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Cuartas-Arias, M. (2021). Fenómica: una forma de aumentar y perfeccionar las opciones de tratamiento en psicopatología. International Journal of Psychological Research, 14(2), 6–8. https://doi.org/10.21500/20112084.5659
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The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
To give up copyright, the authors allow that, International Journal of Psychological Research, distribute the work more broadly, check for the reuse by others and take care of the necessary procedures for the registration and administration of copyright; at the same time, our editorial board represents the interests of the author and allows authors to re-use his work in various forms. In response to the above, authors transfer copyright to the journal, International Journal of Psychological Research. This transfer does not imply other rights which are not those of authorship (for example those that concern about patents). Likewise, preserves the authors rights to use the work integral or partially in lectures, books and courses, as well as make copies for educational purposes. Finally, the authors may use freely the tables and figures in its future work, wherever make explicit reference to the previous publication in International Journal of Psychological Research. The assignment of copyright includes both virtual rights and forms of the article to allow the editorial to disseminate the work in the manner which it deems appropriate.
The editorial board reserves the right of amendments deemed necessary in the application of the rules of publication.
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Referencias
Bach, B., & First, M. B. (2018). Application of the ICD-11 classification of personality disorders. BMC Psychiatry, 18(1), 1–14. https://doi.org/10.1186/S12888-018-1908-3
Baes, C., & Schenkel, F. (2020). The Future of Phenomics. Animal Frontiers, 10(2), 4–5. https://doi.org/10.1093/AF/VFAA013
Centers for Disease Control and Prevention. (n.d.). HuGE Navigator|Phenopedia|PHGKB. Public Health Genomics and Precision Health Knowledge Base (v7.6). https://phgkb.cdc.gov/PHGKB/phenoPedia.action?firstQuery=obesity&typeSubmit=Go&typeOption=disease&check=n&which=1
Cuartas Arias, J. M., Palacio Acosta, C. A., Valencia, J. G., Montoya, G. J., Arango Viana, J. C., Nieto, O. C., Flórez, A. F., Camarena Medellin, B. E., Montoya, W. R., Lopez Jaramillo, C. A., Achury, J. G., Fuentes, C. C., Berrio, G. B., & Ruiz-Linares, A. (2011). Exploring epistasis in candidate genes for antisocial personality disorder. Psychiatric Genetics, 21(3), 115–124. https://doi.org/10.1097/YPG.0b013e3283437175
Houle, D., Govindaraju, D. R., & Omholt, S. (2010). Phenomics: the next challenge. Nature Reviews Genetics, 11(12), 855–866. https://doi.org/10.1038/nrg2897
Morrison, J. (2015). DSM-5® Guía para el diagnóstico clínico. Manual Moderno. https://store.manualmoderno.com/gpd-dsm-5a-gua-a-para-el-diagna-stico-cla-nico-9786074484892-9786074484908.html
Ospina-Duque, J., Duque, C., Carvajal-Carmona, L., Ortiz-Barrientos, D., Soto, I., Pineda, N., Cuartas, M., Calle, J., Lopez, C., Ochoa, L., Garcia, J., Gomez, J., Agudelo, A., Lozano, M., Montoya, G., Ospina, A., Lopez, M., Gallo, A., Miranda, A., … Ruiz-Linares, A. (2000). An association study of bipolar mood disorder (type I) with the 5-HTTLPR serotonin transporter polymorphism in a human population isolate from Colombia. Neuroscience Letters, 292(3), 199–202. https://doi.org/10.1016/S0304-3940(00)01464-6
