Influenza Research Database: An integrated bioinformatics resource for influenza virus research

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.National Institutes of Health/National Institute for Allergy and Infectious Diseases [HHSN272201400028C]. Funding for open access charge: J. Craig Venter Institute

The RICORDO approach to semantic interoperability for biomedical data and models: strategy, standards and solutions.

BACKGROUND: The practice and research of medicine generates considerable quantities of data and model resources (DMRs). Although in principle biomedical resources are re-usable, in practice few can currently be shared. In particular, the clinical communities in physiology and pharmacology research, as well as medical education, (i.e. PPME communities) are facing considerable operational and technical obstacles in sharing data and models. FINDINGS: We outline the efforts of the PPME communities to achieve automated semantic interoperability for clinical resource documentation in collaboration with the RICORDO project. Current community practices in resource documentation and knowledge management are overviewed. Furthermore, requirements and improvements sought by the PPME communities to current documentation practices are discussed. The RICORDO plan and effort in creating a representational framework and associated open software toolkit for the automated management of PPME metadata resources is also described. CONCLUSIONS: RICORDO is providing the PPME community with tools to effect, share and reason over clinical resource annotations. This work is contributing to the semantic interoperability of DMRs through ontology-based annotation by (i) supporting more effective navigation and re-use of clinical DMRs, as well as (ii) sustaining interoperability operations based on the criterion of biological similarity. Operations facilitated by RICORDO will range from automated dataset matching to model merging and managing complex simulation workflows. In effect, RICORDO is contributing to community standards for resource sharing and interoperability.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain

<p>Abstract</p> <p>Background</p> <p>Skeletal dysplasias are a rare and heterogeneous group of genetic disorders affecting skeletal development. Patients with skeletal dysplasias suffer from many complex medical issues including degenerative joint disease and neurological complications. Because the data and expertise associated with this field is both sparse and disparate, significant benefits will potentially accrue from the availability of an ontology that provides a shared conceptualisation of the domain knowledge and enables data integration, cross-referencing and advanced reasoning across the relevant but distributed data sources.</p> <p>Results</p> <p>We introduce the design considerations and implementation details of the Bone Dysplasia Ontology. We also describe the different components of the ontology, including a comprehensive and formal representation of the skeletal dysplasia domain as well as the related genotypes and phenotypes. We then briefly describe SKELETOME, a community-driven knowledge curation platform that is underpinned by the Bone Dysplasia Ontology. SKELETOME enables domain experts to use, refine and extend and apply the ontology without any prior ontology engineering experience--to advance the body of knowledge in the skeletal dysplasia field.</p> <p>Conclusions</p> <p>The Bone Dysplasia Ontology represents the most comprehensive structured knowledge source for the skeletal dysplasias domain. It provides the means for integrating and annotating clinical and research data, not only at the generic domain knowledge level, but also at the level of individual patient case studies. It enables links between individual cases and publicly available genotype and phenotype resources based on a community-driven curation process that ensures a shared conceptualisation of the domain knowledge and its continuous incremental evolution.</p

Thoracic cord compression caused by disk herniation in Scheuermann’s disease: A case report and review of the literature

We present the case of a 14-year-old male with Scheuermann’s disease and significant neurological deficit due to thoracic disk herniation at the apex of kyphosis. He was treated with an anterior decompression, anterior and posterior fusion in the same setting using plate, cage and a segmental instrumentation system. The patient had an excellent outcome with complete neurological recovery

A Weakened Transcriptional Enhancer Yields Variegated Gene Expression

Identical genes in the same cellular environment are sometimes expressed differently. In some cases, including the immunoglobulin heavy chain (IgH) locus, this type of differential gene expression has been related to the absence of a transcriptional enhancer. To gain additional information on the role of the IgH enhancer, we examined expression driven by enhancers that were merely weakened, rather than fully deleted, using both mutations and insulators to impair enhancer activity. For this purpose we used a LoxP/Cre system to place a reporter gene at the same genomic site of a stable cell line. Whereas expression of the reporter gene was uniformly high in the presence of the normal, uninsulated enhancer and undetectable in its absence, weakened enhancers yielded variegated expression of the reporter gene; i.e., the average level of expression of the same gene differed in different clones, and expression varied significantly among cells within individual clones. These results indicate that the weakened enhancer allows the reporter gene to exist in at least two states. Subtle aspects of the variegation suggest that the IgH enhancer decreases the average duration (half-life) of the silent state. This analysis has also tested the conventional wisdom that enhancer activity is independent of distance and orientation. Thus, our analysis of mutant (truncated) forms of the IgH enhancer revealed that the 250 bp core enhancer was active in its normal position, ∼1.4 kb 3′ of the promoter, but inactive ∼6 kb 3′, indicating that the activity of the core enhancer was distance-dependent. A longer segment – the core enhancer plus ∼1 kb of 3′ flanking material, including the 3′ matrix attachment region – was active, and the activity of this longer segment was orientation-dependent. Our data suggest that this 3′ flank includes binding sites for at least two activators

Standardized metadata for human pathogen/vector genomic sequences

High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium's minimal information (MIxS) and NCBI's BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant

Human BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas construction and usage

\ua9 The Author(s) 2025. The Human BioMolecular Atlas Program (HuBMAP) aims to construct a 3D Human Reference Atlas (HRA) of the healthy adult body. Experts from 20+ consortia collaborate to develop a Common Coordinate Framework (CCF), knowledge graphs and tools that describe the multiscale structure of the human body (from organs and tissues down to cells, genes and biomarkers) and to use the HRA to characterize changes that occur with aging, disease and other perturbations. HRA v.2.0 covers 4,499 unique anatomical structures, 1,195 cell types and 2,089 biomarkers (such as genes, proteins and lipids) from 33 ASCT+B tables and 65 3D Reference Objects linked to ontologies. New experimental data can be mapped into the HRA using (1) cell type annotation tools (for example, Azimuth), (2) validated antibody panels or (3) by registering tissue data spatially. This paper describes HRA user stories, terminology, data formats, ontology validation, unified analysis workflows, user interfaces, instructional materials, application programming interfaces, flexible hybrid cloud infrastructure and previews atlas usage applications

Visualisation and characterisation of mononuclear phagocytes in the chicken respiratory tract using CSF1R-transgenic chickens

Additional file 2. Location of B cells, T cells and follicular dendritic cells (FDC) in the lung of MacReporter chickens. The BALT region of 5 to 7 week old non-vaccination animals were analysed for B, T and FCD cells. Isotype controls were used to standardise the microscope and examine aspecific binding before acquiring images (A-B). The GC of MacReporter animals are tightly packed with Bu1-CSF1R-eGFP+ FDC cells and Bu1+CSF1R-eGFP- B cells (C) with few Bu1+ B cells found in the parabronchi (F). CD3+ T cells are disperse within and outside the GC (D) and parabronchi (G). CSF1R-eGFP+ FDC cells express Fc receptors and trap immunoglobulin by expressing IgY (E) and CSF1R-eGFP+ IgY+ FDC are rarely detected out with the GC, BALT region of the lung. GC are indicated by white dashed lines