Full list of publications

Journal publications

• Cruces-Salguero, S., Larrañaga, I., Garcia-Galindo, A., Armañanzas, R., Mar, J., Matheu, A. (2024) Analysis of response of centenarians of the Basque Country to COVID-19. Journal of the American Geriatrics Society, 72(6),1926-1929. DOI 10.1111/jgs.18853
• Armañanzas, R., Liang, B., Kanakia, S., Bazarian, J.J., Prichep, L.S. (2024) Identification of Concussion Subtypes Based on Intrinsic Brain Activity. JAMA Network Open, 7(2):e2355910, 1-12. DOI 10.1001/jamanetworkopen.2023.55910
• Liang, B., Alosco, M.L., Armañanzas, R., Martin, B.M., Tripodis, Y., Stern, R.A., Prichep, L.S. (2023) Long-term Changes in Brain Connectivity Reflected in Quantitative Electrophysiology of Symptomatic Former NFL Players. Journal of Neurotrauma, 40, 309-317. DOI 10.1089/neu.2022.0029
• DeFelipe, J., Felipe-Oroquieta, J., Furcila, D., Muñoz-Alegre, M., Maestu, F., Sola, R.G., Blazquez-Llorca, L., Armañanzas, R., Kastanauskaite, A., Alonso-Nanclares, L., Rockland1, K.S., Arellano, J.I. (2022) Neuroanatomical and psychological considerations in temporal lobe epilepsy. Frontiers in Neuroanatomy, 16, 1-39. DOI 10.3389/fnana.2022.995286
• Yuste, R., Hawrylycz, M., Aalling, N., Aguilar-Valles, A., Arendt, D., Armañanzas, R., et al. (2020) A community-based transcriptomics classification and nomenclature of neocortical cell types. Nature Neuroscience, 23, 1456-1468. DOI 10.1038/s41593-020-0685-8.
• Maraver, P., Armañanzas, R., Gillette, T.A. & Ascoli, G.A. (2019) PaperBot: open-source web-based search and metadata organization of scientific literature. BMC Bioinformatics, 20(50), 1-13. DOI 10.1186/s12859-019-2613-z
• Armañanzas, R. (2018) Revealing post-transcriptional microRNA-mRNA regulations in Alzheimer's disease through ensemble graphs. BMC Genomics, 19(Suppl 19):668, 15-25. DOI 10.1186/s12864-018-5025-y
• Akram, M., Nanda, S., Maraver, P., Armañanzas, R. & Ascoli, G.A. (2018) An open repository for single-cell reconstructions of the brain forest. Scientific Data, 5(180006). DOI 10.1038/sdata.2018.6
• Ascoli, G.A., Maraver, P., Nanda, S., Polavaram, S. & Armañanzas, R. (2017) Win-win data sharing in neuroscience. Nature Methods, 14(2), 112-116. DOI 10.1038/nmeth.4152
• Armañanzas, R., Iglesias, M., Morales D.A. & Alonso-Nanclares, L. (2017). Voxel-based diagnosis of Alzheimer's disease using classifier ensembles. IEEE Journal of Biomedical and Health Informatics, 21(3), 778-784. DOI 10.1109/JBHI.2016.2538559. Supplementary content & Original fMRI data.
• Ibáñez, A., Armañanzas, R., Bielza, C. & Larrañaga, P. (2016). Genetic algorithms and Gaussian Bayesian networks to uncover the predictive core set of bibliometric indices. Journal of the Association for Information Science and Technology, 67(7), 1703-1721. DOI 10.1002/asi.23467
• Armañanzas, R. & Ascoli, G.A. (2015). Towards the Automatic Classification of Neurons. Trends in Neurosciences, 38(5), 307-318. DOI 10.1016/j.tins.2015.02.004. Supplementary content
• Parekh, R., Armañanzas, R. & Ascoli, G.A. (2015). The importance of metadata to assess information content in digital reconstructions of neuronal morphology. Cell & Tissue Research. 360(1), 121-127. DOI 10.1007/s00441-014-2103-6
• Nanda, S., Allaham, M., Bergamino, M., Polavaram, S., Armañanzas, R., Ascoli, G.A. & Parekh, R. (2015). Doubling up on the fly: NeuroMorpho.Org meets Big Data. Neuroinformatics, 13(1), 127-129. DOI 10.1007/s12021-014-9257-y
• Masegosa, A.R., Armañanzas, R., Abad-Grau, M.M., Potenciano, V., Moral, S., Larrañaga, P., Bielza, C. & Matesanz, F. (2015). Learning classifiers from discretized expression quantitative trait loci. Current Bioinformatics, 10(2), 144-164. DOI 10.2174/157489361002150518123918
• Armañanzas, R., Alonso-Nanclares, L., DeFelipe-Oroquieta, J., Kastanauskaite, A., de Sola, R.G., DeFelipe, J., Bielza, C. & Larrañaga, P. (2013). Machine learning approach for the outcome prediction of temporal lobe epilepsy surgery. PLoS ONE, 8(4), e62819. DOI 10.1371/journal.pone.0062819
