Dr. Patricio Yankilevich

BS in Computer Sciences – University of Buenos Aires (UBA) (2002). Master in Bioinformatics and Neuroinformatics, University of Edinburgh (2003). Ph.D. in Molecular Biology, Universidad Autónoma de Madrid, Spain (2011).

He started working in bioinformatics in the UK, at Organon Laboratories (now Merck), then he moved to Madrid as staff scientist at the Spanish National Cancer Research Center – CNIO (2003-2005) and for Integromics S.L., a spin off of the National Center for Biotechnology – CNB (2009-2011). In Argentina he worked for Biosidus S.A. and at the Institute of Agrobiotechnology of Rosario – INDEAR (2005-2009).

Selected publications

  • Malena Manzi, Martín Palazzo, María Elena Knott, Pierre Beauseroy, Patricio Yankilevich, María Isabel Giménez, and María Eugenia Monge.
    Coupled Mass-Spectrometry-Based Lipidomics Machine Learning Approach for Early Detection of Clear Cell Renal Cell Carcinoma.
    Journal of Proteome Research Article. 20:841-857 (2021).
  • María Sol Ruiz, María Belén Sánchez, Simone Bonecker, Carolina Furtado, Daniel Isaac Koile, Patricio Yankilevich, Santiago Cranco, María del Rosario Custidiano, Josefina Freitas, Beatriz Moiraghi, Mariel Ana Pérez, Carolina Pavlovsky, Ana Inés Varela, Verónica Ventriglia, Julio César Sánchez Ávalos, Irene Larripa, Ilana Zalcberg, José Mordoh, Peter Valent, Michele Bianchini.
    miRNome profiling of LSC-enriched CD34+CD38-CD26+ fraction in Ph+ CML-CP from Argentinean patients: a potential new pharmacogenomic tool.
    Frontiers in Pharmacology 11: 2231 (2020).
  • Martín Palazzo, Pierre Beauseroy and Patricio Yankilevich.
    Unsupervised feature selection for tumor profiles using autoencoders and kernel methods.
    2020 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), Viña del Mar, 2020, pp. 1-8.
  • Podaza E, Carri I, Aris M, von Euw E, Bravo AI, Blanco P, Ortiz Wilczyñski JM, Koile D, Yankilevich P, Nielsen M, Mordoh J, Barrio MM.
    Evaluation of T-Cell Responses Against Shared Melanoma Associated Antigens and Predicted Neoantigens in Cutaneous Melanoma Patients Treated With the CSF-470 Allogeneic Cell Vaccine Plus BCG and GM-CSF.
    Front Immunol. 11:1147 (2020)
  • Vogl AM, Phu L, Becerra R, Giusti SA, Verschueren E, Hinkle TB, Bordenave MD, Adrian M, Heidersbach A, Yankilevich P, Stefani FD, Wurst W, Hoogenraad CC, Kirkpatrick DS, Refojo, D., Sheng, M.
    Global site-specific neddylation profiling reveals that NEDDylated cofilin regulates actin dynamics.
    Nature Structural and Molecular Biology 27:210-20 (2020).
  • Palazzo M, Beauseroy P, Yankilevich P.
    A Pan-cancer Somatic Mutation Embedding using Autoencoders.
    BMC Bioinformatics 20:655 (2019).
  • Pazos Obregón F, Palazzo M, Soto P, Guerberoff G, Yankilevich P, Cantera R.
    An improved catalogue of putative synaptic genes defined exclusively by temporal transcription profiles through an ensemble machine learning approach.
    BMC Genomics 20:1011 (2019).
  • Tedesco L, Elguero B, Pacin DG, Senin S, Pollak C, Garcia Marchiñena PA, Jurado AM, Isola M, Labanca MJ, Palazzo M, Yankilevich P, Fuertes M, Arzt E.
    Von Hippel-Lindau mutants in renal cell carcinoma are regulated by increased expression of RSUME.
    Cell death & disease 10: 266 (2019).
  • Koile, D; Cordoba, M; de Sousa Serro, M; Kauffman, M; Yankilevich, P.
    GenIO: a phenotype-genotype analysis web server for clinical genomics of rare diseases.
    BMC Bioinformatics 19:25 (2018)
  • Parra, R.G.; Rohr, C.O.; Koile, D.; Perez-Castro, C.; Yankilevich, P.
    INSECT 2.0: a web-server for genome-wide cis-regulatory modules prediction.
    Bioinformatics 32:1229-31 (2016)
  • Díaz Flaqué, C.M., Galigniana, M. N., Béguelin, W., Vicario, R., Proietti, J.C., Cordo Russo, R., Rivas, A.M., Tkach, M., Guzmán, P., Roa, C. J., Maronna, E., Pineda, V., Muñoz S., Mercogliano, F.M., Charreau, H.E., Yankilevich, P., Schillaci, R., Elizalde V.P.
    Progesterone receptor assembly of a transcriptional complex along with activator protein 1, signal transducer and activator of transcription 3 and ErbB-2 governs breast cancer growth and predicts response to endocrine therapy.
    Breast Cancer Research 15:R118 (2013)
  • Andreu Alibés; Patricio Yankilevich; Andrés Cañada; Ramón Díaz-Uriarte.
    IDconverter and IDClight: Conversion and annotation of gene and protein IDs.
    BMC Bioinformatics 8:9 (2007)
  • Ribas G, Gonzalez-Neira A, Salas A, Milne RL, Vega A, Carracedo B, Gonzalez E, Barroso E, Fernandez LP, Yankilevich P, Robledo M, Carracedo A, Benitez J.
    Evaluating HapMap SNP data transferability in a large-scale genotyping project involving 175 cancer associated genes.
    Human Genetics 118:669-679 (2006)
  • Vaquerizas JM, Conde L, Yankilevich P, Cabezon A, Minguez P, Diaz-Uriarte R, Al-Shahrour F, Herrero J, Dopazo J.
    GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data.
    Nucleic Acids Res Vol. 33, Web Server issue (2005)