@conference {664,
	title = {Hybrid mathematical modeling decodes the complexity of sphingolipid pathway to predict chemosensitivity},
	booktitle = {2017 International Conference and Workshop on Bioinspired Intelligence (IWOBI)},
	year = {2017},
	month = {July},
	keywords = {cancer, chemotherapy, Computer architecture, drugs, EDO, fluorescence, Fuzzy logic, GMM, Inhibitors, Mathematical model, Microprocessors, Sphingolipids},
	doi = {10.1109/IWOBI.2017.7985532},
	author = {Molina-Mora, J.A. and Kop-Montero, M. and Crespo-Marino, J.L. and Quiros, S. and Mora-Rodriguez, R.A.}
}
@conference {659,
	title = {A biocomputational application for the automated construction of large-scale metabolic models from transcriptomic data},
	booktitle = {2016 IEEE 36th Central American and Panama Convention (CONCAPAN XXXVI)},
	year = {2016},
	month = {Nov},
	keywords = {aldehyde dehydrogenase, automated construction, biochemistry, biocomputational application, biocomputing, Biological system modeling, biology approach, biology computing, Breast cancer, breast cancer cell lines, breast cancer stem cells, cancer, cancer behavior, cancer chemoresistance, cancer evolution, cancer-specific alterations, cell death, chemotherapy response, Computational modeling, Data models, FBA, Flux balance analysis, gene expression data, general metabolic model, glutathione peroxidase, glycolysis, large-scale metabolic models, Mathematical model, medical diagnostic computing, metabolic models, personalized cancer targets, therapy resistance, transcriptomic data, Tumors},
	doi = {10.1109/CONCAPAN.2016.7942349},
	author = {B. V. Edwin and S. C. Francisco and M. R. RA}
}
@conference {657,
	title = {A biocomputational platform for the automated construction of large-scale mathematical models of miRNA-transcription factor networks for studies on gene dosage compensation},
	booktitle = {2016 IEEE 36th Central American and Panama Convention (CONCAPAN XXXVI)},
	year = {2016},
	month = {Nov},
	keywords = {biocomputational platform, cancer, cancer cell, cancer complexity, cancer resistance, cell-to-cell heterogeneity, chromosomal alteration, Correlation, DNA, gene dosage compensation, gene expression, genetic material, genetics, large-scale mathematical model, Mathematical model, microRNA, miRNA-transcription factor networks, miRNAs, molecular biophysics, proteins, RNA, systems biology, transcription factors},
	doi = {10.1109/CONCAPAN.2016.7942348},
	author = {A. Man-Sai and S. C. Francisco and R. Mora-Rodriguez}
}
@conference {653,
	title = {Identification of cancer chemosensitivity by ODE and GMM modeling of heterogeneous cellular response to perturbations in fluorescent sphingolipid metabolism},
	booktitle = {2016 IEEE 36th Central American and Panama Convention (CONCAPAN XXXVI)},
	year = {2016},
	month = {Nov},
	keywords = {biochemistry, biomedical optical imaging, biosensors, BxPC3 cell lines, cancer, cancer chemosensitivity, cell classification, cellular biophysics, chemotherapy, Data models, drugs, dynamical mathematical model, EDO, flow cytometry, fluorescence, fluorescent sphingolipid metabolism, Gaussian processes, Gaussian-mixture model, gemcitabine response sensor, glucosyl-ceramide, GMM, GMM modeling, heterogeneous cellular response, image features, Inhibitors, lipid bilayers, Mathematical model, MiaPaca-4, mixture models, ODE modeling, optical sensors, pancreatic cancer, pathway dynamics, physiological models, single cell level, Sphingolipids, sphingomyelin-synthase, tumor, tumours},
	doi = {10.1109/CONCAPAN.2016.7942347},
	author = {J. Molina-Mora and R. Mora-Rodriguez}
}