• Armañanzas, R., Bielza, C., Chaudhuri, K. R., Martínez-Martín, P. & Larrañaga, P. (2013). Unveiling relevant non-motor Parkinson's disease severity symptoms using a machine learning approach. Artificial Intelligence in Medicine, 58(3), 195-202. DOI 10.1016/j.artmed.2013.04.002
• Santana, R., Armañanzas, R., Bielza, C. & Larrañaga, P. (2013). Network measures for information extraction in evolutionary algorithms. International Journal of Computational Intelligence Systems, 6(6), 1163-1188. DOI 10.1080/18756891.2013.823004
• García-Torres, M., Armañanzas, R., Bielza, C. & Larrañaga, P. (2013). Comparison of metaheuristic strategies for peakbin selection in proteomic mass spectrometry data. Information Sciences, 222, 229-246. DOI 10.1016/j.ins.2010.12.013
• García-Bilbao, A., Armañanzas, R., Ispizua, Z., Calvo, B., Alonso-Varona, A., Inza, I., Larrañaga, P., López Vivanco, G., Suárez-Merino, B. & Betanzos, M. (2012). Identification of a biomarker panel for colorectal cancer diagnosis. BMC Cancer, 12(43). DOI 10.1186/1471-2407-12-43
• Armañanzas, R., Larrañaga, P. & Bielza, C. (2012). Ensemble transcript interaction networks: A case study on Alzheimer's disease. Computer Methods and Programs in Biomedicine, 108(1), 442-450. DOI 10.1016/j.cmpb.2011.11.011
• Armañanzas, R., Saeys, Y., Inza, I., García-Torres, M., Bielza, C., van de Peer, Y. & Larrañaga, P. (2011). Peakbin selection in mass spectrometry data using a consensus approach with estimation of distribution algorithms. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 8(3), 760-774. DOI 10.1109/TCBB.2010.18. Supplementary content
• Santana, R., Bielza, C., Larrañaga, P., Lozano, J.A., Echegoyen, C., Mendiburu, A., Armañanzas, R. & Shakya, S. (2010). MATEDA: A Matlab Package for the Implementation and Analysis of Estimation of Distribution Algorithms. Journal of Statistical Software, 35(7), 1-30. DOI 10.18637/jss.v035.i07
• Otaegui, D., Baranzini, S., Armañanzas, R., Calvo, B., Muñoz-Culla, M., Khankhanian, P., Inza, I., Lozano, J.A., Castillo-Triviño, T., Asensio, A., Olsacoaga, J. & López de Munain, A. (2009). Differential micro RNA expression in PBMC from multiple sclerosis patients. PLoS ONE, 4(7), e6309. DOI 10.1371/journal.pone.0006309
• Armañanzas, R., Calvo, B., Inza, I., López-Hoyos, M., Martínez-Taboada, V., Ucar, E., Bernales, I., Fullaondo, A., Larrañaga, P., Zubiaga, A.M. (2009). Microarray analysis of autoimmune diseases by machine learning procedures. IEEE Transactions on Information Technology in Biomedicine, 13(3), 341-350. DOI 10.1109/TITB.2008.2011984
• Sáenz, A., Azpitarte, M., Armañanzas, R., Leturcq, F., Alzualde, A., Inza, I., García-Bragado, F., De la Herran, G., Corcuera, J., Cabello, A., Navarro, C., De la Torre, C., Gallardo, E., Illa, I. & López de Munain, A. (2008). Gene expression profiling in limb-girdle muscular dystrophy 2A. PLoS ONE, 3(11), e3750. DOI 10.1371/journal.pone.0003750
• Armañanzas, R., Inza, I., Santana, R., Saeys, Y., Flores, J.L., Lozano, J.A., Van de Peer, Y., Blanco, R., Robles, V., Bielza, C. & Larrañaga, P. (2008). A review of estimation of distribution algorithms in bioinformatics. BioData Mining, 1(6). DOI 10.1186/1756-0381-1-6
• Armañanzas, R., Inza, I. & Larrañaga, P. (2008). Detecting reliable gene interactions by a hierarchy of Bayesian networks classifiers. Computer Methods and Programs in Biomedicine, 91, 110-121. DOI 10.1016/j.cmpb.2008.02.010
• Zipritia, I., Elorriaga, J., Arruarte, A., Larrañaga, P. & Armañanzas, R. (2008). What is behind a summary evaluation decision?. Behavior Research Methods, 2(40), 597-612. DOI 10.3758/BRM.40.2.597
• Larrañaga, P., Calvo, B., Santana, R., Bielza, C., Galdiano, J., Inza, I., Lozano, J.A., Armañanzas, R., Santafé, G., Pérez, A. & Robles, V. (2006). Machine Learning in Bioinformatics. Briefings in Bioinformatics, 17(1), 86-112. DOI 10.1093/bib/bbk007

