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Objective:To establish a IgA nephropathy (IgAN) standard dataset for the structured and standardization of IgAN clinical information, which will be beneficial to the integration and utilization of clinical information among different medical institutions. Therefore, the IgAN Expert Collaboration Group composed the "IgA Nephropathy Standard Dataset".Methods:Referring to the domestic information standards, guidelines, data standard and consensus of related fields, based on electronic medical history, the patient identification number was used as the primary key of the system to collect information. By standardizing each data element in the data set, the standardization of the management system in data and information exchange, data collaboration and sharing was ensured, and a quality control system was developed.Results:This standard dataset included 607 data elements and 8 business domains, which were patient information, medical history information, physical examination, laboratory examination, assistant examination, renal pathology, drug treatment, and follow-up, respectively. Each module was composed of module name, data element name, English name, definition, range, reference standard, etc. At the same time, a corresponding quality control system was formulated to evaluate data quality from multiple dimensions such as completeness, standardization, accuracy, timeliness, and security for ensuring the high quality and security of the data.Conclusion:The IgAN standard dataset is established, which will contribute to the structuration and standardization of clinical information of IgAN patients.
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Este estudo aborda o tema de sistemas de informação utilizados na gestão de recursos humanos em saúde na Secretaria de Estado de Saúde do Rio de Janeiro (SES/RJ), órgão da Administração Direta do Poder Executivo do Estado. A SES/RJ é responsável por definir políticas de saúde no Estado, a qual utiliza vários sistemas de informação para gestão de sua força de trabalho, com evidências de fragmentação dos dados, dificuldade na gestão das informações e prejuízo na definição de estratégias. Nesse sentido, este trabalho tem como objetivo descrever os sistemas de informação de recursos humanos em uso na SES/RJ, no contexto dos modelos de gestão adotados em suas unidades de saúde, e contribuir para melhorar a gestão de recursos humanos e das informações geradas no âmbito da instituição, fornecendo subsídios para o processo de tomada de decisão. Para tanto, fez-se, primeiramente, uma revisão bibliográfica sobre o tema desde o ano de 1995, período da Reforma do Estado, e uma pesquisa documental em portais e legislações, tanto da SES/RJ como de outros órgãos estaduais, assim como das esferas federal e municipal. Em seguida, o trabalho discute as possibilidades e os subsídios que possam favorecer a interoperabilidade desses sistemas e, assim, facilitar a gestão da força de trabalho na instituição.
This study investigates the use of information systems in the administration of human resources in health at the Rio de Janeiro State Department of Health (SES/RJ), which is part of the Direct Administration of the State Government. SES/RJ oversees establishing state health policies and managing its staff using a variety of information systems, with evidence of data fragmentation, information management challenges, and strategy development impairment. In this sense, this study aims to describe the human resources information systems in use at SES/RJ in relation to the management models used in its health units, as well as to contribute to improving human resources management and the information generated within the institution by providing decision-making inputs. To that end, we conducted a bibliographic review of the topic dating back to 1995, during the State Reform period, as well as document search in the portals and legislation of SES/RJ and other state agencies, as well as federal and municipal domains. The study then moves on to the possibilities and advantages that may encourage system interoperability and, as a result, make labor management in the institution easier.
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Personnel Management , Information Systems , Public Health , Electronic Health Records , Health Workforce , BrazilABSTRACT
The emergence of single-cell sequencing technology enables people to observe cells with unprecedented precision. However, it is difficult to capture the information on all cells and genes in one single-cell RNA sequencing (scRNA-seq) experiment. Single-cell data of a single modality cannot explain cell state and system changes in detail. The integrative analysis of single-cell data aims to address these two types of problems. Integrating multiple scRNA-seq data can collect complete cell types and provide a powerful boost for the construction of cell atlases. Integrating single-cell multimodal data can be used to study the causal relationship and gene regulation mechanism across modalities. The development and application of data integration methods helps fully explore the richness and relevance of single-cell data and discover meaningful biological changes. Based on this, this article reviews the basic principles, methods and applications of multiple scRNA-seq data integration and single-cell multimodal data integration. Moreover, the advantages and disadvantages of existing methods are discussed. Finally, the future development is prospected.
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Humans , Base Sequence , Gene Expression Profiling , Gene Expression Regulation , Sequence Analysis, RNA , Single-Cell AnalysisABSTRACT
Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells. A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations. To address this issue, we present the first web-based application, consensus cancer driver gene caller (C), to identify the consensus driver genes using six different complementary strategies, i.e., frequency-based, machine learning-based, functional bias-based, clustering-based, statistics model-based, and network-based strategies. This application allows users to specify customized operations when calling driver genes, and provides solid statistical evaluations and interpretable visualizations on the integration results. C is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c3.
