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Yazar M, Özbek P. In Silico Tools and Approaches for the Prediction of Functional and Structural Effects of Single-Nucleotide Polymorphisms on Proteins: An Expert Review. OMICS-A JOURNAL OF INTEGRATIVE BIOLOGY 2020; 25:23-37. [PMID: 33058752 DOI: 10.1089/omi.2020.0141] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Single-nucleotide polymorphisms (SNPs) are single-base variants that contribute to human biological variation and pathogenesis of many human diseases. Among all SNP types, nonsynonymous single-nucleotide polymorphisms (nsSNPs) can alter many structural, biochemical, and functional features of a protein such as folding characteristics, charge distribution, stability, dynamics, and interactions with other proteins/nucleotides. These modifications in the protein structure can lead nsSNPs to be closely associated with many multifactorial diseases such as cancer, diabetes, and neurodegenerative diseases. Predicting structural and functional effects of nsSNPs with experimental approaches can be time-consuming and costly; hence, computational prediction tools and algorithms are being widely and increasingly utilized in biology and medical research. This expert review examines the in silico tools and algorithms for the prediction of functional or structural effects of SNP variants, in addition to the description of the phenotypic effects of nsSNPs on protein structure, association between pathogenicity of variants, and functional or structural features of disease-associated variants. Finally, case studies investigating the functional and structural effects of nsSNPs on selected protein structures are highlighted. We conclude that creating a consistent workflow with a combination of in silico approaches or tools should be considered to increase the performance, accuracy, and precision of the biological and clinical predictions made in silico.
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Affiliation(s)
- Metin Yazar
- Department of Bioengineering, Marmara University, Göztepe, İstanbul, Turkey.,Department of Genetics and Bioengineering, Istanbul Okan University, Tuzla, Istanbul, Turkey
| | - Pemra Özbek
- Department of Bioengineering, Marmara University, Göztepe, İstanbul, Turkey
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Prioritization of Variants for Investigation of Genotype-Directed Nutrition in Human Superpopulations. Int J Mol Sci 2019; 20:ijms20143516. [PMID: 31323740 PMCID: PMC6678450 DOI: 10.3390/ijms20143516] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 07/04/2019] [Accepted: 07/16/2019] [Indexed: 01/06/2023] Open
Abstract
Dietary guidelines recommended by key health agencies are generally designed for a global population. However, ethnicity affects human disease and environment-gene interactions, including nutrient intake. Historically, isolated human populations with different genetic backgrounds have adapted to distinct environments with varying food sources. Ethnicity is relevant to the interaction of food intake with genes and disease susceptibility; yet major health agencies generally do not recommend food and nutrients codified by population genotypes and their frequencies. In this paper, we have consolidated published nutrigenetic variants and examine their frequencies in human superpopulations to prioritize these variants for future investigation of population-specific genotype-directed nutrition. The nutrients consumed by individuals interact with their genome and may alter disease risk. Herein, we searched the literature, designed a data model, and manually curated hundreds of papers. The resulting database houses 101 variants that reached significance (p < 0.05), from 35 population studies. Nutrigenetic variants associated with modified nutrient intake have the potential to reduce the risk of colorectal cancer, obesity, metabolic syndrome, type 2 diabetes, and several other diseases. Since many nutrigenetic studies have identified a major variant in some populations, we suggest that superpopulation-specific genotype-directed nutrition modifications be prioritized for future study and evaluation. Genotype-directed nutrition approaches to dietary modification have the potential to reduce disease risk in select human populations.
