Molecular defects in primary ciliary dyskinesia are associated with agenesis of the frontal and sphenoid paranasal sinuses and chronic rhinosinusitis.

Primary ciliary dyskinesia (PCD; MIM 242650) is a rare genetic disorder characterized by malfunction of the motile cilia resulting in reduced mucociliary clearance of the airways. Together with recurring infections of the lower respiratory tract, chronic rhinosinusitis (CRS) is a hallmark symptom of PCD. Data on genotype-phenotype correlations in the upper airways are scarce.

A Temporal Graph Model to Predict Chemical Transformations in Complex Dissolved Organic Matter.

Dissolved organic matter (DOM) is a complex mixture of thousands of natural molecules that undergo constant transformation in the environment, such as sunlight induced photochemical reactions. Despite molecular level resolution from ultrahigh resolution mass spectrometry (UHRMS), trends of mass peak intensities are currently the only way to follow photochemically induced molecular changes in DOM. Many real-world relationships and temporal processes can be intuitively modeled using graph data structures (networks).

Evolution of biomedical ontologies and mappings: Overview of recent approaches.

Biomedical ontologies are heavily used to annotate data, and different ontologies are often interlinked by ontology mappings. These ontology-based mappings and annotations are used in many applications and analysis tasks. Since biomedical ontologies are continuously updated dependent artifacts can become outdated and need to undergo evolution as well.

Region Evolution eXplorer - A tool for discovering evolution trends in ontology regions.

Background: A large number of life science ontologies has been developed to support different application scenarios such as gene annotation or functional analysis. The continuous accumulation of new insights and knowledge affects specific portions in ontologies and thus leads to their adaptation. Therefore, it is valuable to study which ontology parts have been extensively modified or remained unchanged.

A multi-part matching strategy for mapping LOINC with laboratory terminologies.

Objective: To address the problem of mapping local laboratory terminologies to Logical Observation Identifiers Names and Codes (LOINC). To study different ontology matching algorithms and investigate how the probability of term combinations in LOINC helps to increase match quality and reduce manual effort.

Materials And Methods: We proposed two matching strategies: full name and multi-part.

Impact of ontology evolution on functional analyses.

Motivation: Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings.

COnto-Diff: generation of complex evolution mappings for life science ontologies.

Life science ontologies evolve frequently to meet new requirements or to better reflect the current domain knowledge. The development and adaptation of large and complex ontologies is typically performed collaboratively by several curators. To effectively manage the evolution of ontologies it is essential to identify the difference (Diff) between ontology versions.

CODEX: exploration of semantic changes between ontology versions.

Life science ontologies substantially change over time to meet the requirements of their users and to include the newest domain knowledge. Thus, an important task is to know what has been modified between two versions of an ontology (diff). This diff should contain all performed changes as compact and understandable as possible.

GOMMA: a component-based infrastructure for managing and analyzing life science ontologies and their evolution.

Background: Ontologies are increasingly used to structure and semantically describe entities of domains, such as genes and proteins in life sciences. Their increasing size and the high frequency of updates resulting in a large set of ontology versions necessitates efficient management and analysis of this data.

Results: We present GOMMA, a generic infrastructure for managing and analyzing life science ontologies and their evolution.

OnEX: Exploring changes in life science ontologies.

Background: Numerous ontologies have recently been developed in life sciences to support a consistent annotation of biological objects, such as genes or proteins. These ontologies underlie continuous changes which can impact existing annotations. Therefore, it is valuable for users of ontologies to study the stability of ontologies and to see how many and what kind of ontology changes occurred.