Books

• Armañanzas, R. (2012). Consensus Policies to Solve Bioinformatic Problems. LAP LAMBERT Academic Publishing. ISBN 978-3843353120

Book chapters

• Calvo, B., Armañanzas, R., Inza, I. & Lozano, J.A. (2011). From Bayesian to module networks: experiences modeling gene relationships with expression data. In Loza M., López V., Martín F. & Pazos A. (editors), Advances in Biomedical Informatics: COMBIOMED. Universidade da Coruña. ISBN 978-8497494779
• Inza, I., Calvo, B., Armañanzas, R., Bengoetxea, E., Larrañaga, P. & Lozano, J.A. (2009). Machine learning: An indispensable tool in bioinformatics. In Matthiesen, R. (editor), Bioinformatics Methods in Clinical Research. Springer. ISBN 978-1-60327-194-3
• Inza, I., Armañanzas, R. & Santafé, G (2006). Una aproximación al software WEKA. In B. Sierra (editor), Aprendizaje Automático: conceptos básicos y avanzados. Pearson Educación. ISBN 84-8322-318-X
• Armañanzas, R., Calvo, B., Inza, I., Larrañaga, P., Bernales, I., Fullaondo, A. et al (2005). Clasificadores Bayesianos con selección consensuada de genes en la predicción del lupus eritematoso sistémico. In J.A. Gámez & I. García Varela & J. Hernández Orallo (editors), Minería de Datos: Técnicas y Aplicaciones. Ediciones Dpt. de Informática de la UCLM. ISBN 84-921873-7-9

