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Jaramillo-Garzón, Jorge Alberto
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1

Support Vector Machines for Biomarkers Detection in in vitr..:

Lopera-Rodríguez, Jorge Alejandro ; Zuluaga, Martha ; Jaramillo-Garzón, Jorge Alberto
TecnoLógicas.  24 (2021)  52 - p. e2088 , 2021
Link: https://doi.org/10.22430..
 
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2

Performance comparison of particle swarm optimization and C..:

Goez-Sanchez, German David ; Jaramillo-Garzon, Jorge Alberto ; Velasquez, Ricardo Andres
IEEE Aerospace and Electronic Systems Magazine.  33 (2018)  10 - p. 40-50 , 2018
Link: https://doi.org/10.1109/..
 
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3

Predictability of gene ontology slim-terms from primary str..:

Jaramillo-Garzón, Jorge Alberto ; Gallardo-Chacón, Joan Josep ; Castellanos-Domínguez, César Germán.
BMC Bioinformatics.  14 (2013)  1 - p. , 2013
Link: https://doi.org/10.1186/..
 
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4

Support Vector Machines for Biomarkers Detection in in vitr..:

Lopera-Rodríguez, Jorge Alejandro ; Zuluaga, Martha ; Jaramillo-Garzón, Jorge Alberto
https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2088/2212.  , 2021
Link: https://revistas.itm.edu..
 
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5

Applicability of semi-supervised learning assumptions for g..:

Jaramillo-Garzón, Jorge Alberto ; Castellanos, Cesar German ; Perera Lluna, Alexandre , 2016
Link: http://hdl.handle.net/21..
 
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6

Applicability of semi-supervised learning assumptions for g..:

Jaramillo-Garzón, Jorge Alberto ; Castellanos-Domínguez, César Germán ; Perera-Lluna, Alexandre
https://revistas.udea.edu.co/index.php/ingenieria/article/view/22934/20780406.  , 2016
Link: https://revistas.udea.ed..
 
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7

Applicability of semi-supervised learning assumptions for g..:

Jaramillo-Garzón, Jorge Alberto ; Castellanos, Cesar German ; Perera Lluna, Alexandre
Jaramillo-Garzón, J., Castellanos, C., Perera, A. Applicability of semi-supervised learning assumptions for gene ontology terms prediction. "Revista Facultad de Ingeniería. Universidad de Antioquía", 1 Juny 2016, núm. 79, p. 19-32..  , 2016
Link: http://hdl.handle.net/21..
 
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8

Predictability of gene ontology slim-terms from primary str..:

Jaramillo-Garzón, Jorge Alberto ; Gallardo Chacón, Joan Josep ; Castellanos Domínguez, Germán.
http://www.biomedcentral.com/1471-2105/14/68/abstract.  , 2013
Link: http://hdl.handle.net/21..
 
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9

Predictability of gene ontology slim-terms from primary str..:

Jaramillo-Garzón, Jorge Alberto ; Gallardo Chacón, Joan Josep ; Castellanos Domínguez, Germán.
http://www.biomedcentral.com/1471-2105/14/68/abstract.  , 2013
Link: http://hdl.handle.net/21..
 
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10

Manipulability index study on the KUKA robot KR5 ARC HW:

, In: 2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA),
Ramirez Henao, Juan Camilo ; Jaramillo Garzon, Jorge Alberto ; Duque Mumoz, Leonardo - p. 72-77 , 2012
Link: https://doi.org/10.1109/..
 
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11

Protein function prediction with semi-supervised classifica..:

Jaramillo Garzón, Jorge Alberto
Universidad Nacional de Colombia Sede Manizales Facultad de Ingeniería y Arquitectura Departamento de Ingeniería Eléctrica, Electrónica y Computación.  , 2013
Link: https://repositorio.unal..
 
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12

Dissimilarity-based classification for stochastic models of..:

Godino, Juan Ignacio ; Jaramillo Garzón, Jorge Alberto ; Castellano Domínguez, Germán
Rev. Fac. Ing. Univ. Antioquia.  , 2009
Link: http://hdl.handle.net/10..
 
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13

Metodología de optimización de los parámetros de control de..:

Jaramillo Garzón, Jorge Alberto
Universidad Nacional de Colombia Sede Manizales Facultad de Ingeniería y Arquitectura Departamento de Ingeniería Eléctrica, Electrónica y Computación.  , 2007
Link: https://repositorio.unal..
 
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14

Support Vector Machines for Biomarkers Detection in in vitr..:

Jorge Alejandro Lopera-Rodríguez ; Martha Zuluaga ; Jorge Alberto Jaramillo-Garzón
https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2088.  , 2021
Link: https://doi.org/10.22430..
 
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15

Applicability of semi-supervised learning assumptions for g..:

Jorge Alberto Jaramillo-Garzón ; César Germán Castellanos-Domínguez ; Alexandre Perera-Lluna
https://revistas.udea.edu.co/index.php/ingenieria/article/view/22934.  , 2016
Link: https://doi.org/10.17533..
 
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