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The era of medical big data,translational medicine and precision medicine brings new opportunities for the study of etiology of chronic complex diseases.How to implement evidence-based medicine,translational medicine and precision medicine are the challenges we are facing.Systems epidemiology,a new field of epidemiology,combines medical big data with system biology and examines the statistical model of disease risk,the future risk simulation and prediction using the data at molecular,cellular,population,social and ecological levels.Due to the diversity and complexity of big data sources,the development of study design and analytic methods of systems epidemiology face new challenges and opportunities.This paper summarizes the theoretical basis,concept,objectives,significances,research design and analytic methods of systems epidemiology and its application in the field of public health.
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From the perspectives like connotation,characteristics,design idea and realization path,the paper expounds on design of interdisciplinary knowledge service application;taking environmental health field as an example,it introduces the design and development of interdisciplinary knowledge service system function,summarizes the existing problems based on the application effect and puts forward corresponding suggestions.
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The era of medical big data,translational medicine and precision medicine brings new opportunities for the study of etiology of chronic complex diseases.How to implement evidence-based medicine,translational medicine and precision medicine are the challenges we are facing.Systems epidemiology,a new field of epidemiology,combines medical big data with system biology and examines the statistical model of disease risk,the future risk simulation and prediction using the data at molecular,cellular,population,social and ecological levels.Due to the diversity and complexity of big data sources,the development of study design and analytic methods of systems epidemiology face new challenges and opportunities.This paper summarizes the theoretical basis,concept,objectives,significances,research design and analytic methods of systems epidemiology and its application in the field of public health.
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The paper analyzes the current situation of integration in healthcare industry and the difficulties in the construction of healthcare big data platform,proposes the construction of healthcare big data platform by Cloud P2P network,and the platform framework including the five layers of resource layer,sense/access layer,transfer layer,service layer and application layer.
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High-throughput metabolomics have developed very rapidly in recent years and been widely used in medicinal plants research .At present ,high-throughput metabolomics mainly applied in the following areas ,quality control of medicinal plants by fingerprints ,metabolites difference comparison before and after genetic engineering ,monitoring metabolites change in different environment and gene function study .High-throughput metabolomics have a great future ,but still have some challen-ges ,such as the requirements for more sophisticated equipment and complexity of data integration .With the advancement of science and technology ,high-throughput metabolomics will be an irreplaceable tool for the research of medicinal plants .
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Since it is one of the hotspots to discover the new knowledge in life science in data-intensive scientific discovery by integrating the biomedical literature and scientific data that can provide an open environment for their interactive operation , the mining of foreign and domestic biomedical literature and integration of scientific data were analyzed , the corresponding systems for different integration methods were investigated , the development trend in biomedical literature and scientific data integration was predicted .
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Based on analyzing the problems existed in hostital informatization, the paper proposes using shared-database to realize data sharing among various departments.It mainly introduces shared-database and its function module and customer display module. The introduction of shared-database is conducive to comprehensive management of hospital data, providing basis for future data mining.
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This study was aimed to discuss possible problems in the data collection process of traditional Chinese medicine (TCM) clinical medicine and to propose appropriate solutions. Based on analysis of clinical data features and data collection demands among 20 TCM clinical research bases, reference were made on key technologies of the Electronic Medical Records' integration and sharing, to propose the solution of TCM clinical data collection. The re-sults showed that proposing the metadata and data entities synchronized intersecting strategy, analyzing key points on this strategy, and proposing appropriate solutions, found the technical processes of the TCM clinical data collec-tion. It was concluded that the analysis and solution on key points of TCM clinical data collection provided the basis and the reference to data collection issues of TCM clinical research base.
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Cancer control researchers seek to reduce the burden of cancer by studying interventions, their impact on defined populations, and the means by which they can be better used. The first step in cancer control is identifying where the cancer burden is elevated, which suggests locations where interventions are needed. Geographic information systems (GIS) and other spatial analytic methods provide such a solution and thus can play a major role in cancer control. The purpose of this article is to examine the impact of GIS on the direction of cancer research. It will consider the application of GIS techniques to research in cancer etiology.
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Epidemiologic Research Design , Geographic Information Systems , Humans , Neoplasms/diagnosis , Neoplasms/epidemiologyABSTRACT
Gene Expression Omnibus (GEO) has kept the largest amount of gene-expression microarray data that have grown exponentially. Microarray data in GEO have been generated in many different formats and often lack standardized annotation and documentation. It is hard to know if preprocessing has been applied to a dataset or not and in what way. Standard-based integration of heterogeneous data formats and metadata is necessary for comprehensive data query, analysis and mining. We attempted to integrate the heterogeneous microarray data in GEO based on Minimum Information About a Microarray Experiment (MIAME) standard. We unified the data fields of GEO Data table and mapped the attributes of GEO metadata into MIAME elements. We also discriminated non-preprocessed raw datasets from others and processed ones by using a two-step classification method. Most of the procedures were developed as semi-automated algorithms with some degree of text mining techniques. We localized 2,967 Platforms, 4,867 Series and 103,590 Samples with covering 279 organisms, integrated them into a standard-based relational schema and developed a comprehensive query interface to extract. Our tool, GEOQuest is available at http://www.snubi.org/software/GEOQuest/
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Data Mining , DNA , Gene Expression , Mining , Oligonucleotide Array Sequence AnalysisABSTRACT
In this paper we review the impact that the availability of the Schistosoma mansoni genome sequence and annotation has had on schistosomiasis research. Easy access to the genomic information is important and several types of data are currently being integrated, such as proteomics, microarray and polymorphic loci. Access to the genome annotation and powerful means of extracting information are major resources to the research community.