Conference contributions

• Abbas-Aghababazadeh, F., Alonso, L., López-de-Castro, M., Guinot, F., Desponds, J., Furger, S., Karapetyan, A., Ott, S.I., Bergmann, E., Jones, N., Vasudevan, G., Sankarlingam, V., Chithambaram, S., Gautschi, P., Chandler, G.S., Mohindra, R., Garonce-Hediger, R., Fontes, M., Karanikas, V., Crespo, M., MacPherson, C., Haibe-Kains, B., Hernaez, M., Armañanzas, R., Szabados, B. (2024). Harnessing the cancer immunity cycle via machine learning models to generate novel strategies for personalized cancer therapy. In Journal for ImmunoTherapy of Cancer, 12(Suppl 2), A1334-AA1337. Houston, USA. DOI 10.1136/jitc-2024-SITC2024.1197
• López-De-Castro, M., García-Galindo, A., Armañanzas, R. (2024). Conformal Stability Measure of Feature Selection Algorithms. In Proceedings of the Thirteenth Symposium on Conformal and Probabilistic Prediction with Applications, PMLR 230, pages 105-119. Milan, Italy.
• García-Galindo, A., López-De-Castro, M., Armañanzas, R. (2024). Multi-class Classification with Reject Option and Performance Guarantees using Conformal Prediction. In Proceedings of the Thirteenth Symposium on Conformal and Probabilistic Prediction with Applications, PMLR 230, pages 295-314. Milan, Italy.
• Liang, B., Prichep, L.S., Kanakia, S., Bazarian, J.J., Covassin, T., Elbin, R.J., Hotz, G.A., Struder, J.F., Armañanzas, R. (2023). Electronic Near Point of Convergence: A Tool to Aid the Assessment of Concussion. In IEEE International Conference on Bioinformatics and Biomedicine, pages 4086-4092. Istanbul, Turkey.
• González-Montesino, L., Grass-Boada, D.H., Armañanzas, R. (2023). Network Community Detection in Connectomics Data using Graph Theory. In IEEE International Conference on Bioinformatics and Biomedicine, pages 3459-3465. Istanbul, Turkey.
• Garcia-Galindo, A., Lopez-De-Castro, M., Armañanzas, R. (2023). An Uncertainty-Aware Sequential Approach for Predicting Response to Neoadjuvant Therapy in Breast Cancer. In Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, PMLR 204, pages 74-88. Limassol, Cyprus.
• Martínez-García, M., García-Gutierrez, S., Armañanzas, R., Díaz, A., Inza, I., Lozano, J.A. (2022). Learning a battery of COVID-19 mortality prediction models by multi-objective optimization. In Proceedings of the 20th International Conference on Artificial Intelligence in Medicine, pages 332-342. Halifax, Canada.
• Armañanzas, R., Díaz, A., Martínez-García, M., Mazuelas, S. (2021). Derivation of a Cost-Sensitive COVID-19 Mortality Risk Indicator Using a Multistart Framework. In IEEE International Conference on Bioinformatics and Biomedicine, pages 2179-2186. Online. DOI 10.1109/BIBM52615.2021.9669288
• Armañanzas, R., Ascoli, G.A. (2018). Cross-lab validation of the neocortical microcircuit's interneuron morphological types. In Fall Brain Conference 2018: The Necessity of Cell Types for Brain Function, pages 11-12. Copenhagen, Denmark.
• Armañanzas, R. (2017). Ensemble Graphs to Reveal Post-Transcriptional Regulatory Networks in Alzheimer's Disease. In IEEE International Conference on Bioinformatics and Biomedicine, pages 297-304. Kansas City, USA. DOI 10.1109/BIBM.2017.8217667
• Nanda, S., Armañanzas, R., Maraver, P., Akram, M.A., Ascoli, G.A. (2017). Multiplicative impact of digitally reconstructed neural arbors by online sharing. In 2017 Annual Meeting of the Society for Neuroscience, 813.16/WW33. Washington D.C., USA.
• Maraver, P., Nanda, S., Armañanzas, R., Akram, M.A., Ascoli, G.A. (2017). LiterMate: open source web based selection, annotation, and metadata organization of peer reviewed publications identified by full text mining. In 2017 Annual Meeting of the Society for Neuroscience, 814.10/WW47. Washington D.C., USA.
• Armañanzas, R., Nanda, S., Ascoli, G.A. (2016). Circuitry Profiling in the Drosophila Brain through Machine Learning. In 2016 Annual Meeting of the Society for Neuroscience, 96.04/LLL4. San Diego, USA.
• Armañanzas, R., Polavaram, S., Nanda, S., Marver, P., Ascoli, G.A. (2016). A Decade of NeuroMorpho.Org: Lessons Learned and Future Prospects. In 2016 Annual Meeting of the Society for Neuroscience, 25.08SU/NNN34. San Diego, USA.