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Investigation of somatic single nucleotide variations in human endogenous retrovirus elements and their potential association with cancer. PLoS One 2019; 14:e0213770. [PMID: 30934003 PMCID: PMC6443178 DOI: 10.1371/journal.pone.0213770] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 02/28/2019] [Indexed: 11/19/2022] Open
Abstract
Human endogenous retroviruses (HERVs) have been investigated for potential links with human cancer. However, the distribution of somatic nucleotide variations in HERV elements has not been explored in detail. This study aims to identify HERV elements with an over-representation of somatic mutations (hot spots) in cancer patients. Four HERV elements with mutation hotspots were identified that overlap with exons of four human protein coding genes. These hotspots were identified based on the significant over-representation (p<8.62e-4) of non-synonymous single-nucleotide variations (nsSNVs). These genes are TNN (HERV-9/LTR12), OR4K15 (HERV-IP10F/LTR10F), ZNF99 (HERV-W/HERV17/LTR17), and KIR2DL1 (MST/MaLR). In an effort to identify mutations that effect survival, all nsSNVs were further evaluated and it was found that kidney cancer patients with mutation C2270G in ZNF99 have a significantly lower survival rate (hazard ratio = 2.6) compared to those without it. Among HERV elements in the human non-protein coding regions, we found 788 HERVs with significantly elevated numbers of somatic single-nucleotide variations (SNVs) (p<1.60e-5). From this category the top three HERV elements with significantly over-represented SNVs are HERV-H/LTR7, HERV-9/LTR12 and HERV-L/MLT2. Majority of the SNVs in these 788 HERV elements are located in three DNA functional groups: long non-coding RNAs (lncRNAs) (60%), introns (22.2%) and transcriptional factor binding sites (TFBS) (14.8%). This study provides a list of mutational hotspots in HERVs, which could potentially be used as biomarkers and therapeutic targets.
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Brown DK, Tastan Bishop Ö. HUMA: A platform for the analysis of genetic variation in humans. Hum Mutat 2018; 39:40-51. [PMID: 28967693 PMCID: PMC5722678 DOI: 10.1002/humu.23334] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Revised: 08/01/2017] [Accepted: 08/17/2017] [Indexed: 11/06/2022]
Abstract
The completion of the human genome project at the beginning of the 21st century, along with the rapid advancement of sequencing technologies thereafter, has resulted in exponential growth of biological data. In genetics, this has given rise to numerous variation databases, created to store and annotate the ever-expanding dataset of known mutations. Usually, these databases focus on variation at the sequence level. Few databases focus on the analysis of variation at the 3D level, that is, mapping, visualizing, and determining the effects of variation in protein structures. Additionally, these Web servers seldom incorporate tools to help analyze these data. Here, we present the Human Mutation Analysis (HUMA) Web server and database. HUMA integrates sequence, structure, variation, and disease data into a single, connected database. A user-friendly interface provides click-based data access and visualization, whereas a RESTful Web API provides programmatic access to the data. Tools have been integrated into HUMA to allow initial analyses to be carried out on the server. Furthermore, users can upload their private variation datasets, which are automatically mapped to public data and can be analyzed using the integrated tools. HUMA is freely accessible at https://huma.rubi.ru.ac.za.
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Affiliation(s)
- David K Brown
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown, South Africa
| | - Özlem Tastan Bishop
- Research Unit in Bioinformatics (RUBi), Department of Biochemistry and Microbiology, Rhodes University, Grahamstown, South Africa
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Schork NJ, Nazor K. Integrated Genomic Medicine: A Paradigm for Rare Diseases and Beyond. ADVANCES IN GENETICS 2017; 97:81-113. [PMID: 28838357 PMCID: PMC6383766 DOI: 10.1016/bs.adgen.2017.06.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Individualized medicine, or the tailoring of therapeutic interventions to a patient's unique genetic, biochemical, physiological, exposure and behavioral profile, has been enhanced, if not enabled, by modern biomedical technologies such as high-throughput DNA sequencing platforms, induced pluripotent stem cell assays, biomarker discovery protocols, imaging modalities, and wireless monitoring devices. Despite successes in the isolated use of these technologies, however, it is arguable that their combined and integrated use in focused studies of individual patients is the best way to not only tailor interventions for those patients, but also shed light on treatment strategies for patients with similar conditions. This is particularly true for individuals with rare diseases since, by definition, they will require study without recourse to other individuals, or at least without recourse to many other individuals. Such integration and focus will require new biomedical scientific paradigms and infrastructure, including the creation of databases harboring study results, the formation of dedicated multidisciplinary research teams and new training programs. We consider the motivation and potential for such integration, point out areas in need of improvement, and argue for greater emphasis on improving patient health via technological innovations, not merely improving the technologies themselves. We also argue that the paradigm described can, in theory, be extended to the study of individuals with more common diseases.
