I am Ibon Martínez-Arranz. I hold a BSc in Mathematics from the University of the Basque Country (EHU/UPV), as well as two MSc degrees: one in Current Applied Statistics Techniques and another in Mathematical Modeling Research, Statistical Analysis, and Computing Sciences. In 2004, I joined the Basque Country Health Service (Department of Health of the Basque Government and Osakidetza) as a data analyst, focusing primarily on epidemiological reports for renal patients.
In 2010, I joined OWL Metabolomics (now Rubió Metabolomics), initially as a researcher in the Metabolomics Department. Since 2017, I have been leading the Data Science Department, overseeing predictive modeling and statistical computing. My work supports metabolomics services, laboratory processes, data handling, R&D projects, and technology transfer.
In 2025, I completed a PhD in Biomedical Sciences, with a thesis focused on the application of 🧬 genetic algorithms 🧬 for the identification of MASLD subtypes, bridging computational approaches with translational medicine and contributing to the field of precision medicine.
Education
| INSTITUTION AND LOCATION |
DEGREE | COMPLETION DATE |
FIELD OF STUDY |
|---|---|---|---|
| University of Basque Country (UPV/EHU) (Biscay, Spain) | BSc. | June 2003 | Mathematics |
| National University of Distance Education (Spain) | Expert degree | July 2007 | Statistics Applied to Health Sciences |
| National University of Distance Education (Spain) | Expert degree | July 2008 | Advanced Methods of Applied Statistics |
| National University of Distance Education (Spain) | MSc. | July 2012 | Current Applied Statistics Techniques |
| National University of Distance Education (Spain) | Expert degree | July 2013 | Multivariate Statistical Techniques |
| University of Basque Country (UPV/EHU) (Biscay, Spain) | MSc. | May 2016 | Mathematical Modeling, Statistical Analysis and Computation |
| University of Basque Country (UPV/EHU) (Biscay, Spain) | PhD. | June 2025 | Applied Mathematics |
I completed a doctoral thesis entitled Genetic Algorithms Applied to Translational Strategy in MASH: Learning from Mouse Models, where I applied 🧬 genetic algorithms 🧬 to identify MASLD subtypes. This methodology can be extended to other diseases driven by metabolic changes. The work contributes to the advancement of precision medicine by enabling more targeted and effective interventions.
Contributions to Science
Author of 27 publications. Scopus h-index = 19. Researcher unique identifier
'Omics' research generates a large amount of data for every sample. OWL has established a well-defined workflow and a set of guidelines for analyzing omics data. It includes statistical design of experiments, data structuration and predictive modelling.
Peer-reviewed papers:
- Martínez-Arranz, I, et al. Enhancing metabolomics research through data mining, J. Proteomics, 2015;127(B)275-288.
- Barr J, et al. Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression. J. Proteome Res 2012;11(4),2521-32
- Arbelaiz A, et al. Serum extracellular vesicles contain protein biomarkers for primary sclerosing cholangitis and cholangiocarcinoma. Hepatology. 2017; 10.1002/hep.29291.
- Cano A, et al. A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients. Scientific Reports. 2017;7(1):10497.
We have developed predictive algorithms for several diseases. We have been really involved in the development and validation of the OWLiver, OWLiver F2+ and OWLiver DM2 tests.
Peer-reviewed papers:
- Barr J, et al. Obesity-dependent metabolic signatures associated with nonalcoholic fatty liver disease progression. J. Proteome Res. 2012;11(4):2521-32.
- Cano A, et al. A Metabolomics Signature Linked To Liver Fibrosis In The Serum Of Transplanted Hepatitis C Patients. Scientific Reports. 2017;7(1):10497.
- Herreros-Villanueva M, et al. Plasma MicroRNA Signature Validation for Early Detection of Colorectal Cancer. Clin Transl Gastroenterol. 2019 Jan;10(1).
- Matorras R, et al. The lipidome of endometrial fluid differs between implantative and non-implantative IVF cycles. J Assist Reprod Genet. 2020;37(2):385-94.