• Armañanzas, R., Parekh, R., Polavaram, S., Nanda, S., Ascoli, G.A. (2015). NeuroMorpho.Org: connecting neuronal morphology with digital neuroscience. In 2015 Annual Meeting of the Society for Neuroscience, 735.11/DD42. Chicago, USA.
• Armañanzas, R., Parekh, R., Polavaram, S., Nanda, S., Ascoli, G.A. (2014). Neuron identity in the digital era: Knowledge flow optimization and automatic classification. In 2014 Annual Meeting of the Society for Neuroscience, 187.04/TT53. Washington D.C., USA.
• Nanda, S., Armañanzas, R., Parekh, R., Polavaram, S., Cox, D.N., Ascoli, G.A. (2014). Comparing stochastic growth models to explore the developmental mechanisms of dendritic arbors. In 2014 Annual Meeting of the Society for Neuroscience, 31.18/A64. Washington D.C., USA.
• Parekh, R., Armañanzas, R., Polavaram, S., Nanda, S., Ascoli, G.A. (2014). The inner workings of NeuroMorpho.Org. In 2014 Annual Meeting of the Society for Neuroscience, 185.01/SS60. Washington D.C., USA.
• Polavaram, S., Parekh, R., Armañanzas, R., Nanda, S., Ascoli, G.A. (2014). OntoSearch - Using formal ontologies to enable concept-based searches in NeuroMorpho.Org. In 2014 Annual Meeting of the Society for Neuroscience, 187.03/TT52. Washington D.C., USA.
• García-Bilbao, A., Armañanzas, R., Ispizua, Z., Calvo, B., Alonso-Varona, A., Inza, I., Larrañaga, P., López Vivanco, G., Suárez-Merino, B. & Betanzos, M (2012). Identification of a biomarker panel for colorectal cancer diagnosis. In Proceedings of the 6th International Meeting on Biotechnology, pages 77. Bilbao, Spain.
• Armañanzas, R., Martínez-Martín, P., Bielza, C. & Larrañaga, P. (2012). Restating clinical impression of severity index for Parkinson's disease using just non-motor criteria. In Proceedings of the 25th European Conference on Operational Research, pages 231-232. Vilnius, Lithuania.
• Calvo, B. & Armañanzas, R (2010). Module Network-Based Classifiers for Redundant Domains. In Proceedings of the Fourth International Workshop on Machine Learning in Systems Biology, pages 115-118. Edinburgh, Scotland.
• Muñoz-Culla, M., Irizar, H., Calvo, B., Armañanzas, R., Olaskoaga, J., Castillo-Triviño, T., López de Munain, A., Baranzini, S. & Otaegui D. (2010). miRNA: Biomarkers in MS?. In Proceedings of the 26th Congress of the European Committee for Treatment and Research in Multiple Sclerosis, pages 558. Gothenburg, Sweden.
• Armañanzas, R., Saeys, Y., Inza, I., García-Torres, M., Van de Peer, Y., Bielza, C. & Larrañaga, P. (2008). Mass spectrometry data analysis: it's all in the preprocessing. In Proceedings of the Benelux Bioinformatics Conference, pages 92. Maastricht, The Netherlands.
• Armañanzas, R., Calvo, B., Inza, I., Larrañaga, P., Bernales, I., Fullaondo, A., Zubiaga, A.M. (2007). Bayesian Classifiers with Consensus Gene Selection: a case study in the Systemic Lupus Erythematosus. In Progress in Industrial Mathematics at ECMI 2006, pages 560-565. Springer. DOI 10.1007/978-3-540-71992-2_91
• García, A., Freije, A., Armañanzas, R., Inza, I., Ispizua, Z., Heredia, P., Larrañaga, P., López Vivanco, G., Suárez, T. & Betanzos, M. (2007). Gene expression model for the classification of human colorectal cancer and potential CRC biomarkers search. In Drug Discovery Technology. London, UK.
• García, A., Freije, A., Armañanzas, R., Inza, I., Ispizua, Z., Heredia, P., Larrañaga, P., López Vivanco, G., Suárez, T. & Betanzos, M. (2006). Simultaneous Search of Genomic and Proteomic Biomarkers in Human Colorectal Cancer. In Genomes to Systems Conference. Manchester, UK.
• Armañanzas, R. & Lozano, J.A. (2005). A Multiobjective Approach to the Portfolio Optimization Problem. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation, pages 1388-1395. Edinburgh, Scotland. DOI 10.1109/CEC.2005.1554852. Supplementary content.
• Armañanzas, R., Inza, I. & Larrañaga, P. (2005). Consensus Gene Selection on DNA Microarrays. In European Conference on Computational Biology. Madrid, Spain.
• Armañanzas, R., Calvo, B., Inza, I., Larrañaga, P., Bernales, I., Fullaondo, A. & Zubiaga, A.M. (2005). Selección de genes asociados a dos enfermedades autoinmunes a partir de microarrays de ADN. In VI Jornadas de Transferencia Tecnológica de Inteligencia Artificial, TTIA (AEPIA), pages 63-70. Granada, Spain.

