Biology Reference
In-Depth Information
Turner, K., Zhu, H., Yu, C., Li, S., Jian, M., Zhou, Y., Li, Y., Zhang, X., Li, S., Qin, N.,
Yang, H., Wang, J., Brunak, S., Dore, J., Guarner, F., Kristiansen, K., Pedersen, O.,
Parkhill, J., Weissenbach, J., Bork, P., Ehrlich, S. D., and Wang, J. (2010). A human gut
microbial gene catalogue established by metagenomic sequencing.
Nature
464, 59-65.
Quinlan, R. (1993).
C4.5: Programs for Machine Learning.
Morgan Kaufmann.
Rashid, M., Saha, S., and Raghava, G. P. S. (2007). Support vector machine-based method for
predicting subcellular localization of mycobacterial proteins using evolutionary informa-
tion and motifs.
BMC Bioinformatics
8, 337.
Rattray, J., Floros, J. D., and Linton, R. H. (1999). Computer-aided microbial identification
using decision trees.
Food Control
10, 107-116.
Rausch, C., Weber, T., Kohlbacher, O., Wohlleben, W., and Huson, D. H. (2005).
Specificity prediction of adenylation domains in nonribosomal peptide synthetases
(NRPS) using transductive support vector machines (TSVMs).
Nucleic Acids Res.
33,
5799-5808.
Ravcheev, D. A., Best, A. A., Tintle, N., Dejongh, M., Osterman, A. L., Novichkov, P. S., and
Rodionov, D. A. (2011). Inference of the transcriptional regulatory network in
Staphylo-
coccus aureus
by integration of experimental and genomics-based evidence.
J. Bacteriol.
193, 3228-3240.
Robinson, A. (2007).
The Last Man Who Knew Everything.
Oneworld Publications.
Rohde, H., Qin, J., Cui, Y., Li, D., Loman, N. J., Hentschke, M., Chen, W., Pu, F., Peng, Y.,
Li, J., Xi, F., Li, S., Li, Y., Zhang, Z., Yang, X., Zhao, M., Wang, P., Guan, Y., Cen, Z.,
Zhao, X., Christner, M., Kobbe, R., Loos, S., Oh, J., Yang, J., Danchin, A., Gao, G. F.,
Song, Y., Li, Y., Yang, H., Wang, J., Xu, J., Pallen, M. J., Wang, J., Aepfelbacher, M., and
Yang, R. (2011). Open-source genomic analysis of shiga-toxin-producing
E. coli
.
N. Engl.
J. Med.
365, 718-724.
Rooney-Varga, J. N., Anderson, R. T., Fraga, J. L., Ringelberg, D., and Lovley, D. R. (1999).
Microbial communities associated with anaerobic benzene degradation in a petroleum-
contaminated aquifer.
Appl. Environ. Microbiol.
65, 3056-3063.
Rosales-Colunga, L. M., Garc´a, R. G., and De Le´n Rodr´guez, A. (2010). Estimation of
hydrogen production in genetically modified
E. coli
fermentations using an artificial neu-
ral network.
Int. J. Hydr. Energy
35, 13186-13192.
Ross, I. L., Browne, C. R., and Hume, D. A. (1994). Transcription of individual genes in
eukaryotic cells occurs randomly and infrequently.
Immunol. Cell Biol.
72, 177-185.
Sarker, M., Talcott, C., Madrid, P., Chopra, S., Bunin, B. A., Lamichhane, G.,
Freundlich, J. S., and Ekins, S. (2012). Combining chemoinformatics methods and path-
way analysis to identify molecules with whole-cell activity against
Mycobacteriun tuber-
culosis
.
Pharm. Res.
29, 2115-2127.
Schippa, S., Lebba, V., Barbato, M., Di Nardo, G., Totino, V., Checchi, M. P., Longhi, C.,
Maiella, G., Cucchiara, S., and Conte, M. P. (2010). A distinctive 'microbial signature'
in celiac pediatric patients.
BMC Microbiol.
10, 175.
Schloss, P. D. and Handelsman, J. (2005). Metagenomics for studying unculturable microor-
ganisms: cutting the Gordian knot.
Genome Biol.
6, 229.
Schwikowski, B., Uetz, P., and Fields, S. (2000). A network of interacting proteins in yeast.
Nat. Biotechnol.
18, 1257-1261.
Shannon, C. E. (1948). A mathematical theory of communication.
Bell Syst. Techn. J.
27
(379-423), 623-656.
