137 documents found, page 1 of 14
Leveraging deep learning to detect stance in Spanish tweets on COVID-19 vaccina...
Blanco, Guillermo; Yáñez Martínez, Rubén; Lourenço, AnáliaObjectives: The automatic detection of stance on social media is an important task for public health applications, especially in the context of health crises. Unfortunately, existing models are typically trained on English corpora. Considering the benefits of extending research to other widely spoken languages, the goal of this study is to develop stance detection models for social media posts in Spanish. Mater...
Targeted depletion of pks+ bacteria from a fecal microbiota using specific anti...
Blanco-Míguez, Aitor; Marcos-Fernández, Raquel; Guadamuro-García, Lucía; Fdez-Riverola, Florentino; Cubiella, Joaquín; Lourenço, AnáliaThe pks island is one of the most prevalent pathogenicity islands among the Escherichia coli strains that colonize the colon of colorectal carcinoma (CRC) patients. This pathogenic island encodes the production of a nonribosomal polyketide-peptide named colibactin, which induces double-strand breaks in DNA molecules. Detection or even depletion of this pks-producing bacteria could help to understand the role of...
Use social media knowledge for exploring the portuguese wine industry: followin...
Pérez-Rodríguez, Gael; Baptista, João Pedro; Igrejas, Gilberto; Fdez-Riverola, Florentino; Lourenço, AnáliaThis work presents an exploratory study that retrieves, processes, and analyses Twitter data to gain insights about the relevance and perceptions of the wine industry in the Douro Portuguese region (including Porto and Douro wines), as well as other regions in the country. The main techniques and algorithms used in our work belong to the families of natural language processing and machine learning, and the prac...
Optimism and pessimism analysis using deep learning on COVID-19 related Twitter...
Blanco, Guillermo; Lourenço, AnáliaThis paper proposes a new deep learning approach to better understand how optimistic and pessimistic feelings are conveyed in Twitter conversations about COVID-19. A pre-trained transformer embedding is used to extract the semantic features and several network architectures are compared. Model performance is evaluated on two new, publicly available Twitter corpora of crisis-related posts. The best performing pe...
HaemoKBS: a knowledge-based system for real-time, continuous categorisation of ...
Ramoa, Augusto; Condeço, Jorge; Fdez-Riverola, Florentino; Lourenço, AnáliaThis work introduces HaemoKBS, a novel Haemovigilance decision support system for adverse reactions in blood recipients. Machine learning inference and rule-based reasoning were applied to build the underlying decision support models, namely to automatically extract evidence from different types of data included in hospital notifications and incorporate a priori expert knowledge. The ultimate aim is to dynamica...
Computational resources and strategies to assess single-molecule dynamics of th...
Magalhães, Beatriz T.; Lourenço, Anália; Azevedo, Nuno F.This work provides a systematic and comprehensive overview of available resources for the molecular-scale modelling of the translation process through agent-based modelling. The case study is the translation in Saccharomyces cerevisiae, one of the most studied yeasts. The data curation workflow encompassed structural information about the yeast (i.e. the simulation environment), and the proteins, ribonucleic ac...
Computational approach to the systematic prediction of glycolytic abilities: lo...
Blanco, Guillermo; Sanchez, Borja; Ruiz, Lorena; Fdez-Riverola, Florentino; Margolles, Abelardo; Lourenço, AnáliaGlycoside hydrolases are responsible for the enzymatic deconstruction of complex carbohydrates. Most of the families are known to conserve the catalytic machinery and molecular mechanisms. This work introduces a new method to predict glycolytic abilities in sequenced genomes and thus, gain a better understanding of how to target specific carbohydrates and identify potentially interesting sources of specialised ...
A health-related study from food online reviews. The case of gluten-free foods
Pérez-Pérez, Martín; Lourenço, Anália; Igrejas, Gilberto; Fdez-Riverola, FlorentinoConcerning the field of Health Sciences, one of the trends with the greatest impact today is related to the feeding and consumption of foods intended for chronic patients with a nutritional association. According to this, the gluten-free diet is one of the diets with a today's fastest-growing due to their health therapy associations for different diseases and because of more and more people are freely choosing ...
The activity of bioinformatics developers and users in Stack Overflow
Pérez-López, Roi; Blanco, Guillermo; Fdez-Riverola, Florentino; Lourenço, AnáliaIn this work, different social data mining approaches are used to characterize the user churning and social traits of the Bioinformatics community over the first ten years of Stack Overflow. The proposed workflow consists of a four-step procedure that allows the characterization of users based on the social exchange exhibited by the Bioinformatics community and the Developers communities, notably the Python, Ma...
A framework to extract biomedical knowledge from gluten-related tweets: the cas...
Pérez-Pérez, Martín; Igrejas, Gilberto; Fdez-Riverola, Florentino; Lourenço, AnáliaBig data importance and potential are becoming more and more relevant nowadays, enhanced by the explosive growth of information volume that is being generated on the Internet in the last years. In this sense, many experts agree that social media networks are one of the internet areas with higher growth in recent years and one of the fields that are expected to have a more significant increment in the coming yea...