Technical reports & Preprints

• Grass-Boada, D.H., González-Montesino, L. & Armañanzas, R. (2024). A Novel Algorithm for Community Detection in Networks using Rough Sets and Consensus Clustering. arXiv:2406.12412, 1-39.
• López-De-Castro, M., García-Galindo, A. & Armañanzas, R. (2024). Conformal Recursive Feature Elimination. arXiv:2405.19429, 1-35.
• Martínez-García, M., García-Gutierrez, S., Barreñada Taleb, L., Armañanzas, R., Inza, I. & Lozano, J.A. (2023). Clinical severity prediction of COVID-19 admitted patients in Spain: SEMI and REDISSEC cohorts. medRxiv, DOI 10.1101/2023.02.08.23285589.
• Armañanzas, R., Bielza, C., Larrañaga, P. & Martínez-Martín, P. (2011). Restating Parkinson's disease severity indices by means of non-motor criteria. Technical Report, UPM-FI/DIA/2011-2.
• Santana, R., Echegoyen, C., Mendiburu, A., Bielza, C., Lozano, J.A., Larrañaga, P., Armañanzas R. & Shakya, S.K. (2009). MATEDA: A suite of EDA programs in Matlab, Servicio de Publicaciones de la Facultad de Informática, UPV/EHU. EHU-KZAA-IK-2/09.
• Armañanzas, R. (2006). Solving bioinformatics problems by means of Bayesian classifiers and feature selection, Technical Report EHU-KZAA-IK-2/06. University of the Basque Country.

Patents

• Otaegui, D., López de Munain, A., Olascoaga, J., Calvo, B., Armañanzas, R., Inza, I. & Lozano, J.A. (2011). Methods for the diagnosis of Multiple Sclerosis based on its microRNA expression profiling. Patent No. 003989. World International Property Organization. USPTO Application no. US 2012-0164653 A1.
• García, A., Suárez, B., Betanzos, M., López Vivanco, G. M., Armañanzas, R., Inza, I. & Larrañaga, P. (2010). Methods and kits for the diagnosis and the staging of colorectal cancer. Patent No. 034794A2. World International Property Organization. USPTO Application no. US 2011-0319282 A1.

Thesis

• Armañanzas, R. (2009). Consensus Policies to Solve Bioinformatic Problems Through Bayesian Network Classifiers and Estimation of Distribution Algorithms. Phd Thesis, Departamento de Ciencias de la Computación e Inteligencia Artificial. Universidad del País Vasco. Awarded with an extraordinary doctorate award 2008-2009 in technical education field. Defense dissertation.

Editorial experience

• Frontiers in Computational Neuroscience
• Journal of Integrated OMICS - a methodological journal

Reviewer profile

• Reviewer for: International Journal of Functional Informatics and Personalised Medicine, Journal of Biomedical Informatics, IEEE Transactions on Biomedical Engineering, Quantitative Finance, Journal of Bioinformatics and Computational Biology, Machine Learning, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Artificial Intelligence in Medicine, Data Mining and Knowledge Discovery, Revista Iberoamericana de Inteligencia Artificial, Neuroinformatics, Neural Computing and Applications, Frontiers in Computational Neuroscience, PLOS ONE, Bioinformatics, BMC Bioinformatics, IEEE Transactions on Knowledge and Data Engineering, Nature Scientific Reports, Nature.
• PC member of: BIRD 2008, ITBAM 2010-11, ICANNGA 2011-2013, IJCAI 2011, CEC 2012-2013-2014, SSCI 2013, IWBBIO 2013-2014, CAEPIA 2013, ECML PKDD 2015.