Exploring the optimal strategy to predict essential genes in microbes

Biomolecules

Volumn 2, Issue 1, 2012, Pages

  Deng, Jingyuan ^a,b   Tan, Lirong ^a,b   Lin, Xiaodong ^d   Lu, Yao ^e   Lu, Long J ^a,b,c  

^a CINCINNATI CHILDREN S HOSPITAL RESEARCH FOUNDATION   (United States)

^b University of Cincinnati   (United States)

^c UNIVERSITY OF CINCINNATI COLLEGE OF MEDICINE   (United States)

^d RUTGERS UNIVERSITY   (United States)

^e SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Annotation; Essential genes; Machine learning

Indexed keywords

ACINETOBACTER BAYLYI; ARTICLE; ASPERGILLUS FUMIGATUS; BACILLUS SUBTILIS; BIOENGINEERING; CELL FUNCTION; CELL STRUCTURE; ESCHERICHIA COLI; ESSENTIAL GENE; GENE DELETION; GENE SEQUENCE; GENE TRANSFER; GOLD STANDARD; MICROORGANISM; MUTAGENESIS; NEUROSPORA CRASSA; NONHUMAN; PNEUMOCYSTIS CARINII; PREDICTION; PSEUDOMONAS AERUGINOSA; RECEIVER OPERATING CHARACTERISTIC; SACCHAROMYCES CEREVISIAE; SYNTHETIC BIOLOGY; TRANSPOSON;

EID: 85016385416     PISSN: None     EISSN: 2218273X     Source Type: Journal    
DOI: 10.3390/biom2010001     Document Type: Article

References (14)

1. Kyte, J.; Doolittle, R.F. A simple method for displaying the hydropathic character of a protein. J. Mol. Biol. 1982, 157, 105-132.
2. Wright, F. The 'effective number of codons' used in a gene. Gene 1990, 87, 23-29.
3. Fuglsang, A. The 'effective number of codons' revisited. Biochem. Biophys. Res. Commun. 2004, 317, 957-964.
4. Sharp, P.M.; Li, W.H. The codon adaptation index-A measure of directional synonymous codon usage bias, and its potential applications. Nucleic Acids Res. 1987, 15, 1281-1295.
5. Lu, Z.; Szafron, D.; Greiner, R.; Lu, P.; Wishart, D.S.; Poulin, B.; Anvik, J.; Macdonell, C.; Eisner, R. Predicting subcellular localization of proteins using machine-learned classifiers. Bioinformatics 2004, 20, 547-556.
6. Sonnhammer, E.L.; von Heijne, G.; Krogh, A. A hidden markov model for predicting transmembrane helices in protein sequences. Proc. Int. Conf. Intell. Syst. Mol. Biol. 1998, 6, 175-182.
7. Krogh, A.; Larsson, B.; von Heijne, G.; Sonnhammer, E.L. Predicting transmembrane protein topology with a hidden markov model: Application to complete genomes. J. Mol. Biol. 2001, 305, 567-580.
8. Chen, Y.; Xu, D. Understanding protein dispensability through machine-learning analysis of high-throughput data. Bioinformatics 2005, 21, 575-581.
9. Jeong, H.; Oltvai, Z.N.; Barabasi, A.L. Prediction of protein essentiality based on genomic data. ComPlexUs 2003, 1, 19-28.
10. Barrett, T.; Troup, D.B.; Wilhite, S.E.; Ledoux, P.; Rudnev, D.; Evangelista, C.; Kim, I.F.; Soboleva, A.; Tomashevsky, M.; Edgar, R. Ncbi geo: Mining tens of millions of expression profiles-Database and tools update. Nucleic Acids Res. 2007, 35, D760-D765.
11. Parkinson, H.; Kapushesky, M.; Shojatalab, M.; Abeygunawardena, N.; Coulson, R.; Farne, A.; Holloway, E.; Kolesnykov, N.; Lilja, P.; Lukk, M.; Mani, R.; Rayner, T.; Sharma, A.; William, E.; Sarkans, U.; Brazma, A. Arrayexpress-A public database of microarray experiments and gene expression profiles. Nucleic Acids Res. 2007, 35, D747-D750.
12. Gasch, A.P.; Spellman, P.T.; Kao, C.M.; Carmel-Harel, O.; Eisen, M.B.; Storz, G.; Botstein, D.; Brown, P.O. Genomic expression programs in the response of yeast cells to environmental changes. Mol. Biol. Cell 2000, 11, 4241-4257.
13. Lu, L.J.; Xia, Y.; Paccanaro, A.; Yu, H.; Gerstein, M. Assessing the limits of genomic data integration for predicting protein networks. Genome Res. 2005, 15, 945-953.
14. Yu, H.; Greenbaum, D.; Xin Lu, H.; Zhu, X.; Gerstein, M. Genomic analysis of essentiality within protein networks. Trends Genet. 2004, 20, 227-231.