Correlacionando genes e doenças através de caminhos metabólicos
Resumo
Um dos principais desafios da ciência é identificar os fatores que causam essas doenças, dentre estes fatores estão os genes. Neste trabalho, será apresentada uma metodologia para priorizar genes e vias metabólicas relacionados a uma doença complexa, com o desafio de descobrir quais os genes podem contribuir para desencadear uma doença complexa. O objetivo é desenvolver uma metodologia para predição de gene-doença através da integração de dados de genes-doencas-vias metabólicas, visando a descoberta de novos genes associado a doença.
Referências
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Duarte, N. and Becker, S. A. (2007). Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proceedings of the National Academy of Sciences of the United States of America, 104(6):1777–1782.
Goh, K. I. and Choi, I. G. (2012). Exploring the human diseasome: The human disease network. Briefings in Functional Genomics, 11(6):533–542.
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Lee, D. S., Park, J., Kay, K. A., Christakis, N. A., Oltvai, Z. N., and Barabasi, A. L. (2008). The implications of human metabolic network topology for disease comorbidity. Proceedings of the National Academy of Sciences of the United States of America, 105(29):9880–9885.
Lee, I., Blom, U. M., Wang, P. I., Shim, J. E., and Marcotte, E. M. (2011). Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Research, 21(7):1109–1121.
Li, Y. and Agarwal, P. (2009). A pathway-based view of human diseases and disease relationships. PLoS ONE, 4(2):e4346.
Menche, J., Sharma, A., Kitsak, M., Ghiassian, S. D., Vidal, M., Loscalzo, J., and Barabási, A.-L. (2015). Disease networks. Uncovering disease-disease relationships through the incomplete interactome. Science, 347(6224):1257601.
Ritchie, M. D., Holzinger, E. R., Li, R., Pendergrass, S. A., and Kim, D. (2015). Methods of integrating data to uncover genotype–phenotype interactions. Nature Reviews Genetics, 16(2):85–97.
Vidal, M., Cusick, M. E., and Barabási, A.-L. (2011). Interactome networks and human disease. Cell, 144(6):986–98.
Wu, X., Jiang, R., Zhang, M. Q., and Li, S. (2008). Network-based global inference of human disease genes. Molecular Systems Biology, 4(189):189.
Zhou, X., Menche, J., Barabási, A.-L., and Sharma, A. (2014). Human symptoms–disease network. Nature Communications, 5(May).
Barabási, A.-L., Gulbahce, N., and Loscalzo, J. (2011). Network Medicine: A Network-based Approach to Human Disease. Nature Reviews Genetics, 12(1):56–68.
Barrenas, F., Chavali, S., Holme, P., Mobini, R., and Benson, M. (2009). Network Properties of Complex Human Disease Genes Identified through Genome-Wide Association Studies. PLoS ONE, 4(11):2–7.
Duarte, N. and Becker, S. A. (2007). Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proceedings of the National Academy of Sciences of the United States of America, 104(6):1777–1782.
Goh, K. I. and Choi, I. G. (2012). Exploring the human diseasome: The human disease network. Briefings in Functional Genomics, 11(6):533–542.
Goh, K.-i., Cusick, M. E., Valle, D., Childs, B., and Vidal, M. (2007). The human disease network. Proceedings of the National Academy of Sciences, 104(21):8685–8690.
Lee, D. S., Park, J., Kay, K. A., Christakis, N. A., Oltvai, Z. N., and Barabasi, A. L. (2008). The implications of human metabolic network topology for disease comorbidity. Proceedings of the National Academy of Sciences of the United States of America, 105(29):9880–9885.
Lee, I., Blom, U. M., Wang, P. I., Shim, J. E., and Marcotte, E. M. (2011). Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Research, 21(7):1109–1121.
Li, Y. and Agarwal, P. (2009). A pathway-based view of human diseases and disease relationships. PLoS ONE, 4(2):e4346.
Menche, J., Sharma, A., Kitsak, M., Ghiassian, S. D., Vidal, M., Loscalzo, J., and Barabási, A.-L. (2015). Disease networks. Uncovering disease-disease relationships through the incomplete interactome. Science, 347(6224):1257601.
Ritchie, M. D., Holzinger, E. R., Li, R., Pendergrass, S. A., and Kim, D. (2015). Methods of integrating data to uncover genotype–phenotype interactions. Nature Reviews Genetics, 16(2):85–97.
Vidal, M., Cusick, M. E., and Barabási, A.-L. (2011). Interactome networks and human disease. Cell, 144(6):986–98.
Wu, X., Jiang, R., Zhang, M. Q., and Li, S. (2008). Network-based global inference of human disease genes. Molecular Systems Biology, 4(189):189.
Zhou, X., Menche, J., Barabási, A.-L., and Sharma, A. (2014). Human symptoms–disease network. Nature Communications, 5(May).
Publicado
02/07/2017
Como Citar
DA SILVA, Carla Fernandes; ABRAHAM, Kuruvilla Joseph; RUIZ, Evandro Eduardo Seron.
Correlacionando genes e doenças através de caminhos metabólicos. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 17. , 2017, São Paulo.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2017
.
p. 2068-2071.
ISSN 2763-8952.
DOI: https://doi.org/10.5753/sbcas.2017.3725.
