Integration of chromosome locations and functional aspects of enhancers and topologically associating domains in knowledge graphs enables versatile queries about gene regulation.

Knowledge about transcription factor binding and regulation, target genes, cis-regulatory modules and topologically associating domains is not only defined by functional associations like biological processes or diseases but also has a determinative genome location aspect. Here, we exploit these location and functional aspects together to develop new strategies to enable advanced data querying. Many databases have been developed to provide information about enhancers, but a schema that allows the standardized representation of data, securing interoperability between resources, has been lacking.

Sequence-oriented sensitive analysis for PM2.5 exposure and risk assessment using interactive process mining.

The World Health Organization has estimated that air pollution will be one of the most significant challenges related to the environment in the following years, and air quality monitoring and climate change mitigation actions have been promoted due to the Paris Agreement because of their impact on mortality risk. Thus, generating a methodology that supports experts in making decisions based on exposure data, identifying exposure-related activities, and proposing mitigation scenarios is essential. In this context, the emergence of Interactive Process Mining-a discipline that has progressed in the last years in healthcare-could help to develop a methodology based on human knowledge.

Flower transcriptional response to long term hot and cold environments in .

Short term experiments have identified heat shock and cold response elements in many biological systems. However, the effect of long-term low or high temperatures is not well documented. To address this gap, we grew plants from two-weeks old until maturity under control (normal) (22/16°C), cold (15/5°C), and hot (30/23°C) conditions for a period of two years.

Improvement of large copy number variant detection by whole genome nanopore sequencing.

Introduction: Whole-genome sequencing using nanopore technologies can uncover structural variants, which are DNA rearrangements larger than 50 base pairs. Nanopore technologies can also characterize their boundaries with single-base accuracy, owing to the kilobase-long reads that encompass either full variants or their junctions. Other methods, such as next-generation short read sequencing or PCR assays, are limited in their capabilities to detect or characterize structural variants.

Performance assessment of ontology matching systems for FAIR data.

Background: Ontology matching should contribute to the interoperability aspect of FAIR data (Findable, Accessible, Interoperable, and Reusable). Multiple data sources can use different ontologies for annotating their data and, thus, creating the need for dynamic ontology matching services. In this experimental study, we assessed the performance of ontology matching systems in the context of a real-life application from the rare disease domain.

Analysis of the landscape of human enhancer sequences in biological databases.

The process of gene regulation extends as a network in which both genetic sequences and proteins are involved. The levels of regulation and the mechanisms involved are multiple. Transcription is the main control mechanism for most genes, being the downstream steps responsible for refining the transcription patterns.

An automated process for supporting decisions in clustering-based data analysis.

Background And Objective: Metrics are commonly used by biomedical researchers and practitioners to measure and evaluate properties of individuals, instruments, models, methods, or datasets. Due to the lack of a standardized validation procedure for a metric, it is assumed that if a metric is appropriate for analyzing a dataset in a certain domain, then it will be appropriate for other datasets in the same domain. However, such generalizability cannot be taken for granted, since the behavior of a metric can vary in different scenarios.

The gene regulation knowledge commons: the action area of GREEKC.

As computational modeling becomes more essential to analyze and understand biological regulatory mechanisms, governance of the many databases and knowledge bases that support this domain is crucial to guarantee reliability and interoperability of resources. To address this, the COST Action Gene Regulation Ensemble Effort for the Knowledge Commons (GREEKC, CA15205, www.greekc.

Formalization of gene regulation knowledge using ontologies and gene ontology causal activity models.

Gene regulation computational research requires handling and integrating large amounts of heterogeneous data. The Gene Ontology has demonstrated that ontologies play a fundamental role in biological data interoperability and integration. Ontologies help to express data and knowledge in a machine processable way, which enables complex querying and advanced exploitation of distributed data.

Analysis of readability and structural accuracy in SNOMED CT.

Background: The increasing adoption of ontologies in biomedical research and the growing number of ontologies available have made it necessary to assure the quality of these resources. Most of the well-established ontologies, such as the Gene Ontology or SNOMED CT, have their own quality assurance processes. These have demonstrated their usefulness for the maintenance of the resources but are unable to detect all of the modelling flaws in the ontologies.

CLIN-IK-LINKS: A platform for the design and execution of clinical data transformation and reasoning workflows.

Background And Objective: Effective sharing and reuse of Electronic Health Records (EHR) requires technological solutions which deal with different representations and different models of data. This includes information models, domain models and, ideally, inference models, which enable clinical decision support based on a knowledge base and facts. Our goal is to develop a framework to support EHR interoperability based on transformation and reasoning services intended for clinical data and knowledge.

