generalized Pair Hidden Markov Models to Alignment and Gene Finding Problems. Journal of Computational Biology, 9(2):389 - 400.
- Motif finding
- MEME
T. L. Bailey and C. Elkan (1995). Unsupervised Learning of Multiple Motifs in Biopolymers using EM. Machine Learning, 21(1-2): 51--80.
- Gibbs motif sampling
C. E. Lawrence, S. F. Altschul, M. S. Boguski, J. S. Liu, A. F. Neuwald and J. C. Wootton (1993).Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. Science, 262: 208--214.
Protein structure and function
-
T. Head--Gordon and J. C. Wooley
(2001). Computational Challenges in Structural and Functional Genomics.
IBM
Systems Journal, 40(2):265--296.
-
*** ADD
Genetic mapping
-
K.W. Broman (2001).
Review of statistical methods for QTL mapping in experimental crosses.
Lab
Animal, 30(7):44--52.
- K. Chase, D. R. Carrier, F. R. Adler, T. Jarvik, E. A. Ostrander, T. D. Lorentzen and K. G. Lark (2002). Genetic basis for systems of skeletal quantitative traits: principal component analysis of the canid skeleton. Proceedings of the National Academy of Sciences, USA
, 99(15): 9930--9935.
-
A. Grupe, S. Germer, J. Usuka, D. Aud, J. K. Belknap, R. F. Klein, M. K.
Ahluwalia, R. Higuchi, and G Peltz (2001). In Silico Mapping of Complex
Disease-Related Traits in Mice. Science, 292:1915--1918.
-
Web supplement
-
Technical comments: E. J. Chesler, S. L. Rodriguez--Zas, J. S. Mogil, A.
Darvasi, J. Usuka, A. Grupe, S. Germer, D. Aud, J. K. Belknap, R.
F. Klein, M. K. Ahluwalia, R. Higuchi, and G. Peltz (2001). In Silico Mapping
of Mouse Quantitative Trait Loci. Science, 294:2423.
- Maize genetics:
-
G. W. Beadle (1939). Teosinte and the origin of maize. J. Hered., 30: 245--247.
- G. W. Beadle (1980). The ancestry of corn. Scientific American 242:
112--119.
- J. F. Doebley, A. Stec and C. Gustus (1995). Teosinte branched1 and the origin
of maize: evidence for epistasis and the evolution of dominance. Genetics, 141: 333--346.
- J. F. Doebley and A. Stec (1991) Genetic analysis of the morphological
differences between maize and teosinte. Genetics, 129: 285--295.
Computing
-
R packages for Bioinformatics
-
Basic Local Alignment Search Tool - BLAST
-
W. Ewens and G. R. Grant (2001). Statistical Methods in Bioinformatics: An
Introduction. Springer-Verlag, New York. (Chapter 9).
-
BLAST
-
C. Gibas and P. Jambeck (2001). Developing Bioinformatics Computer Skills.
O'Reilly.
-
Microarray G. Parmigiani, E. S. Garrett, R. A. Irizarry and S. L. Zeger
(eds). The Analysis of
Gene Expression Data: Methods and Software, Springer, New York (To
appear).
Databases