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Introduction to the Lab [intro-to-lab]
These constitute a good selection of papers to introduce one to the lab and the general field of bioinformatics.One might start with Luscombe et al. (2002) for an introduction to bioinformatics.
Specific fields are highlighted in other short papers:
In each list, it is probably best to read the papers listed first.
- Data integration for function prediction
- Gerstein et al. (2002), Bertone and Gerstein (2001), Greenbaum et al. (2001)
- Simulation on molecular structure
- Gerstein and Levitt (1998); Gerstein and Chothia (1999)
- Pseudogenes and genome annotation
- Gerstein and Snyder (2003); Harrison and Gerstein (2002)
- Structural genomics
- Gerstein (2000); Teichmann et al. (1999)
- E-publishing
- Gerstein (1999)
- Expression analysis
- Gerstein and Jansen (2000)
Unfortunately, none of these papers give one much detail on the mathematical or computational aspects of the work. For this, it's best to look at some samples of recent research, which are listed below, to get a sense of the type of mining that we are doing -- e.g. Yu & Gerstein (2006), Du et al. (2006), Lu et al., (2005), Yip et al., (2007), and Echols et al. (2003).
- A supervised hidden markov model framework for efficiently segmenting tiling array data in transcriptional and chIP-chip experiments: systematically incorporating validated biological knowledge.
- J Du, JS Rozowsky, JO Korbel, ZD Zhang, TE Royce, MH Schultz, M Snyder, M Gerstein (2006) Bioinformatics 22: 3016-24.
- The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks.
- KY Yip, H Yu, PM Kim, M Schultz, M Gerstein (2006) Bioinformatics 22: 2968-70.
- Genomic analysis of the hierarchical structure of regulatory networks.
- H Yu, M Gerstein (2006) Proc Natl Acad Sci U S A 103: 14724-31.
- Assessing the limits of genomic data integration for predicting protein networks.
- LJ Lu, Y Xia, A Paccanaro, H Yu, M Gerstein (2005) Genome Res 15: 945-53.
- A Bayesian networks approach for predicting protein-protein interactions from genomic data.
- R Jansen, H Yu, D Greenbaum, Y Kluger, NJ Krogan, S Chung, A Emili, M Snyder, JF Greenblatt, M Gerstein (2003) Science 302: 449-53.
- Genomics. Defining genes in the genomics era.
- M Snyder, M Gerstein (2003) Science 300: 258-60.
- MolMovDB: analysis and visualization of conformational change and structural flexibility.
- N Echols, D Milburn, M Gerstein (2003) Nucleic Acids Res 31: 478-82.
- Studying genomes through the aeons: protein families, pseudogenes and proteome evolution.
- PM Harrison, M Gerstein (2002) J Mol Biol 318: 1155-74.
- Proteomics. Integrating interactomes.
- M Gerstein, N Lan, R Jansen (2002) Science 295: 284-7.
- What is bioinformatics? A proposed definition and overview of the field.
- NM Luscombe, D Greenbaum, M Gerstein (2001) Methods Inf Med 40: 346-58.
- Interrelating different types of genomic data, from proteome to secretome: 'oming in on function.
- D Greenbaum, NM Luscombe, R Jansen, J Qian, M Gerstein (2001) Genome Res 11: 1463-8.
- Integrative data mining: the new direction in bioinformatics.
- P Bertone, M Gerstein (2001) IEEE Eng Med Biol Mag 20: 33-40.
- Integrative database analysis in structural genomics.
- M Gerstein (2000) Nat Struct Biol 7 Suppl: 960-3.
- The current excitement in bioinformatics-analysis of whole-genome expression data: how does it relate to protein structure and function?
- M Gerstein, R Jansen (2000) Curr Opin Struct Biol 10: 574-84.
- Perspectives: signal transduction. Proteins in motion.
- M Gerstein, C Chothia (1999) Science 285: 1682-3.
- E-publishing on the Web: promises, pitfalls, and payoffs for bioinformatics.
- M Gerstein (1999) Bioinformatics 15: 429-31.
- Advances in structural genomics.
- SA Teichmann, C Chothia, M Gerstein (1999) Curr Opin Struct Biol 9: 390-9.
- Simulating water and the molecules of life.
- M Gerstein, M Levitt (1998) Sci Am 279: 100-5.
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