Lucía Prieto Santamaría

Lucía Prieto Santamaría
Universidad Politécnica de Madrid | UPM · Centre for Biomedical Technology

About

32
Publications
4,974
Reads
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118
Citations
Citations since 2017
32 Research Items
118 Citations
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201720182019202020212022202301020304050
Additional affiliations
October 2019 - present
Universidad Politécnica de Madrid
Position
  • PhD Student
Education
September 2018 - July 2019
Universidad Politécnica de Madrid
Field of study
  • Computational Biology
September 2014 - July 2018
Universidad Politécnica de Madrid
Field of study
  • Biotechnology

Publications

Publications (32)
Article
This paper presents an original Intelligent and Secure Asset Discovery Tool (ISADT) that uses artificial intelligence and TPM-based technologies to: (i) detect the network assets, and (ii) detect suspicious pattern in the use of the network. The architecture has specifically been designed to discover the assets of medium and large size companies an...
Chapter
There is a large number of online documents data sources available nowadays. The lack of structure and the differences between formats are the main difficulties to automatically extract information from them, which also has a negative impact on its use and reuse. In the biomedical domain, the DISNET platform emerged to provide researchers with a re...
Article
Full-text available
Rare diseases are a group of uncommon diseases in the world population. To date, about 7000 rare diseases have been documented. However, most of them do not have a known treatment. As a result of the relatively low demand for their treatments caused by their scarce prevalence, the pharmaceutical industry has not sufficiently encouraged the research...
Preprint
Full-text available
There is a large number of online documents data sources available nowadays. The lack of structure and the differences between formats are the main difficulties to automatically extract information from them, which also has a negative impact on its use and reuse. In the biomedical domain, the DISNET platform emerged to provide researchers with a re...
Preprint
In the recent years and due to COVID-19 pandemic, drug repurposing or repositioning has been placed in the spotlight. Giving new therapeutic uses to already existing drugs, this discipline allows to streamline the drug discovery process, reducing the costs and risks inherent to de novo development. Computational approaches have gained momentum, and...
Preprint
Drug repositioning is a novel, useful, and crucial technique to find new uses for existing drugs. In this field of study, when the clinical trials necessary to obtain successful drug repositioning have been carried out, the female gender has not been given much consideration. Thus far, the participation of women in clinical trials has been very lim...
Preprint
The DISNET project (https://disnet.ctb.upm.es) was conceived in the context of drug repurposing, aiming to build a large-scale disease network and integrating heterogeneous biomedical knowledge. It is being carried out in the Medical Data Analytics Laboratory (MEDAL) located at the Center for Biomedical Technology (CTB) of the Universidad Politécni...
Chapter
Rare diseases are a group of unusual pathologies in the world population, hence their name. They are considered the great neglected field of pharmaceutical research. To date, over 6,000 rare diseases have been identified and most of them lack treatment. The fact that they are so rare in the population does not encourage research efforts since their...
Article
Full-text available
Established nosological models have provided physicians an adequate enough classification of diseases so far. Such systems are important to correctly identify diseases and treat them successfully. However, these taxonomies tend to be based on phenotypical observations, lacking a molecular or biological foundation. Therefore, there is an urgent need...
Article
Objectives The aim of the study is to design an ontology model for the representation of assets and its features in distributed health care environments. Allow the interchange of information about these assets through the use of specific vocabularies based on the use of ontologies. Methods Ontologies are a formal way to represent knowledge by means...
Article
Full-text available
In the COVID-19 pandemic, drug repositioning has presented itself as an alternative to the time-consuming process of generating new drugs. This review describes a drug repurposing process that is based on a new data-driven approach: we put forward five information paths that associate COVID-19-related genes and COVID-19 symptoms with drugs that dir...
Article
Full-text available
Drug repurposing has become a widely used strategy to accelerate the process of finding treatments. While classical de novo drug development involves high costs, risks, and time-consuming paths, drug repurposing allows to reuse already-existing and approved drugs for new indications. Numerous research has been carried out in this field, both in vit...
Article
Full-text available
The ever-growing availability of biomedical text sources has resulted in a boost in clinical studies based on their exploitation. Biomedical named-entity recognition (bio-NER) techniques have evolved remarkably in recent years and their application in research is increasingly successful. Still, the disparity of tools and the limited available valid...
