curriculum

Bioinformatician

MALL, Universidade da Coruña

Working on drug repurposing. The project's focus on repurposing existing drugs for new therapies aims to address high failure rates and costs.

• Bioinformatics
• Drug Repurpousing
• Docking

Bioinformatician

CITIC, Universidade da Coruña

Working on an application for the detection of polyps in colonoscopy using Deep Learning. As well as the integration of the models generated in web applications and mobile applications.I was working with python for image processing and model training (opencv, tensorflow, keras, scikit-learn...). For the web development I used flask and for the Android application I used TensorFlow Lite and Dart.

• Bioinformatics
• Computer Vision

Bioinformatician

Fundación Profesor Novoa Santos

Working as a bioinformatics researcher in a project called Practicum Direct (IN845D2020/03), focused on analysis, validation and testing of ad hoc simulation models designed with open data and predictive models based on real data. I had several duties: review of the state of the art in terms of availability of open omics and clinical data, implementation of predictive models on real open data in R/Python and create dashboards with R and Shiny for the manipulation and presentation of results in an interactive ways.

• Bioinformatics
• Machine Learning

Bioinformatician

Fundación Profesor Novoa Santos

Working as a bioinformatics researcher in a colorectal cancer project. During this period I gained experience in metagenomic data processing, as well as, developing Machine Learning and Artificial Intelligence pipelines. Also I gained experience in the presentation and visualization of complex data.

• Bioinformatics
• Machine Learning

Teacher

Small World Initiative

The Small World Initiative® (SWI) is an innovative program that encourages students to pursue careers in science while addressing a worldwide health threat superbugs and the diminishing supply of effective antibiotics

• SWI
• Superbugs
• Antibiotics
• Scientific dissemination

PhD at MALL Lab

University of A Coruña

Bioinformatics

• Bioinformatics

Bioinformatics for Health Sciences Masters degree

University of A Coruña

Bioinformatics for Health Sciences

• Bioinformatics

Biology degree

University of A Coruña

Biology

• Biology

Honourable mention

University of A Coruña

Honourable mention in Master's thesis

Honourable mention

University of A Coruña

Honourable mention in Data Structures and Algorithmics for Biological Sequences

RePo-SUDOE - A translational network for drug repurposing in the SUDOE space

RExPO25 Conference

The RePo-SUDOE project brings together diverse partners from the SUDOE space to collaborate on drug repurposing, making scientific information more accessible and using advanced visualization technologies to strengthen the field in this geographic region.

Fecal microbiome analysis in patients with metabolic syndrome and type 2 diabetes

PeerJ

This study reveals notable differences in the intestinal microbiota composition among patients with MS and T2D.

Cross Sequencing Integration of Compositional Microbiome Data in Cancer

Lecture Notes in Computer Science

This work evaluates batch effect removal (BER) methods for integrating microbiome composition data from different sequencing platforms.

Microbiome preterm birth DREAM challenge: Crowdsourcing machine learning approaches to advance preterm birth research

Cell Reports Medicine

This work serves as the foundation for subsequent efforts to translate predictive tests into clinical practice and to better understand and prevent preterm birth.

VIBES: A consensus subtyping of the vaginal microbiota reveals novel classification criteria

Computational and Structural Biotechnology Journal

This study aimed to develop a robust classification scheme for stratifying patients based on vaginal microbiome. By employing consensus clustering analysis, we identified four distinct clusters using a cohort that includes individuals diagnosed with Bacterial Vaginosis (BV) as well as control participants, each characterized by unique patterns of microbiome species abundances.

Machine Learning analysis of the human infant gut microbiome identifies influential species in type 1 diabetes

Expert Systems with Applications

Diabetes is a disease that is closely linked to genetics and epigenetics, yet mechanisms for clarifying the onset and/or progression of the disease have sometimes not been fully managed. In recent years and due to the large number of recent studies, it is known that changes in the balance of the microbiota can cause a high battery of diseases, including diabetes.

La Inteligencia Artificial como herramienta para la gestión y explotación de datos, informaciones y conocimientos biomédicos en entornos “Big Data” en la nube

I+ S: Revista de la Sociedad Española de Informática y Salud

En este artículo, se ofrecerá una panorámica, no exhaustiva, de la situación actual en la I+D+i de la Inteligencia Artificial en el campo Biomedicina, los pros y los contras, así como algunos de los “hitos” ya alcanzados en este ámbito.

Identification of Pevotella, Anaerotruncus and Eubacterium Genera by Machine Learning Analysis of Metagenomic Profiles for Stratificaction of Patients Affected by Type I Diabetes

Proceedings

Previous works have reported different bacterial strains and genera as the cause of different clinical pathological conditions. In our approach, using the fecal metagenomic profiles of newborns, a machine learning-based model was generated capable of discerning between patients affected by type I diabetes and control

TBD

TBD

• TBD
• TBD