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Results for “data integration”

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PubMed1990

Integrity of small data bases in computer analysis of dietary data.

The integrity of data bases to support microcomputer-based dietary analysis programs has become increasingly important to developers and users of nutritional analysis software. This paper reviews critical issues in maintaining data integrity during development of small nutritional data bases. Because a limited number of large, source data bases provides the data for smaller, special-purpose data bases, this review initially focuses on factors that affect the quality and precision of methodologies used in establishing large data bases. Issues discussed are accuracy of source data as determined by analytical methodology and imputation procedures, and methods for insuring representativeness of data. The effect of data transfer procedures on small data base integrity are discussed, including use of multiple sources and standardization of naming and coding conventions. Also reviewed are procedures for selecting reduced numbers of foods and nutrients without sacrificing accuracy of analysis, and methods currently in use for validating small data bases.

Databases, Factual↗
PubMed2025

Oncopacket: integration of cancer research data using GA4GH phenopackets.

SUMMARY: Lack of data integration remains a significant impediment to cancer research, and many analyses still require customized software to transform and prepare cancer data. We describe a software package to harmonize genetic and clinical cancer data into the GA4GH Phenopacket schema, an ISO standard for representing clinical case data. We integrated demographic, mutation, morphology, diagnosis, intervention, and survival data using case data from the National Cancer Institute for 12 cancer types. The Phenopacket standard provides a foundation for downstream use, including sophisticated statistical and AI/ML analyses. We demonstrate fitness for purpose by using the integrated data to recapitulate a known association between mutations in the gene encoding isocitrate dehydrogenase 1 and survival time in brain cancer patients. AVAILABILITY AND IMPLEMENTATION: Source code is freely available at: https://github.com/monarch-initiative/oncopacket (archived at 10.5281/zenodo.15353125).

Humans↗
PubMed2025

JASMINE: A powerful representation learning method for enhanced analysis of incomplete multi-omics data.

Integrative analysis of multi-omics data provides a more comprehensive and nuanced view of a subject's biological state. However, high-dimensionality and ubiquitous modality missingness present significant analytical challenges. Existing methods for incomplete multi-omics data are scarce, do not fully leverage both modality-specific and shared information, and produce task-biased representations. We propose JASMINE, a self-supervised representation learning method for incomplete multi-omics data that preserves both modality-specific and joint information and enhances sample similarity structure. JASMINE produces embeddings that achieve superior performance across multiple tasks for two different incomplete multi-omics datasets while requiring only a single round of training per dataset.

missing data↗
PubMed2026

Investing in Canada's nursing workforce: a comprehensive review to inform policy innovations and directions.

BACKGROUND: Health systems worldwide face persistent health workers challenges including nursing shortages, workforce strain, and inequities. In Canada, these challenges have prompted renewed national and provincial reforms to strengthen recruitment, retention, leadership, and sustainability. This paper compares nursing workforce policy directions across Canada, and international jurisdictions to inform policy and planning. METHODS: A cross-country comparative analysis of policies building on a comprehensive national funded review that included an umbrella review of 69 systematic reviews, a comparative policy review of nursing workforce strategies in five jurisdictions, and validation through national horizon-scanning and policy dialogues (n >100). Evidence was analyzed across system, organizational, and individual levels. RESULTS: At the system level, international jurisdictions demonstrate comprehensive, legislated approaches integrating data, governance, and multi-year funding have advanced key nursing strategies. In Canada, the advances show the importance of strategies to have national and provincial/territorial alignment emphasizing leadership, flexibility, and inclusion as key levers. Organizational and individual-level reforms such as mentorship, leadership development, and wellness initiatives are expanding but remain variably evaluated. Experts identified national workforce data strategies and policy integration with embedded evaluation as key enablers to inform scalability and sustainability of implemented strategies. CONCLUSIONS: Canada's nursing workforce reforms are advancing toward coordinated, equity-driven, and evidence-informed strategies. Continued investment in evaluation, leadership, and national integrated data systems along with integrating nursing workforce planning within broader intersectoral planning will consolidate these gains and position Canada as an international leader in sustainable nursing workforce policy.

Canada↗
PubMed1991

Providing an integrated clinical data view in a hospital information system that manages multimedia data.

The VA's hospital information system, the Decentralized Hospital Computer Program (DHCP), is an integrated system based on a powerful set of software tools with shared data accessible from any of its application modules. It includes many functionally specific application subsystems such as laboratory, pharmacy, radiology, and dietetics. Physicians need applications that cross these application boundaries to provide useful and convenient patient data. One of these multi-specialty applications, the DHCP Imaging System, integrates multimedia data to provide clinicians with comprehensive patient-oriented information. User requirements for cross-disciplinary image access can be studied to define needs for similar text data access. Integration approaches must be evaluated both for their ability to deliver patient-oriented text data rapidly and their ability to integrate multimedia data objects. Several potential integration approaches are described as they relate to the DHCP Imaging System.

Computer Communication Networks↗
PubMed1995

Data integrity-conduct of clinical investigations: university investigator perspective.

Clinical investigations are studies designed to evaluate the effectiveness of a new animal drug. Expectations for documentation of events occurring during clinical investigations have been greatly increased. The Food and Drug Administration (FDA) through its Center for Veterinary Medicine (CVM) division recently issued a guideline to address the responsibilities (under 21 CFR 511.1 and 512[j] of the Federal, Food, Drug and Cosmetic Act) of investigators who conduct clinical investigations of new animal drugs and of monitors of these investigations. The guideline is part of a continuing effort by FDA/CVM to propose data integrity initiatives that will continue to assure the reliability and accuracy of the data upon which decisions to approve new animal drugs are based. In addition to the increased documentation, FDA/CVM intends to make real-time inspection of clinical investigations a routine practice. In response to these changes; those involved with clinical investigations will need to make appropriate adjustments. The purpose of this review is to provide additional notification to clinical investigators of the changes in their responsibilities under the new guideline and to provide an investigator perspective of how these changes might impact research efforts.

