Dr. Patricio Yankilevich

Licenciado en Ciencias de la Computación en la Universidad de Buenos Aires (2002). Master en Bioinformática y Neuroinformática en la Universidad de Edimburgo (2003). Doctorado en Biología Molecular en la Universidad Autónoma de Madrid (2011).

Comenzó a trabajar como bioinformático profesional en Reino Unido para Organon Laboratories (hoy Merck). Trabajó en España como investigador en el Centro Nacional de Investigaciones Oncológicas – CNIO (2003-2005) y para Integromics S.L., un spin off del Centro Nacional de Biotecnología – CNB (2009-2011). En Argentina se desempeñó como investigador en Biosidus S.A. y en el Instituto de Agrobiotecnología Rosario–INDEAR (2005-2009).

Publicaciones destacadas

  • 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 (2020)
  • 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)