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http://senselab.med.yale.edu/cellpropdb

A repository for data regarding membrane channels, receptor and neurotransmitters that are expressed in specific types of cells. The database is presently focused on neurons but will eventually include other cell types, such as glia, muscle, and gland cells. This resource is intended to: * Serve as a repository for data on gene products expressed in different brain regions * Support research on cellular properties in the nervous system * Provide a gateway for entering data into the cannonical neuron forms in NeuronDB * Identify receptors across neuron types to aid in drug development * Serve as a first step toward a functional genomics of nerve cells * Serve as a teaching aid

Proper citation: Cell Properties Database (RRID:SCR_007285) Copy   

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http://www.adcs.org/

An initiative for Alzheimer's disease clinical studies that works to facilitate the discovery, development and testing of new drugs, and is a part of the Alzheimer's Disease Prevention Initiative. This resource has an emphasis on expanding the range of its patients, mainly by enhancing the recruitment of minority groups. There is a further emphasis placed on testing agents that cannot be patented, as well as developing novel compounds that had been developed by individuals, academic institutions and drug discovery units. This resource also helps in the development of Alzheimer's disease centers to carry out studies, as well as establish administrative, data, operations and medical cores in San Diego. This organization is specifically involved in studies demonstrating the lack of benefit associated, previously used treatments such as: the use of estrogen, non-steroidal anti-inflammatory drugs, B vitamins and a statin drug. The Alzheimer's Disease Cooperative Study also develops assessment instruments to be used in clinical trials. The most frequently used of these tools include: the Alzheimer's Disease Assessment Scale-Cognitive sub-scale (ADAS-cog), Activities of Daily Living (ADL), and the Clinical Global Impression of Change Scale (CGIC). There is also an associated tissue bank at UCSD that includes materials from the clinical trials including: human tissue, blood, plasma, DNA, urine and cerebrospinal fluid.

Proper citation: Alzheimer's Disease Cooperative Study (RRID:SCR_008254) Copy   

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http://www.uky.edu/coa/adc/investigators-research-resources

An organization which includes a tissue bank, a database, study design consultation, clinical resources, and a community registry database. The UK-ADC shares data with the NIA national database (NACC), as well as with independent, qualified investigators both within and outside the UK-ADC. This resource's associated tissue bank is comprised of anonymized brain tissue, blood, and cerebrospinal fluid samples from patients in the clinic, as well as frozen post-mortem brain tissue samples. This organization also shares research resources with the National Alzheimer's Coordinating Center (NACC), NACC collaborative initiatives, the Alzheimer's Disease Neuroimaging Initiative (ADNI), other Alzheimer Disease Centers (ADCs), and any qualified investigators from either the University of Kentucky or the general scientific community.

Proper citation: University of Kentucky's Alzheimer's Disease Center (RRID:SCR_008766) Copy   

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http://centerforaging.duke.edu/index.php?option=com_content&view=article&id=115&Itemid=152

The project has been collecting detailed panel data about the health, disability, demographic, family, socioeconomic, and behavioral risk-factors for mortality and healthy longevity of the oldest old, with a comparative sub-sample of younger elders, to examine the factors in healthy longevity. The baseline survey was conducted in 1998 and the follow-up surveys with replacement to compensate for deceased elders were conducted in 2000, 2002, 2005, and 2008, For each centenarian, one near-by octogenarian (aged 80-89) and one near-by nonagenarian (aged 90-99) of pre-designated age and sex were interviewed. Near-by is loosely defined it could be in the same village or street if available, or in the same town or in the same county or city. The idea was to have comparable numbers of male and female octogenarians and nonagenarians at each age from 80 to 99. In 2002, the study added a refresher sub-sample of 4,845 interviewees aged 65-79, and a sub-sample of 4,478 adult children (aged 35-65) of the elderly interviewees aged 65-110 in eight provinces Comparative study of intergenerational relationships in the context of rapid aging and healthy longevity between Mainland China and Taiwan is possible. At each wave, the longitudinal survivors were re-interviewed, and the deceased interviewees were replaced by additional participants. Data on mortality and health status before dying for the 12,136 elders aged 65-112 who died between the waves were collected in interviews with a close family member of the deceased. The study also included interviews and follow-ups with 4,478 elderly interviewees'''' children aged 35-65. * Dates of Study: 1998-2005 * Study Features: Longitudinal, International * Sample Size: ** 1998: 8,993 ** 2000: 11,199 ** 2002: 16,064 ** 2005: 14,923 Links * Data Archive, http://www.geri.duke.edu/china_study/CLHLS6.htm * ICPSR, http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/03891