Animals↗
PubMed2026

AI-Based 3D Heterogeneous Network Model for Functional Prediction of Epigenetics.

Human biology and diseases are the result of constantly evolving processes within an intricately complex molecular network of interactions, such as epigenetic regulation. Epigenetics refers to heritable changes in gene expression that occur without alterations to the underlying DNA sequence. These changes, driven by mechanisms such as DNA methylation, histone modifications, and noncoding RNAs, play critical roles in regulating chromatin structure and gene activity. Epigenetic regulation offers valuable insights into biological systems, and when integrated with sophisticated analyses, it enables us to gain insights into gene regulation and cellular behavior. Here, we describe an artificial intelligence (AI)-based model that is capable of generating 3-dimensional (3D) heterogeneous network by integrating multimodal data for the functional prediction of epigenetic mechanisms, emphasizing its applications in medicine, developmental biology, and personalized therapeutics. Heterogeneous networks in biology are powerful tools for understanding the complex interactions and interdependencies within biological systems. Key advancements in AI and multiomics data integration have propelled this field, offering new insights into disease mechanisms, biomarker discovery, and therapeutic interventions.

Epigenesis, Genetic↗
PubMed1991

[Experiences with a Token Ring Network in blood bank administration of the Hannover medical university].

The Token Ring Network is a Local Area Network of IBM. It is a very helpful tool for modulating working processes by personal computers. The Token Ring is a network of the third generation and constructed like a star net. The blood bank of the Medical University of Hannover (MHH) is using the Token Ring for the administration of blood storage and donors. Medical data of foreign laboratories are transmitted into the blood bank computer. During the last year, we had no difficulties working with this software tool in response time and data security and it seemed to us a very cheap opportunity for data integration and data collection on decentralized systems.

Blood Banks↗
PubMed2025

scMGCL: accurate and efficient integration representation of single-cell multi-omics data.

MOTIVATION: Single-cell multi-omics data integration is essential for understanding cellular states and disease mechanisms, yet integrating heterogeneous data modalities remains a challenge. We present scMGCL, a graph contrastive learning framework for robust integration of single-cell ATAC-seq and RNA-seq data. Our approach leverages self-supervised learning on cell-cell similarity graphs, in which each modality's graph structure serves as an augmentation for the other. This cross-modality contrastive paradigm enables the learning of biologically meaningful, shared representations while preserving modality-specific features. RESULTS: Benchmarking against state-of-the-art methods demonstrates that scMGCL outperforms others in cell-type clustering, label transfer accuracy, and preservation of marker-gene correlations. Additionally, scMGCL significantly improves computational efficiency, reducing runtime and memory usage. The method's effectiveness is further validated through extensive analyses of cell-type similarity and functional consistency, providing a powerful tool for multi-omics data exploration. AVAILABILITY AND IMPLEMENTATION: Code and datasets are released at https://github.com/zlCreator/scMGCL.

Single-Cell Analysis↗
PubMed2026

The ASH HematOmics Program supports integrative analysis of genomic and clinical data in hematologic diseases.

The increasing availability of genomic and transcriptomic sequencing has uncovered diverse genomic alterations and distinct gene expression profiles driving hematologic diseases, yet a data integration and sharing platform dedicated to hematology remains lacking. We developed the American Society of Hematology (ASH) HematOmics Program (ASHOP; ashop.hematology.org), a resource for exploring somatic alterations and gene fusions, transcriptomic results, and clinical data from 5960 patients spanning B-cell precursor and T-cell acute lymphoblastic leukemia, acute myeloid leukemia, myelodysplastic syndromes, and chronic lymphocytic leukemia. Users can explore genomic alteration landscapes and comutation patterns via lollipop and matrix plots and analyze significantly altered genes in user-defined subcohorts. Transcriptomes can be explored through interactive uniform manifold approximation and projections, clustering, differential expression, and pathway enrichment. Genomic, transcriptomic features, and clinical outcomes can be correlated in a user-driven manner or combined to precisely define study cohorts. We illustrate the following 4 use cases of ASHOP: (1) stratification of DUX4-rearranged B-cell leukemias into Early/Multipotent and Committed subgroups with distinct outcomes, (2) characterization of HOXA/HOXB expression patterns in acute myeloid leukemias, (3) correlating mutational burden with mismatch repair deficiency and mutational signatures, and (4) investigation of TP53 alteration landscape. ASHOP is an open-access resource to inform genomic and transcriptomic data interpretation for hematologic malignancies and will expand to support additional diseases and data modalities from the ASH community.

Humans↗
PubMed1975

A profile for managing sensory integrative test data.

A concise method for compiling a data profile from a general sensory integrative test battery has been presented. Subtests from each test used were categorized according to the sensory integrative and motor functions being tested. These categories have been defined and include: tactile-kinesthetic perception, visual perception-figure ground, visual perception-constancy, ocular control, gross motor control, fine motor control, integration of function-two sides of the body, orientation in space, body awareness, and auditory discrimination. A method for converting the various scores into descriptive terminology is provided in which the test results are reported as above age expectancy, appropriate for age, somewhat deficient for age, and markedly deficient for age. The clinical implications of the technique are discussed.

Auditory Perception↗