- Martínez-Arranz I, et al. Metabolomic-based noninvasive serum test to diagnose nonalcoholic steatohepatitis: Results from discovery and validation cohorts. Hepatol Commun. 2018 May 4;2(7):807-820.
Peer-reviewed papers:
- Alonso C, et al. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis. Gastroenterology 2017;152(6):1449-61.
- Banales JM, et al. Serum metabolites as diagnostic biomarkers for cholangiocarcinoma, hepatocellular carcinoma and primary sclerosing cholangitis. Hepatology 2019;70(2):547-65.
- Herreros-Villanueva M, et al. Plasma MicroRNA Signature Validation for Early Detection of Colorectal Cancer. Clin Transl Gastroenterol. 2019 Jan;10(1).
- Matorras R, et al. The lipidome of endometrial fluid differs between implantative and non-implantative IVF cycles. J Assist Reprod Genet. 2020;37(2):385-94.
- Martínez-Arranz I, Alonso C, Mayo R, Mincholé I, Mato JM, Lee DJ. Genetic algorithms applied to translational strategy in metabolic-dysfunction associated steatohepatitis (MASH). Learning from mouse models. Comput Methods Programs Biomed. 2024 Oct;255:108346. doi: 10.1016/j.cmpb.2024.108346.
Skills
| TOPIC | SOFTWARE | SKILLS |
|---|---|---|
| Programming Languages for Data Science | Python R SQL |
🟥🟥🟥🟥🟥 🟥🟥🟥🟥⬜ 🟥🟥🟥🟥⬜ |
| Data Analysis | Pandas Pingouin |
🟥🟥🟥🟥🟥 🟥🟥🟥🟥🟥 |
| Data Computation | Numpy Scipy |
🟥🟥🟥🟥🟥 🟥🟥🟥🟥⬜ |
| Data Bases | MySQL SQLite MongoDB |
🟥🟥🟥⬜⬜ 🟥🟥🟥🟥⬜ 🟥🟥⬜⬜⬜ |
| Machine Learning | Scikit-Learn | 🟥🟥🟥🟥⬜ |
| Big Data | H2O | 🟥🟥🟥🟥⬜ |
| Visualization Tools | Matplotlib Seaborn Altair |
🟥🟥🟥🟥⬜ 🟥🟥🟥🟥🟥 🟥🟥🟥🟥⬜ |
| Web | Shiny Streamlit |
🟥🟥🟥🟥⬜ 🟥🟥🟥⬜⬜ |
Patents and Pendings
| PUBLICATION NUMBER |
TITLE | INTERNATIONAL FILING DATE |
|---|---|---|
| WO2021028562 | Lipid signatures for determining the outcome of embryo implantation during in vitro fertilization | 14.08.2020 |
| WO2018007511 | Diagnostic methods based on lipid profiles | 06.07.2017 |
| WO2018007422 | Identification of human Non-Alcoholic Fatty Liver Disease (NAFLD) subtypes | 05.07.2017 |
| WO2017055397 | Metabolomic signature of diagnosis and disease progression in Non-Alcoholic Fatty Liver Disease (NAFLD) | 29.09.2016 |
Publications
🟨 MASLD Disease 🟩 Subtypes 🟧 Machine Learning and Modelling 🟪 In Vitro Diagnostic test
- 📌 I’m currently working as 📊 Senior Data Scientist 📊 @ Rubió Metabolomics.
- 📌 I’m currently learning Streamlit, Panel and MongoDB, ...
- 📌 I'm interested in: 👨🔬 Data Science 🐍 Python 🐼 Pandas 🤖 Machine Learning 🗂️ SQL and DataBases 📊 Data Analysis 🚀 SKlearn
- 📌 I want to learn about: ⚙️ awk
- 📌 I use daily:
.ipynb,.py,.sql,.sqlite,.yaml,.R,.tex, ... - 📌 Ask me about 🧬 Genetic Algorithms 🧬
- 📌 I Love Data Visualization 📊📈📉.
- 📌 Fun fact: I'm a huge fan of The Lord of the Rings and LEGO®
