Francisco Cubillos
Francisco Cubillos
Academico Departamento de Ingeniería Quimica
Verified email at - Homepage
Cited by
Cited by
High quality de novo sequencing and assembly of the Saccharomyces arboricolus genome
G Liti, ANN Ba, M Blythe, CA Müller, A Bergström, FA Cubillos, ...
BMC genomics 14 (1), 1-14, 2013
Life history shapes trait heredity by accumulation of loss-of-function alleles in yeast
E Zörgö, A Gjuvsland, FA Cubillos, EJ Louis, G Liti, A Blomberg, ...
Molecular biology and evolution 29 (7), 1781-1789, 2012
Dynamic modelling and simulation of semi-autogenous mills
JL Salazar, L Magne, G Acuna, F Cubillos
Minerals Engineering 22 (1), 70-77, 2009
Extensive cis-regulatory variation robust to environmental perturbation in Arabidopsis
FA Cubillos, O Stegle, C Grondin, M Canut, S Tisné, I Gy, O Loudet
The Plant Cell 26 (11), 4298-4310, 2014
Hybrid-neural modeling for particulate solid drying processes
FA Cubillos, PI Alvarez, JC Pinto, EL Lima
Powder Technology 87 (2), 153-160, 1996
Neural networks and support vector machine models applied to energy consumption optimization in semiautogeneous grinding
M Curilem, G Acuña, F Cubillos, E Vyhmeister
Chemical Engineering Transactions 25, 761-766, 2011
Mushroom dehydration in a hybrid-solar dryer
A Reyes, A Mahn, F Cubillos, P Huenulaf
Energy conversion and management 70, 31-39, 2013
Mapping genetic variants underlying differences in the central nitrogen metabolism in fermenter yeasts
M Jara, FA Cubillos, V García, F Salinas, O Aguilera, G Liti, C Martínez
PLoS One 9 (1), e86533, 2014
Self-fertilization is the main sexual reproduction mechanism in native wine yeast populations
FA Cubillos, C Vasquez, S Faugeron, A Ganga, C Martínez
FEMS microbiology ecology 67 (1), 162-170, 2009
Natural variation in non-coding regions underlying phenotypic diversity in budding yeast
F Salinas, CG De Boer, V Abarca, V García, M Cuevas, S Araos, ...
Scientific reports 6 (1), 1-13, 2016
Comparison of methods for training grey-box neural network models
G Acuña, F Cubillos, J Thibault, E Latrille
Computers & Chemical Engineering 23, S561-S564, 1999
Adaptability of the Saccharomyces cerevisiae yeasts to wine fermentation conditions relies on their strong ability to consume nitrogen
C Brice, FA Cubillos, S Dequin, C Camarasa, C Martínez
PloS one 13 (2), e0192383, 2018
Drying of carrots in a fluidized bed. II. Design of a model based on a modular neural network approach
F Cubillos, A Reyes
Drying Technology 21 (7), 1185-1196, 2003
Dynamic simulation and control of direct rotary dryers
JR Pérez-Correa, F Cubillos, E Zavala, C Shene, PI Álvarez
Food Control 9 (4), 195-203, 1998
Adaptive hybrid neural models for process control
FA Cubillos, EL Lima
Computers & chemical engineering 22, S989-S992, 1998
Bioprospecting for brewers: Exploiting natural diversity for naturally diverse beers
FA Cubillos, B Gibson, N Grijalva‐Vallejos, K Krogerus, J Nikulin
Yeast 36 (6), 383-398, 2019
Model predictive control of semiautogenous mills (sag)
JL Salazar, H Valdés-González, E Vyhmesiter, F Cubillos
Minerals Engineering 64, 92-96, 2014
Exploiting budding yeast natural variation for industrial processes
FA Cubillos
Current genetics 62 (4), 745-751, 2016
Identification of nitrogen consumption genetic variants in yeast through QTL mapping and Bulk segregant RNA-seq analyses
FA Cubillos, C Brice, J Molinet, S Tisné, V Abarca, SM Tapia, C Oporto, ...
G3: Genes, Genomes, Genetics 7 (6), 1693-1705, 2017
Rotary dryer control using a grey-box neural model scheme
FA Cubillos, E Vyhmeister, G Acuña, PI Alvarez
Drying Technology 29 (15), 1820-1827, 2011
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