Poldrack, R. A., Congdon, E., Triplett, W., Gorgolewski, K. J., Karlsgodt, K. H., Mumford, J. A., Sabb, F. W., Freimer, N. B., London, E. D., Cannon, T. D., & Bilder, R. M. (2016). A phenome-wide examination of neural and cognitive function. Scientific Data, 3(1), 1–12. https://doi.org/10.1038/sdata.2016.110
Vélez, J. I. (2021). Machine Learning based Psychology: Advocating for A Data-Driven Approach. International Journal of Psychological Research, 14(1), 6–11. https://doi.org/10.21500/20112084.5365
Wagner, G. P., Kenney-Hunt, J. P., Pavlicev, M., Peck, J. R., Waxman, D., & Cheverud, J. M. (2008). Pleiotropic scaling of gene effects and the “cost of complexity.” Nature, 452(7186), 470–472. https://doi.org/10.1038/nature06756
Wendt, F. R., Pathak, G. A., Lencz, T., Krystal, J. H., Gelernter, J., & Polimanti, R. (2020). Multivariate genome-wide analysis of education, socioeconomic status and brain phenome. Nature Human Behaviour, 5(4), 482–496. https://doi.org/10.1038/s41562-020-00980-y
Baes, C., & Schenkel, F. (2020). The Future of Phenomics. Animal Frontiers, 10(2), 4–5. https://doi.org/10.1093/AF/VFAA013
Centers for Disease Control and Prevention. (n.d.). HuGE Navigator|Phenopedia|PHGKB. Public Health Genomics and Precision Health Knowledge Base (v7.6). https://phgkb.cdc.gov/PHGKB/phenoPedia.action?firstQuery=obesity&typeSubmit=Go&typeOption=disease&check=n&which=1
Cuartas Arias, J. M., Palacio Acosta, C. A., Valencia, J. G., Montoya, G. J., Arango Viana, J. C., Nieto, O. C., Flórez, A. F., Camarena Medellin, B. E., Montoya, W. R., Lopez Jaramillo, C. A., Achury, J. G., Fuentes, C. C., Berrio, G. B., & Ruiz-Linares, A. (2011). Exploring epistasis in candidate genes for antisocial personality disorder. Psychiatric Genetics, 21(3), 115–124. https://doi.org/10.1097/YPG.0b013e3283437175
Houle, D., Govindaraju, D. R., & Omholt, S. (2010). Phenomics: the next challenge. Nature Reviews Genetics, 11(12), 855–866. https://doi.org/10.1038/nrg2897
Morrison, J. (2015). DSM-5® Guía para el diagnóstico clínico. Manual Moderno. https://store.manualmoderno.com/gpd-dsm-5a-gua-a-para-el-diagna-stico-cla-nico-9786074484892-9786074484908.html
Ospina-Duque, J., Duque, C., Carvajal-Carmona, L., Ortiz-Barrientos, D., Soto, I., Pineda, N., Cuartas, M., Calle, J., Lopez, C., Ochoa, L., Garcia, J., Gomez, J., Agudelo, A., Lozano, M., Montoya, G., Ospina, A., Lopez, M., Gallo, A., Miranda, A., … Ruiz-Linares, A. (2000). An association study of bipolar mood disorder (type I) with the 5-HTTLPR serotonin transporter polymorphism in a human population isolate from Colombia. Neuroscience Letters, 292(3), 199–202. https://doi.org/10.1016/S0304-3940(00)01464-6
Poldrack, R. A., Congdon, E., Triplett, W., Gorgolewski, K. J., Karlsgodt, K. H., Mumford, J. A., Sabb, F. W., Freimer, N. B., London, E. D., Cannon, T. D., & Bilder, R. M. (2016). A phenome-wide examination of neural and cognitive function. Scientific Data, 3(1), 1–12. https://doi.org/10.1038/sdata.2016.110
Vélez, J. I. (2021). Machine Learning based Psychology: Advocating for A Data-Driven Approach. International Journal of Psychological Research, 14(1), 6–11. https://doi.org/10.21500/20112084.5365
Wagner, G. P., Kenney-Hunt, J. P., Pavlicev, M., Peck, J. R., Waxman, D., & Cheverud, J. M. (2008). Pleiotropic scaling of gene effects and the “cost of complexity.” Nature, 452(7186), 470–472. https://doi.org/10.1038/nature06756
Wendt, F. R., Pathak, G. A., Lencz, T., Krystal, J. H., Gelernter, J., & Polimanti, R. (2020). Multivariate genome-wide analysis of education, socioeconomic status and brain phenome. Nature Human Behaviour, 5(4), 482–496. https://doi.org/10.1038/s41562-020-00980-y
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