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Affiliation(s)
- Nicholas J. Schork
- The Translational Genomics Research Institute, 445 North Fifth Street, Phoenix, AZ 85004, , 858-794-4054
| | - Kristopher Nazor
- MYi Diagnostics and Discovery, 5310 Eastgate Mall, San Diego, CA 92121, , 858-458-9305
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Affiliation(s)
- Mohamed Helmy
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | | | - Gary D. Bader
- The Donnelly Centre, University of Toronto, Toronto, ON, Canada
- * E-mail:
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Yohe SL, Carter AB, Pfeifer JD, Crawford JM, Cushman-Vokoun A, Caughron S, Leonard DGB. Standards for Clinical Grade Genomic Databases. Arch Pathol Lab Med 2016; 139:1400-12. [PMID: 26516938 DOI: 10.5858/arpa.2014-0568-cp] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
CONTEXT Next-generation sequencing performed in a clinical environment must meet clinical standards, which requires reproducibility of all aspects of the testing. Clinical-grade genomic databases (CGGDs) are required to classify a variant and to assist in the professional interpretation of clinical next-generation sequencing. Applying quality laboratory standards to the reference databases used for sequence-variant interpretation presents a new challenge for validation and curation. OBJECTIVES To define CGGD and the categories of information contained in CGGDs and to frame recommendations for the structure and use of these databases in clinical patient care. DESIGN Members of the College of American Pathologists Personalized Health Care Committee reviewed the literature and existing state of genomic databases and developed a framework for guiding CGGD development in the future. RESULTS Clinical-grade genomic databases may provide different types of information. This work group defined 3 layers of information in CGGDs: clinical genomic variant repositories, genomic medical data repositories, and genomic medicine evidence databases. The layers are differentiated by the types of genomic and medical information contained and the utility in assisting with clinical interpretation of genomic variants. Clinical-grade genomic databases must meet specific standards regarding submission, curation, and retrieval of data, as well as the maintenance of privacy and security. CONCLUSION These organizing principles for CGGDs should serve as a foundation for future development of specific standards that support the use of such databases for patient care.
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Affiliation(s)
| | | | | | | | | | | | - Debra G B Leonard
- From the Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Minneapolis (Dr Yohe); the Department of Pathology and Laboratory Medicine and the Department of Biomedical Informatics, Emory University, Atlanta, Georgia (Dr Carter); the Department of Pathology, Washington University School of Medicine, St. Louis, Missouri (Dr Pfeifer); the Department of Pathology and Laboratory Medicine, Hofstra North Shore-Long Island Jewish School of Medicine, Hempstead, New York (Dr Crawford); the Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha (Dr Cushman-Vokoun); the MAWD Pathology Group, North Kansas City, Missouri (Dr Caughron); and the Department of Pathology and Laboratory Medicine, University of Vermont College of Medicine, Burlington (Dr Leonard)
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Wu TJ, Shamsaddini A, Pan Y, Smith K, Crichton DJ, Simonyan V, Mazumder R. A framework for organizing cancer-related variations from existing databases, publications and NGS data using a High-performance Integrated Virtual Environment (HIVE). DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau022. [PMID: 24667251 PMCID: PMC3965850 DOI: 10.1093/database/bau022] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Years of sequence feature curation by UniProtKB/Swiss-Prot, PIR-PSD, NCBI-CDD, RefSeq and other database biocurators has led to a rich repository of information on functional sites of genes and proteins. This information along with variation-related