Optimal stepwise experimental design for pairwise functional interaction studies

Bioinformatics

Volumn 24, Issue 23, 2008, Pages 2733-2739

  Casey, Fergal P ^a   Cagney, Gerard ^b   Krogan, Nevan J ^b   Shields, Denis C ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CLUSTER ANALYSIS; COMPUTER SIMULATION; EXPERIMENTAL DESIGN; GENE INTERACTION; GENETIC EPISTASIS; INFORMATION PROCESSING; MATHEMATICAL COMPUTING; PRIORITY JOURNAL; STATISTICAL MODEL;

MAMMALIA;

EID: 56649116093     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btn472     Document Type: Article

References (23)

1. Ashburner,M. et al. (2000) Gene ontology: Tool for the unification of biology. Nat. Genet., 25, 25-29.
2. Boone,C. et al. (2007) Exploring genetic interactions and networks with yeast. Nat. Rev. Genet., 8, 437-449.
3. Boyle,E. et al. (2004) Go::Termfinder - open source software for accessing gene ontology information and finding significantly enriched gene ontology terms associated with a list of genes. Bioinformatics 20, 3710-3715.
4. Casella,G. and Berger,R. (1983) Statistical Inference. Duxbury Press, Belmont, CA, USA.
5. Collins,S. et al. (2007) Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map. Nature, 446, 806-810.
6. Davierwala,A. et al. (2005) Systematic yeast synthetic lethal and synthetic dosage lethal screens identify genes required for chromosome segregation. Nat. Genet., 37, 1147-52.
7. Dempster,A. et al. (1977) Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. Ser. B, 39, 1-38.
8. Draper,B. et al. (2005) EM in high-dimensional spaces. IEEE Trans. Syst. Man Cybern. Part B, 35, 571-577.
9. Fraley,C. (1998a) Algorithms for model-based gaussian hierarchical clustering. SIAM J. Sci. Comput., 20, 270-281.
10. Fraley,C. (1998b) How many clusters? Which clustering method? Answers via model-based cluster analysis. Comput. J., 41, 578-588.
11. Gavin,A.C. et al. (2006) Proteome survey reveals modularity of the yeast cell machinery. Nature, 440, 631-636.
12. Janda,K. (1994) Tagged versus untagged libraries: Methods for the generation and screening of combinatorial chemical libraries. Proc. Natl Acad. Sci. USA, 91, 10779-10785.
13. Jin,F. et al. (2007) A yeast two-hybrid smart-pool-array system for protein-interaction mapping. Nat. Methods, 4, 405-407.
14. Krogan,N.J. et al. (2006) Global landscape of protein complexes in the yeast Saccharomyces cerevisiae. Nature, 440, 637-643.
15. Lappe,M. and Holm,L. (2004) Unraveling protein interaction networks with near-optimal efficiency. Nat. Biotechnol., 22, 98-103.
16. Lehar,J. et al. (2007) Chemical combination effects predict connectivity in biological systems. Mol. Syst. Biol., 3, 80.
17. Lehner,B. et al. (2006) RNAi screens in Caenorhabditis elegans in a 96-well liquid format and their application to the systematic identification of genetic interactions. Nat. Protoc., 1, 1617-1620.
18. Pan,X. et al. (2004) A robust toolkit for functional profiling of the yeast genome. Mol. Cell., 16, 487-496.
19. Raftery,A. and Dean,N. (2006) Variable selection for model-based clustering. J. Am. Stat. Assoc., 101, 168-178.
20. Schuldiner,M. et al. (2005) Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell, 123, 507-519.
21. St Onge,R. et al. (2007) Systematic pathway analysis using high-resolution fitness profiling of combinatorial gene deletions. Nat. Genet., 39, 199-206.
22. Yeast GO-Slim (2008) Yeast macromolecular complex go slim. Available at ftp://genome-ftp.stanford.edu/pub/yeast/data_download/ literature_curation/go_protein_complex_slim.tab (last accessed date July 2008).
23. Yeh,P. et al. (2006) Functional classification of drugs by properties of their pairwise interactions. Nat. Genet., 38, 489-494.