PPIntegrator: semantic integrative system for protein-protein interaction and application for host-pathogen datasets.

Summary: Semantic web standards have shown importance in the last 20 years in promoting data formalization and interlinking between the existing knowledge graphs. In this context, several ontologies and data integration initiatives have emerged in recent years for the biological area, such as the broadly used Gene Ontology that contains metadata to annotate gene function and subcellular location. Another important subject in the biological area is protein-protein interactions (PPIs) which have applications like protein function inference.

Large-Scale Protein Interactions Prediction by Multiple Evidence Analysis Associated With an In-Silico Curation Strategy.

Predicting the physical or functional associations through protein-protein interactions (PPIs) represents an integral approach for inferring novel protein functions and discovering new drug targets during repositioning analysis. Recent advances in high-throughput data generation and multi-omics techniques have enabled large-scale PPI predictions, thus promoting several computational methods based on different levels of biological evidence. However, integrating multiple results and strategies to optimize, extract interaction features automatically and scale up the entire PPI prediction process is still challenging.

Algorithmic Information Distortions in Node-Aligned and Node-Unaligned Multidimensional Networks.

In this article, we investigate limitations of importing methods based on algorithmic information theory from monoplex networks into multidimensional networks (such as multilayer networks) that have a large number of extra dimensions (i.e., aspects).

Contextual dimensions for cache replacement schemes in information-centric networks: a systematic review.

In recent years, information-centric networks (ICNs) have gained attention from the research and industry communities as an efficient and reliable content distribution network paradigm, especially to address content-centric and bandwidth-needed applications together with the heterogeneous requirements of emergent networks, such as the Internet of Things (IoT), Vehicular Ad-hoc NETwork (VANET) and Mobile Edge Computing (MEC). In-network caching is an essential part of ICN architecture design, and the performance of the overall network relies on caching policy efficiency. Therefore, a large number of cache replacement strategies have been proposed to suit the needs of different networks.

New perspectives on analysing data from biological collections based on social network analytics.

Biological collections have been historically regarded as fundamental sources of scientific information on biodiversity. They are commonly associated with a variety of biases, which must be characterized and mitigated before data can be consumed. In this work, we are motivated by taxonomic and collector biases, which can be understood as the effect of particular recording preferences of key collectors on shaping the overall taxonomic composition of biological collections they contribute to.

AToMS: A Ubiquitous Teleconsultation System for Supporting AMI Patients with Prehospital Thrombolysis.

The latest population-based studies in the medical literature worldwide indicate that acute myocardial infarction (AMI) patients still experience prolonged delay to be rescued, which often results in morbidity and mortality. This paper reports from a technological standpoint a teleconsultation and monitoring system named AToMS. This system addresses the problem of prehospital delivery of thrombolysis to AMI patients by enabling the remote interaction of the paramedics and a cardiologist available at a Coronary Care Unit (CCU).