A5058877446- Biomedical Text Mining and Ontologies
- Topic Modeling
- Semantic Web and Ontologies
- Bioinformatics and Genomic Networks
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Computational Drug Discovery Methods
- Natural Language Processing Techniques
- RNA and protein synthesis mechanisms
- Expert finding and Q&A systems
- Machine Learning in Bioinformatics
- Spam and Phishing Detection
- Genomics and Rare Diseases
- Web Data Mining and Analysis
- CRISPR and Genetic Engineering
- Advanced biosensing and bioanalysis techniques
- Software Engineering Research
- Machine Learning and Data Classification
- Machine Learning and Algorithms
- RNA Research and Splicing
- Genomics and Phylogenetic Studies
- Authorship Attribution and Profiling
- Big Data and Business Intelligence
- Algorithms and Data Compression
- Scientific Computing and Data Management
National Centre of Scientific Research "Demokritos"
2016-2025
Radboud University Nijmegen
2025
Institute of Informatics of the Slovak Academy of Sciences
2022-2025
Institute of Informatics & Telecommunications
2014-2024
Xerox (France)
2008-2015
This article provides an overview of the first BIOASQ challenge, a competition on large-scale biomedical semantic indexing and question answering (QA), which took place between March September 2013. assesses ability systems to semantically index very large numbers scientific articles, return concise user-understandable answers given natural language questions by combining information from articles ontologies.The 2013 comprised two tasks, Task 1a 1b. In participants were asked automatically...
The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated protein 9 (Cas9) system has become a successful and promising technology for gene-editing. To facilitate its effective application, various computational tools have been developed. These can assist researchers in the guide RNA (gRNA) design process by predicting cleavage efficiency specificity excluding undesirable targets. However, while many are available, assessment of their application scenarios...
Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. This study employed machine learning (ML) analyze genomic data from the UK Biobank, aiming predict predisposition complex like multiple sclerosis (MS) Alzheimer's disease (AD). We tested logistic regression (LR), ensemble tree methods, deep models for this purpose. LR displayed remarkable stability across various subsets of data, outshining approaches, which showed greater variability...
Abstract The BioASQ question answering (QA) benchmark dataset contains questions in English, along with golden standard (reference) answers and related material. has been designed to reflect real information needs of biomedical experts is therefore more realistic challenging than most existing datasets. Furthermore, unlike previous QA benchmarks that contain only exact answers, the BioASQ-QA also includes ideal (in effect summaries), which are particularly useful for research on...
Evaluation in empirical computer science is essential to show progress and assess technologies developed. Several research domains such as information retrieval have long relied on systematic evaluation measure progress: here, the Cranfield paradigm of creating shared test collections, defining search tasks, collecting ground truth for these tasks has persisted up until now. In recent years, however, several new challenges emerged that do not fit this very well: extremely large data sets,...
The goal of the BioASQ challenge is to engage researchers into creating cuttingedge biomedical information systems. Specifically, it aims at promotion systems and methodologies that are able deal with a plethora different tasks in domain. This achieved through organization challenges. fifth consisted three tasks: semantic indexing, question answering new task on extraction. In total, 29 teams more than 95 participated challenge. Overall, as previous years, best were outperform strong...
Biomedical experts are facing challenges in keeping up with the vast amount of biomedical knowledge published daily. With millions citations added to databases like MEDLINE/PubMed each year, efficiently accessing relevant information becomes crucial. Traditional term-based searches may lead irrelevant or missed documents due homonyms, synonyms, abbreviations, term mismatch. To address this, semantic search approaches employing predefined concepts associated synonyms and relations have been...
Background: Cell-penetrating peptides (CPPs) facilitate the delivery of a variety therapeutic molecules across plasma membrane, from small chemical substances to nucleic acid-based macromolecules, such as antisense oligonucleotides (ASOs). Among neutral ASOs, peptide acids (PNAs) and phosphorodiamidate morpholino oligomers (PMOs) have been extensively studied potential medical treatments for Duchenne Muscular Dystrophy (DMD), severe genetic disease that causes muscle degeneration...
Evaluation in empirical computer science is essential to show progress and assess technologies developed. Several research domains such as information retrieval have long relied on systematic evaluation measure progress: here, the Cranfield paradigm of creating shared test collections, defining search tasks, collecting ground truth for these tasks has persisted up until now. In recent years, however, several new challenges emerged that do not fit this very well: extremely large data sets,...
In this report, we summarize the outcome of "Evaluation-as-a-Service" workshop that was held on 5th and 6th March 2015 in Sierre, Switzerland. The objective meeting to bring together initiatives use cloud infrastructures, virtual machines, APIs (Application Programming Interface) related projects provide evaluation information retrieval or machine learning tools as a service.