Preprint
Full-text available
The simultaneous presence of diseases worsens the prognosis of patients and makes their treatment difficult. Identifying the co-occurrence of diseases is key to improving the situation of patients and designing effective therapeutic strategies. On the one hand, the increasing availability of clinical information opens new ways to unveil hidden rela...
Preprint
Full-text available
Background and Objectives: The growing integration of healthcare sources is improving our understanding of diseases. Cross-mapping resources such as UMLS play a very important role in this area, but their coverage is still incomplete. With the aim to facilitate the integration and interoperability of biological, clinical and literary sources in stu...
Article
Background and Objectives The growing integration of healthcare sources is improving our understanding of diseases. Cross-mapping resources such as UMLS play a very important role in this area, but their coverage is still incomplete. With the aim to facilitate the integration and interoperability of biological, clinical and literary sources in stud...
Article
Full-text available
Social media, and in particularly Twitter, can be a resource of enormous value to retrieve information about the opinion of general population to vaccines. The increasing popularity of this social media has allowed to use its content to have a clear picture of their users on this topic. In this paper, we perform a study about vaccine-related messag...
Article
Full-text available
Sentiment analysis is one of the hottest topics in the area of natural language. It has attracted a huge interest from both the scientific and industrial perspective. Identifying the sentiment expressed in a piece of textual information is a challenging task that several commercial tools have tried to address. In our aim of capturing the sentiment...
Article
Wikipedia, also known as "The Free Encyclopaedia”, is one of the largest online repositories of biomedical information in the world, and is nowadays increasingly been used by medical researchers and health professionals alike. In spite of its rising popularity, little attention has been devoted to the understanding of how such medical information i...
Preprint
Full-text available
While classical disease nosology is based on phenotypical characteristics, the increasing availability of biological and molecular data is providing new understanding of diseases and their underlying relationships, that could lead to a more comprehensive paradigm for modern medicine. In the present work, similarities between diseases are used to st...
Article
Full-text available
Background Within the global endeavour of improving population health, one major challenge is the identification and integration of medical knowledge spread through several information sources. The creation of a comprehensive dataset of diseases and their clinical manifestations based on information from public sources is an interesting approach th...
Article
Over a decade ago, a new discipline called network medicine emerged as an approach to understand human diseases from a network theory point-of-view. Disease networks proved to be an intuitive and powerful way to reveal hidden connections among apparently unconnected biomedical entities such as diseases, physiological processes, signaling pathways,...
Preprint
Full-text available
The increasing availability of biological, clinical and literary sources enables the study of diseases from a more comprehensive approach. However, the interoperability of these sources, particularly of the codes used to identify diseases, poses a major challenge. Because of its role as a hub of multiple medical vocabularies, the Unified Medical La...
Preprint
Full-text available
Within the global endeavour of improving population health, one major challenge is the increasingly high cost associated with drug development. Drug repositioning, i.e. finding new uses for existing drugs, is a promising alternative; yet, its effectiveness has hitherto been hindered by our limited knowledge about diseases and their relationships. I...
Preprint
Full-text available
Over a decade ago, a new discipline called network medicine emerged as an approach to understand human diseases from a network theory point-of-view. Disease networks proved to be an intuitive and powerful way to reveal hidden connections among apparently unconnected biomedical entities such as diseases, physiological processes, signaling pathways,...
Conference Paper
Full-text available
The increasing availability of biological data is improving our understanding of diseases and providing new insight into their underlying relationships. Thanks to the improvements on both text mining techniques and computational capacity, the combination of biological data with semantic information obtained from medical publications has proven to b...

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Projects

Projects (2)
Project
Taking into account the strong need to use Big Data in healthcare, and specifically in lung cancer treatment, as well as the experience of the five members of the consortium, P4-LUCAT’s objective is: To develop an ICT solution supporting oncologists in the selection of the most appropriate lung cancer treatment. The solution will provide a dashboard based on Big Data analytics integrating both patient data, public repositories and literature evidence.