A5034664449- Semantic Web and Ontologies
- IoT and Edge/Fog Computing
- Gene expression and cancer classification
- Scientific Computing and Data Management
- Bioinformatics and Genomic Networks
- Service-Oriented Architecture and Web Services
- Big Data and Business Intelligence
- Context-Aware Activity Recognition Systems
- Biomedical Text Mining and Ontologies
- Genetic Associations and Epidemiology
- Research Data Management Practices
- Genetics, Bioinformatics, and Biomedical Research
- Data Quality and Management
- Genomics and Phylogenetic Studies
- Digital Innovation in Industries
- Machine Learning in Bioinformatics
- Privacy-Preserving Technologies in Data
- Genetic and phenotypic traits in livestock
- Blockchain Technology Applications and Security
- Global Trade and Competitiveness
- Glycosylation and Glycoproteins Research
- Microtubule and mitosis dynamics
- Big Data Technologies and Applications
- Embedded Systems Design Techniques
- Korean Peninsula Historical and Political Studies
Soka University
2024
Ollscoil na Gaillimhe – University of Galway
2017-2023
National University of Ireland
2018-2019
University of Genoa
2010-2012
Ospedale Policlinico San Martino
2011-2012
Today, internet of things (IoT) platforms offer proprietary interfaces and protocols. To enable interoperable interaction with those we present the generic BIG IoT API that employs a novel approach for self-description semantic annotation to fully adapt arbitrary platforms. We have deployed this multiple from mobility domain.
Next Generation Sequencing (NGS) is playing a key role in therapeutic decision making for the cancer prognosis and treatment. The NGS technologies are producing massive amount of sequencing datasets. Often, these datasets published from isolated different facilities. Consequently, process sharing aggregating multisite thwarted by issues such as need to discover relevant data sources, built scalable repositories, automation linkage, volume data, efficient querying mechanism, information rich...
The average life expectancy of the world's population is increasing and healthcare systems sooner than later will be compromised by its reduced capacity highly economic cost; in addition, age distribution leading towards older spectrum.This trend lead to immeasurable unexpected problems social changes.In order face up this challenge complex problem, it necessary rely on appropriate digital tools technological infrastructures for ensuring that elderly are properly cared their everyday living...
The study of genetic variants (GVs) can help find correlating population groups and to identify cohorts that are predisposed common diseases explain differences in disease susceptibility how patients react drugs. Machine learning techniques increasingly being applied interacting GVs understand their complex phenotypic traits. Since the performance a algorithm not only depends on size nature data but also quality underlying representation, deep neural networks (DNNs) learn non-linear mappings...
Abstract Background With the advent of high-throughput technologies, a great wealth variation data is being produced. Such information may constitute basis for correlation analyses between genotypes and phenotypes and, in future, personalized medicine. Several databases on gene exist, but this kind still scarce Semantic Web framework. In paper, we discuss issues related to integration mutation Linked Open Data infrastructure, part We present development mapping from IARC TP53 Mutation...
Data is currently perceived as one of the most valuable resources by industry. In this context, data marketplaces have emerged for facilitating trading in a coordinated manner. To facilitate open, fair, and transparent trades, it necessary to ensure trust, both among different participants stakeholders, trust sense confidence ecosystem. Thanks emergent blockchain technologies, there are new decentralized that provide manner with disruptive services such automated conflict resolution, non...