annotation can be used to scan human short sequence reads from next-generation sequencing (NGS) pipelines for presence of non-synonymous single-nucleotide variations (nsSNVs) that affect functional sites. This and similar workflows are becoming more important because thousands of NGS data sets are being made available through projects such as The Cancer Genome Atlas (TCGA), and researchers want to evaluate their biomarkers in genomic data. BioMuta, an integrated sequence feature database, provides a framework for automated and manual curation and integration of cancer-related sequence features so that they can be used in NGS analysis pipelines. Sequence feature information in BioMuta is collected from the Catalogue of Somatic Mutations in Cancer (COSMIC), ClinVar, UniProtKB and through biocuration of information available from publications. Additionally, nsSNVs identified through automated analysis of NGS data from TCGA are also included in the database. Because of the petabytes of data and information present in NGS primary repositories, a platform HIVE (High-performance Integrated Virtual Environment) for storing, analyzing, computing and curating NGS data and associated metadata has been developed. Using HIVE, 31 979 nsSNVs were identified in TCGA-derived NGS data from breast cancer patients. All variations identified through this process are stored in a Curated Short Read archive, and the nsSNVs from the tumor samples are included in BioMuta. Currently, BioMuta has 26 cancer types with 13 896 small-scale and 308 986 large-scale study-derived variations. Integration of variation data allows identifications of novel or common nsSNVs that can be prioritized in validation studies. Database URL: BioMuta: http://hive.biochemistry.gwu.edu/tools/biomuta/index.php; CSR: http://hive.biochemistry.gwu.edu/dna.cgi?cmd=csr; HIVE: http://hive.biochemistry.gwu.edu
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Affiliation(s)
- Tsung-Jung Wu
- Department of Biochemistry and Molecular Medicine, George Washington University, Washington, DC 20037, USA, Data Systems and Technology Jet Propulsion Laboratory 4800 Oak Grove Drive Pasadena, CA 91109 Center for Biologics Evaluation and Research, Food and Drug Administration, Rockville, MD 20852, USA and McCormick Genomic and Proteomic Center, George Washington University, Washington, DC 20037, USA
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Byrne M, Fokkema IF, Lancaster O, Adamusiak T, Ahonen-Bishopp A, Atlan D, Béroud C, Cornell M, Dalgleish R, Devereau A, Patrinos GP, Swertz MA, Taschner PE, Thorisson GA, Vihinen M, Brookes AJ, Muilu J. VarioML framework for comprehensive variation data representation and exchange. BMC Bioinformatics 2012; 13:254. [PMID: 23031277 PMCID: PMC3507772 DOI: 10.1186/1471-2105-13-254] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2012] [Accepted: 09/23/2012] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. RESULTS The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. CONCLUSIONS VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.
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Affiliation(s)
- Myles Byrne
- Institute for Molecular Medicine Finland-FIMM, University of Helsinki, Helsinki, Finland.
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Moorthie S, Hall A, Wright CF. Informatics and clinical genome sequencing: opening the black box. Genet Med 2012; 15:165-71. [PMID: 22975759 DOI: 10.1038/gim.2012.116] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Adoption of whole-genome sequencing as a routine biomedical tool is dependent not only on the availability of new high-throughput sequencing technologies, but also on the concomitant development of methods and tools for data collection, analysis, and interpretation. It would also be enormously facilitated by the development of decision support systems for clinicians and consideration of how such information can best be incorporated into care pathways. Here we present an overview of the data analysis and interpretation pipeline, the wider informatics needs, and some of the relevant ethical and legal issues.