ColPortal, an integrative multiomic platform for analysing epigenetic interactions in colorectal cancer.

Colorectal cancer (CRC) is the third leading cause of cancer mortality worldwide. Different pathological pathways and molecular drivers have been described and some of the associated markers are used to select effective anti-neoplastic therapy. More recent evidence points to a causal role of microbiota and altered microRNA expression in CRC carcinogenesis, but their relationship with pathological drivers or molecular phenotypes is not clearly established.

Correction: Quorum sensing and stress-activated MAPK signaling repress yeast to hypha transition in the fission yeast Schizosaccharomyces japonicus.

[This corrects the article DOI: 10.1371/journal.pgen.

Quorum sensing and stress-activated MAPK signaling repress yeast to hypha transition in the fission yeast Schizosaccharomyces japonicus.

Quorum sensing (QS), a mechanism of microbial communication dependent on cell density, governs developmental decisions in many bacteria and in some pathogenic and non-pathogenic fungi including yeasts. In these simple eukaryotes this response is mediated by the release into the growth medium of quorum-sensing molecules (QSMs) whose concentration increases proportionally to the population density. To date the occurrence of QS is restricted to a few yeast species.

Towards the semantic enrichment of Computer Interpretable Guidelines: a method for the identification of relevant ontological terms.

Clinical Practice Guidelines (CPGs) contain recommendations intended to optimize patient care, produced based on a systematic review of evidence. In turn, Computer-Interpretable Guidelines (CIGs) are formalized versions of CPGs for use as decision-support systems. We consider the enrichment of the CIG by means of an OWL ontology that describes the clinical domain of the CIG, which could be exploited e.

Evaluation of ontology structural metrics based on public repository data.

The development and application of biological ontologies have increased significantly in recent years. These ontologies can be retrieved from different repositories, which do not provide much information about quality aspects of the ontologies. In the past years, some ontology structural metrics have been proposed, but their validity as measurement instrument has not been sufficiently studied to date.

From lexical regularities to axiomatic patterns for the quality assurance of biomedical terminologies and ontologies.

Ontologies and terminologies have been identified as key resources for the achievement of semantic interoperability in biomedical domains. The development of ontologies is performed as a joint work by domain experts and knowledge engineers. The maintenance and auditing of these resources is also the responsibility of such experts, and this is usually a time-consuming, mostly manual task.

Lost in translation: bioinformatic analysis of variations affecting the translation initiation codon in the human genome.

Motivation: Translation is a key biological process controlled in eukaryotes by the initiation AUG codon. Variations affecting this codon may have pathological consequences by disturbing the correct initiation of translation. Unfortunately, there is no systematic study describing these variations in the human genome.

Gearing up to handle the mosaic nature of life in the quest for orthologs.

The Quest for Orthologs (QfO) is an open collaboration framework for experts in comparative phylogenomics and related research areas who have an interest in highly accurate orthology predictions and their applications. We here report highlights and discussion points from the QfO meeting 2015 held in Barcelona. Achievements in recent years have established a basis to support developments for improved orthology prediction and to explore new approaches.

Analysis and visualization of disease courses in a semantically-enabled cancer registry.

Background: Regional and epidemiological cancer registries are important for cancer research and the quality management of cancer treatment. Many technological solutions are available to collect and analyse data for cancer registries nowadays. However, the lack of a well-defined common semantic model is a problem when user-defined analyses and data linking to external resources are required.

Preliminary Analysis of the OBO Foundry Ontologies and Their Evolution Using OQuaRE.

The biomedical community has now developed a significant number of ontologies. The curation of biomedical ontologies is a complex task as they evolve rapidly, being new versions regularly published. Therefore, methods to support ontology developers in analysing and tracking the evolution of their ontologies are needed.

Combining Archetypes, Ontologies and Formalization Enables Automated Computation of Quality Indicators.

ArchMS is a framework that represents clinical information and knowledge using ontologies in OWL, which facilitates semantic interoperability and thereby the exploitation and secondary use of clinical data. However, it does not yet support the automated assessment of quality of care. CLIF is a stepwise method to formalize quality indicators.

A platform for exploration into chaining of web services for clinical data transformation and reasoning.

The heterogeneity of clinical data is a key problem in the sharing and reuse of Electronic Health Record (EHR) data. We approach this problem through the combined use of EHR standards and semantic web technologies, concretely by means of clinical data transformation applications that convert EHR data in proprietary format, first into clinical information models based on archetypes, and then into RDF/OWL extracts which can be used for automated reasoning. In this paper we describe a proof-of-concept platform to facilitate the (re)configuration of such clinical data transformation applications.