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Animals , Databases, Genetic , Genomics , Genome, Helminth , Schistosoma mansoni , ResearchABSTRACT
Obiective To expand the functions of the original data integration platform combined business process to achieve cross-system integration in hospital, Methods On the basis of efficient data interaction for every medical information system in hospital, more related function modules for the DIP were added. Results The new function modules can satisfy DIP multiple needs in the hospital daily work and make the DIP more powerful. Conclusion The applicability and rationality of DIP are improved by extended function.
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OBJECTIVES: Nowadays, as the amounts of biological data are rapidly increasing, bioinformatics has become one of the important research issues. The bioinformatics data sources are, however, distributed and heterogeneous, and therefore, often poorly integrated and difficult to use together. As many bioinformatics analyses need to make use of multiple information sources, the problem of integration of bioinformatics data sources has become an important one. The purpose of this paper is to present an integration system for bioinformatics data sources. METHODS: To solve this problem, we present an integration system for bioinformatics data sources using a global MDR, which provides users with efficiency and convenience as if they use one system. We deal with the extraction of data elements for bioinformatics MDRs by using ISO 11179 mandatory attributes. RESULTS: A global bioinformatics MDR schema for given MDRs and the results of query processing are presented. CONCLUSIONS: The proposed system and concepts in this paper may be a good solution for the integration of diverse bioinformatics data sources.
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Computational Biology , Information Storage and RetrievalABSTRACT
Recently vegetation comparative analyses have been increasingly used to define vegetation types in Brazilian territory. To carry out these analyses, each study has elaborated its own database, which usually is discarded at the end of a research project. This practice means waste of time, money, personal effort and mainly information. Organising and centralising information in a database, which lasts for a long time is the best way to avoid effort overlapping and waste of money, besides providing opportunities for scientists in different areas to use and share information. FITOGEO was conceived to meet these requirements. It was developed to store and manage floristic, phytosociologic, associated environmental variables and taxonomic information. FITOGEO maintains data integrity. It is species centred and able to integrate data and metadata from several sources. This database system presents two interfaces: (1) the floristic/phytosociologic, presenting information from species lists including the species and the methods, and associated environmental variables, such geographic co-ordinate, altitude, temperature and precipitation; and (2) the taxonomic, presenting information related to the species, such as correct spelling, valid name and supraspecific hierarchic levels.
Análises comparativas vêm sendo cada vez mais utilizadas para definir e relacionar os tipos de vegetação existentes no Brasil. Para tanto, cada pesquisador vem montando seu próprio banco de dados, usualmente elaborando um sistema com uma finalidade imediata e descartado ao término do projeto ou pesquisa. Essa prática leva ao desperdício de tempo, esforço, dinheiro e, principalmente, informação. Então, um sistema de banco de dados específico para armazenar e gerenciar informações advindas de levantamentos florísticos e, ou, fitossociológicos poderia padronizar, estruturar logicamente, evitar ou eliminar sobreposição de esforços, reduzir os custos e também promover oportunidade para que cientistas de diversas áreas compartilhem informações. Com esses objetivos e para suprir uma necessidade imediata de organizar uma base de dados, foi desenvolvido o FITOGEO. O sistema foi elaborado com a finalidade de gerenciar informações oriundas de listas florísticas ou de levantamentos fitossociológicos, variáveis ambientais associadas a estas listas e taxonômicas. O FITOGEO mantém a integridade dos dados, é centrado na espécie e tem a capacidade de integrar dados e metadados de várias fontes. Apresenta duas interfaces: uma de características florísticas ou fitossociológicas, com todas as informações oriundas do levantamento em si, tanto das espécies quanto da metodologia adotada, e das variáveis ambientais associadas, como coordenadas geográficas, altitude, temperatura e precipitação. E outra taxonômica, resgatando informações como nome corrigido e o nome válido das espécies cadastradas e níveis hierárquicos supra-específicos.
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Objective To build a regional cooperative healthcare system in order to make the best use of the limited medical resources,reduce the cost,and improve the quality of medical treatment.Methods Data warehouse and virtual database were used to build regional data center and realize data integration of hospital information system.Upon this foundation,a web service integration of hospital information system based on SOA was realized.Results This design scheme realized the effective management and integration of huge information resources,and managed the medical workflow effectively.Conclusion This design scheme provides the regional cooperative healthcare system with the characteristics of modularization and expansibility.Hierarchy architecture enhances the stability of the system.