Computational Biology and Systems Biomedicine

Responsable de Grupo: Dr. Marcos J. Araúzo-Bravo, Ph.D.

Biodonostia HRI. Ikerbasque Research Professor. marcos.arauzo@biodonostia.org
Dr. Marcos Araúzo Bravo is an Industrial Engineer in Automation and Electronics, Doctor of Industrial Technologies from the Polytechnic University of Cartagena and Doctor in Information Technology in 2003 from the Kyushu Institute of Technology (KIT) in Japan, where he also completed his postdoctoral studies in 2006. From 2006 to 2014 he launched and headed the Computational Biology and Bioinformatics laboratory at the Max Planck Institute for Molecular Biomedicine in Münster (Germany).
From 1998 to 2004 he was Associate Professor of the Polytechnic School, Department of Electromechanical Engineering at the University of Burgos.
Coordinator, leader and participant in myriad international projects (FET CIRCULAR VISION, EraCoSysMed 4D-HEALING), nationally and regionally, he is also a member of CIBERfes (Network Centre for Biomedical Research in Frailty and Healthy Ageing) and of the Excellence Thematic Network for Translational Bioinformatics (TransBioNet).
He has more than 150 publications in journals including Science, Nature, Nature Cell Biology, Nature Chemical Biology, American Chemical Journal, Cell and Cell Stem Cell. More than 10,000 citations in Google Scholar, h-index: 47 and i10 index: 106 (February 2020). He is also the co-inventor of 3 registered patents.
He has directed one doctoral thesis and is currently directing another four.

Strategic Objectives

  • Development of computational methods for the analysis and modeling of biological systems and their utilization for elucidating better understanding of stem cells, cellular reprogramming stem cells, diseases and aging mechanisms.
  • Study the interaction of biological networks (genetic, epigenetic, metabolic, and proteomic) in terms of their typology, perturbation response and dynamics.
  • Development of artificial vision methods for the automatic analysis and characterization of cellular and subcellular structures from static and dynamic images.
  • Development of data mining methods for medical histories analysis based on artificial intelligent technics to predict health condition, diseases and aging.
  • Synergetic integration of the “macroscopic” information provided by the medical histories data with the “microscopic” information provided by image data with the “molecular” information provided by the omics data for better understanding of human diseases and aging.
  • Exploration of how genetic variations between individuals influence their cell biological functions and – ultimately – disease, using a combination of iPSC technology and –omics data.

Main research lines

In mathematical modeling of biological systems

  • De novo prediction of genomic regulatory hot spots as building blocks for mathematical models of the cross-talk between genetic and epigenetic networks.
  • Biological network analysis. By perturbing network components, analyze the induced changes in their performance to understand the synergistic and antagonistic effects of the perturbations. Developing methods to identify the typology and the dynamics of the biological networks analyzing network properties such as the presence of motifs, and integrating systems engineering tools for the analysis of stability of controllability, robustness, response to perturbation and stochasticity. Application for better understanding of stem cells, cellular reprogramming, disease states, disease progression and aging mechanisms.
  • Identification and characterization of regulatory cores in pluripotent networks, in stem cells, in diseases and in aging.
  • Development of dynamical models to understand the genetic regulatory networks of pluripotent cells, cellular reprogramming, stem cells, diseases and aging.

In bioinformatics

  • Computational quality control of pluripotent cells by high throughput transcriptomics and epigenomics data analysis.
  • Integration of transcriptomics data form different platforms to create big corpus datasets.
  • Development of computational tools to exploit high throughput data, integrating omics data of different nature (transcriptomics, Chip-Seq, DNA methylomics, histone marks, microRNA expression and proteomics).
  • Implementation of data integrative approaches from different omic technologies to elucidate the cross-talk of the main molecular players of pluripotent cells, stem cells, diseases and aging.
  • Develop upstream and downstream statistical/machine learning analysis tools for mining next-generation sequencing data (RNAseq, ChIp-Seq of histone modification, and genome-wide DNA methylation.
  • Identification of targets for direct reprogramming
  • Identification of biomarkers for cancer research.
  • Search of DNA sequence patterns and DNA words for building DNA dictionaries and grammars.
  • Development of data mining methods for medical histories based on artificial intelligent strategies to predict health condition, diseases and aging.

Team Members

Name Surname
Center E-mail
Coloma Álvarez De Eulate López Donostialdea IHO elena.guimonolaizola@osakidetza.eus
Mikel Arrospide Elgarresta Biodonostia HRI mikel.arrospide@biodonostia.org
Javier Cabau Laporta Biodonostia HRI javier.cabau@biodonostia.org
Itziar Frades Alzueta Biodonostia HRI itziar.frades@biodonostia.org
Daniela Ivanova Gerovska Biodonostia HRI daniela.gerovska@biodonostia.org
Olga Ibañez Sole Biodonostia HRI olga.ibanez@biodonostia.org
Shira Knafo CSIC, UPV/EHU s.knafo@ikerbasque.org
Alex Martínez Ascensión Biodonostia HRI  alex.martinez@biodonostia.org
Maite Unzurrunzaga Altube Donostialdea IHO maite.unzurrunzagaaltube@osakidetza.eus

