A. Introduction

1.      Primer on Molecular Genetics

2.      Chapter 1 from Molecular Biology for Computer Scientists

3.      Molecular biology database collection, Nucleic Acids Research, 34, Jan. 2006.

4.      List of sequenced genomes

5.      Interrelating genomic data

6.      Defining bioinformatics

7.      Bioinformatics in the Post-sequence Era, M. Kanehisa and P. Bork, Nature Genetics, 33, March 2003.

8.      Data Management for the Biosciences, Report of the NSF/NLM Workshop of Data Management for Molecular and Cell Biology, Feb. 2003

9.      Bionformatics and Medical Informatics: Collaborations on the Road to Genomic Medicine?, V. Maojo and C.A. Kulikowski, JAMIA, 10(6), Nov/Dec 2003, pp. 515-522.

10.  Pharmacogenetics and Drug Development: The Path to Safer and More Effective Drugs, A.D. Roses, Nature Reviews, Genetics, 5, September 2004, pp. 645-656.

11.  What is the relevance of bioinformatics to pharmacology?, P. A. Whittaker, Trends in Pharmacological Sciences, 24(8), August 2003, pp. 434-439.

12.  Plant Bioinformatics: from Genome to Phenome, D. Edwards and J. Batley, Trends in Biotechnology, 22(5), May 2004, pp. 323-237.

 

B. Sequence analysis

 

  1. A model of evolutionary change in proteins, M. O. Dayhoff, R. M. Schwartz, and B. C. Orcutt
  2. Homology, a personal view on some of the problems, W.M. Fitch, TIG, 16(5), May 2000, pp. 227-231.

3.      Where did the BLOSUM62 alignment score matrix come from?, S.R. Eddy, Nature Biotechnology, 22(8), August 2004.

4.      Amino Acid substitution matrices from Protein Blocks, Heinkoff and Heinkoff, PNAS, 89(22):10915-10919, November 1992.

  1. Protein sequence comparison and protein evolution, W.R. Pearson, Tutorial, ISMB 2000.
  2. Initial sequencing and comparative analysis of the mouse genome, Mouse Genome Sequencing Consortium, Nature, vol. 402, Dec. 2002.
  3. Gapped BLAST and PSI_BLAST: a new generation of protein database search programs, Altschul et al, NAR, 25(17), pp. 3389-3402.
  4. The statistics of sequence similarity scores, NCBI.
  5. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, positions-specific gap penalties and weight matrix choice. Thompson, J.D., Higgins, D.G. and Gibson, T.J. (1994) Nucleic Acids Research, 22:4673-4680.
  6. Alignment of Whole Genomes, Delcher A. L., Kasif S., Fleischmann R. D., Peterson J, White O., Salzberg S.L., Nucleic Acids Research, 27:11, 2369-2376. (1999).
  7. Human and Mouse Gene Structure: Comparative Analysis and Application to Exon Prediction, Batzoglou S., Pachter L, Mesirov J., Berger, B., Lander E. S., Genome Research, 10:950. (2000).

 

C. Structure analysis

 

1.      Structure comparison and structure pattern, An algorithmic approach, Eidhammer, I. and Jonassen, I. Tutorial, ISMB'2001.

2.      SCOP: A Structural Classification of Proteins Database for the Investigation of Sequences and Structures. Murzin, A., Brenner, S.E., Hubbard, T., and Chothia, C., Journal of Molecular Biology, Vol. 247, 1995, pp. 536-540

3.      Protein structure comparison by alignment of distance matrices. Holm, L., and Sander, C., Journal of Molecular Biology,  Vol. 233, 1993, pp. 123-138.

4.        A systematic comparison of protein structure classifications: SCOP, CATH and FSSP, C. Hadley and D. Jones, Structure September 1999, 7:1099-1112.

5.      Critical Assessment of Methods of Protein Structure Prediction (CASP)-Round V, PROTEINS: Structure, Function, and Genetics 53:334–339 (2003).

D. Phylogeny

1.      Phylogeny for the faint of heart: a tutorial. Baldauf SL.  Trends Genet. 2003 June, 19(6):345-51.

2.      Phylogeny Estimation and Hypothesis Testing Using Maximum Likelihood, John P. Huelsenbeck; Keith A. Crandall, Annual Review of Ecology and Systematics, Vol. 28. (1997), pp. 437-466.

3.      The neighbor-joining method: a new method for reconstructing phylogenetic trees, N. Saitou N and M. Nei, Molecular Biology and  Evolution, July1987, 4(4), pp. 406-25.

4.      Lectures on molecular systematics and evolution.

5.      Phylogenetic Tree Computation Tutorial, F. Olken.

6.      Mitochondrial genome variation and the origin of modern humans, Max Ingman, Henrik Kaessmann, Svante Paabo & Ulf Gyllensten, Nature, vol. 408, Dec. 2000.

E. Microrrays

1.      Genomics, gene expression, and DNA arrays, D.J. Lockhart and E.A. Winzeler, Nature, 405, June 2000, pp. 827-836.

2.      Perspective: Microarray technology, seeing more than spots, C.A. Afshari, Endocrinology, 143(6), June 2002, pp. 1983-1989.

3.      Navigating gene expression using microarrays -- a technology review, A. Schulze and J. Downward, Nature Cell Biology, 3, August 2001, pp. E190-E195.

4.      Cluster Analysis and Display of Genome-wide Expression Patterns, Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D., Proc. Natl. Acad. Sci. USA, 95:12863-14868, 1998.

5.      Experimental annotation of the human genome using microarray technology, D.D. Shoemaker et al, Nature, 409, Feb 2001, pp. 922-927.

F. Pathways

1.      Inferring cellular models using probabilistic graphical models, N. Friedman, Science, Jan 2004, pp. 799-805.

2.      Discovering molecular pathways from protein interaction and gene expression data, E. Segal, H. Wang and D. Koller, Bioinformatics, 19, supplement, pp. 264-272.

3.      Protein network inference from multiple genomic data: a supervised approach, Y. Yamanishi, J.-P. Vert, and M. Kanehisa, Bioinformatics, 20, supplement, pp. 363-370.

4.      A Bayesian network approach for predicting protein-protein interactions from genomic data, Jansen et al., Science, 302, Oct. 2003, pp. 449-453.

5.      Function prediction and protein networks, Current opinions in cell biology, 15, 2003, pp. 191-198.

6.      Metabolic pathways in the post-genome era, J.A. Papin et al., Trends in Biochemical Sciences, 28(5), May 2003, pp. 250-258.

7.      Biological networks, E. Alm and A.P. Arkin, Current Opinions in Structural Biology, 2003, 13, pp. 193-202.