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Smith CL, Eppig JT. The Mammalian Phenotype Ontology as a unifying standard for experimental and high-throughput phenotyping data. Mamm Genome 2012; 23:653-68. [PMID: 22961259 PMCID: PMC3463787 DOI: 10.1007/s00335-012-9421-3] [Citation(s) in RCA: 126] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2012] [Accepted: 07/24/2012] [Indexed: 01/16/2023]
Abstract
The Mammalian Phenotype Ontology (MP) is a structured vocabulary for describing mammalian phenotypes and serves as a critical tool for efficient annotation and comprehensive retrieval of phenotype data. Importantly, the ontology contains broad and specific terms, facilitating annotation of data from initial observations or screens and detailed data from subsequent experimental research. Using the ontology structure, data are retrieved inclusively, i.e., data annotated to chosen terms and to terms subordinate in the hierarchy. Thus, searching for "abnormal craniofacial morphology" also returns annotations to "megacephaly" and "microcephaly," more specific terms in the hierarchy path. The development and refinement of the MP is ongoing, with new terms and modifications to its organization undergoing continuous assessment as users and expert reviewers propose expansions and revisions. A wealth of phenotype data on mouse mutations and variants annotated to the MP already exists in the Mouse Genome Informatics database. These data, along with data curated to the MP by many mouse mutagenesis programs and mouse repositories, provide a platform for comparative analyses and correlative discoveries. The MP provides a standard underpinning to mouse phenotype descriptions for existing and future experimental and large-scale phenotyping projects. In this review we describe the MP as it presently exists, its application to phenotype annotations, the relationship of the MP to other ontologies, and the integration of the MP within large-scale phenotyping projects. Finally we discuss future application of the MP in providing standard descriptors of the phenotype pipeline test results from the International Mouse Phenotype Consortium projects.
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Moorthie S, Mattocks CJ, Wright CF. Review of massively parallel DNA sequencing technologies. THE HUGO JOURNAL 2011. [PMID: 23205160 DOI: 10.1007/s11568-011-9156-3] [Citation(s) in RCA: 59] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Since the development of technologies that can determine the base-pair sequence of DNA, the ability to sequence genes has contributed much to science and medicine. However, it has remained a relatively costly and laborious process, hindering its use as a routine biomedical tool. Recent times are seeing rapid developments in this field, both in the availability of novel sequencing platforms, as well as supporting technologies involved in processes such as targeting and data analysis. This is leading to significant reductions in the cost of sequencing a human genome and the potential for its use as a routine biomedical tool. This review is a snapshot of this rapidly moving field examining the current state of the art, forthcoming developments and some of the issues still to be resolved prior to the use of new sequencing technologies in routine clinical diagnosis.
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Frisoni GB, Redolfi A, Manset D, Rousseau MÉ, Toga A, Evans AC. Virtual imaging laboratories for marker discovery in neurodegenerative diseases. Nat Rev Neurol 2011; 7:429-38. [PMID: 21727938 DOI: 10.1038/nrneurol.2011.99] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The unprecedented growth, availability and accessibility of imaging data from people with neurodegenerative conditions has led to the development of computational infrastructures, which offer scientists access to large image databases and e-Science services such as sophisticated image analysis algorithm pipelines and powerful computational resources, as well as three-dimensional visualization and statistical tools. Scientific e-infrastructures have been and are being developed in Europe and North America that offer a suite of services for computational neuroscientists. The convergence of these initiatives represents a worldwide infrastructure that will constitute a global virtual imaging laboratory. This will provide computational neuroscientists with a virtual space that is accessible through an ordinary web browser, where image data sets and related clinical variables, algorithm pipelines, computational resources, and statistical and visualization tools will be transparently accessible to users irrespective of their physical location. Such an experimental environment will be instrumental to the success of ambitious scientific initiatives with high societal impact, such as the prevention of Alzheimer disease. In this article, we provide an overview of the currently available e-infrastructures and consider how computational neuroscience in neurodegenerative disease might evolve in the future.
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Self-perceived health in Belarus: Evidence from the income and expenditures of households survey. DEMOGRAPHIC RESEARCH 2011. [DOI: 10.4054/demres.2011.24.23] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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Significance of life table estimates for small populations: Simulation-based study of estimation errors. DEMOGRAPHIC RESEARCH 2011. [DOI: 10.4054/demres.2011.24.22] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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The crossover between life expectancies at birth and at age one: The imbalance in the life table. DEMOGRAPHIC RESEARCH 2011. [DOI: 10.4054/demres.2011.24.4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
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