Scientific Output

DATA DRIVEN DRUG DISCOVERY FOR WOUND HEALING
Código: AC17/00012
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: ISCIII INSTITUTO DE SALUD CARLOS III
Fecha de Inicio: 2018-01-01
Fecha de finalización: 2021-12-31
Importe Concedido: 149.998,86 €
M4B DESCUBRIMIENTOS DE NUEVOS FARMACOS PARA ENFERMEDADES OSEAS
Código: KK-2018/00031
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: DEPARTAMENTO DE DESARROLLO ECONÓMICO E INFRAESTRUCTURAS
Fecha de Inicio: 2018-02-23
Fecha de finalización: 2020-03-31
Importe Concedido: 82.000,00 €
MIFLUDAN MICROFLUIDICA Y DATA ANALYTICS PARA LA CREACION DE UN SISTEMA DE APOYO AL TRATAMIENTO PERSONALIZADO EN ONCOLOGIA
Código: KK-2018/00034
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: DEPARTAMENTO DE DESARROLLO ECONÓMICO E INFRAESTRUCTURAS
Fecha de Inicio: 2018-02-23
Fecha de finalización: 2020-03-31
Importe Concedido: 55.250,00 €
PREDICCION DEL RIESGO DE PROGRESION DE LA ENFERMEDAD RENAL CRONICA EN UNA POBLACION COLOMBIANA
Código: INTER/18/COLCIENCIAS/
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: GOBIERNO DE COLOMBIA
Fecha de Inicio: 2019-02-01
Fecha de finalización: 2021-01-31
Importe Concedido: 0,00 €
AFIANZANDO LA RED BIOINFORMATICA TRASLACIONAL TRANSBIONET
Código: RED2018-102404-T
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: MINISTERIO DE CIENCIA E INNOVACION
Fecha de Inicio: 2020-01-01
Fecha de finalización: 2021-12-31
Importe Concedido: 0,00 €
MULTFRET NUEVA METODOLOGIA AVANZADA PARA CRIBADO DE FARMACOS PARA ESQUIZOFRENIA
Código: KK-2019/00049
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: DEPARTAMENTO DE DESARROLLO ECONÓMICO E INFRAESTRUCTURAS
Fecha de Inicio: 2019-03-01
Fecha de finalización: 2021-05-31
Importe Concedido: 111.346,00 €
CIRCULAR DNA IN DIAGNOSIS AND DISEASE MODELS
Código: UE/2019/H2020/CIRCULARVISION2
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: COMISION EUROPEA - HORIZON 2020
Fecha de Inicio: 2020-06-01
Fecha de finalización: 2023-12-01
Importe Concedido: 650.625,00 €
RESPUESTAS “ADAPTATIVAS” DE LAS CELULAS MADRE MESENQUIMALES FRENTE AL COVID19, IMPLICACION EN TERAPIA CELULAR
Código: 2020111055/BD
Investigador Principal (IP): MIKEL ARROSPIDE ELGARRESTA
Entidad Financiadora: DEPARTAMENTO DE SALUD
Fecha de Inicio: 2020-12-01
Fecha de finalización: 2023-12-31
Importe Concedido: 31.339,00 €
PREDICCION DEL RIESGO DE RECAIDA EN PACIENTES SOMETIDOS A CIRUGIA DE CANCER COLORRECTAL MEDIANTE TECNICAS DE DEEP LEARNING (PRERCCOL)
Código: 2020111031/BD
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: DEPARTAMENTO DE SALUD
Fecha de Inicio: 2020-12-01
Fecha de finalización: 2023-12-31
Importe Concedido: 127.050,00 €
PLANACON: ESTUDIO BIOLOGICO Y COMPUTACIONAL DEL PAPEL DE LAS CONVERTASAS DE PROTEINAS EN LOS PROCESOS ONCOLOGICOS
Código: 2020333001
Investigador Principal (IP): DANIELA IVANOVA GEROVSKA
Entidad Financiadora: DEPARTAMENTO DE SALUD
Fecha de Inicio: 2020-01-01
Fecha de finalización: 2020-12-31
Importe Concedido: 72.600,00 €
TERSARSFURNA; TERAPIA CONTRA EL VIRUS SARS-COV2 BASADO EN EL BLOQUEO DE LA FURINA COMBINADO CON EXOSOMAS DE CELULAS STEM Y NANOTECNOLOGIA
Código: 2020333039/BD
Investigador Principal (IP): MARCOS JESUS ARAUZO BRAVO
Entidad Financiadora: DEPARTAMENTO DE SALUD
Fecha de Inicio: 2020-01-01
Fecha de finalización: 2020-12-31
Importe Concedido: 77.440,00 €
DESCUBRIMIENTO DE LAS PALABRAS EPIGENÉTICAS DE ADN RESPONSABLE DE LA REGULACIÓN CELULAR MEDIANTE EL DESARROLLO DE ALGORITMOS COMPUTACIONALES DE ANÁLISIS DE DATOS EPIGENÓMICOS
Código: 2020-CIEN-000072-01
Investigador Principal (IP): DANIELA IVANOVA GEROVSKA
Entidad Financiadora: DIPUTACION FORAL GIPUZKOA
Fecha de Inicio: 2020-07-09
Fecha de finalización: 2021-09-30
Importe Concedido: 57.523,00 €