Proper citation: Chinese Longitudinal Healthy Longevity Survey (CLHLS) (RRID:SCR_008904) Copy   

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http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/4050?geography=South+Carolina

The Charleston Heart Study (CHS) is a prospective cohort study of 2,283 subjects (1,394 whites, 889 blacks) in which risk factors of coronary disease have been examined for the past 43 years. The CHS began enrolling a random selection of community residents who in 1960 were 35 years of age and older ����?? including men and women, black and white. A unique feature of this cohort is the fact that 102 high socio-economic status (SES) black men were purposefully included. The primary hypothesis of the original study was to investigate racial differences in the manifestation and risk factors for coronary disease. Over the ensuing 40+ years, a variety of outcome measurements were incorporated into the re-examination of the participants, including psychosocial, behavioral, aging and functional measures. Subjects were initially interviewed and examined in 1960 and 1963. Subsequent interviews and examinations took place during the following time periods: 1974-1975, 1984-1985, 1987-1989, and 1990-1991. During the most recent questionnaire (1990-1991), the following topics were examined: general health, smoking, functional disability, physical disability, cardiovascular health, sexual dysfunction, cognitive disability, depression, coffee consumption, medication history, medical history, nutrition, and body image. In addition, serum samples and blood pressure measurements were taken, and a physical exam was performed by a physician. A search of the National Death Index was completed through the year 2000, matching individuals with date and cause of death. Vital status of the CHS study participants through 12-31-2000 is presented below. Dead * White Men 539 (82.5%) * White Women 500 (67.5%) * Black Men 281 (84.4%) * High SES Black Men 59 (57.8%) * Black Women 343 (75.6%) Data Availability: Datasets are stored in the National Archive of Computerized Data on Aging (NACDA) in the ICPSR as Study No. 4050. Data are also available from the Medical University of South Carolina Library; contact a PI, Paul J. Nietert, nieterpj (at) musc.edu for further information. * Dates of Study: 1960-2000 * Study Features: Longitudinal, Minority Oversamples, Anthropometric Measures * Sample Size: 1960: 2,283 (baseline) Link ICPSR, http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/04050

Proper citation: Charleston Heart Study (RRID:SCR_008895) Copy   

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http://brainmap.wisc.edu/monkey.html

NO LONGER AVAILABLE. Documented on September 17, 2019. A set of multi-subject atlas templates to facilitate functional and structural imaging studies of the rhesus macaque. These atlases enable alignment of individual scans to improve localization and statistical power of the results, and allow comparison of results between studies and institutions. This population-average MRI-based atlas collection can be used with common brain mapping packages such as SPM or FSL.

Proper citation: Rhesus Macaque Atlases for Functional and Structural Imaging Studies (RRID:SCR_008650) Copy   

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http://www.lisdatacenter.org/

A cross-national data archive located in Luxembourg that contains two primary databases: the Luxembourg Income Study Database (LIS Database) includes income microdata from a large number of countries at multiple points in time. The newer Luxembourg Wealth Study Database(LWS Database) includes wealth microdata from a smaller selection of countries. Both databases include labor market and demographic data as well. Our mission is to enable, facilitate, promote, and conduct cross-national comparative research on socio-economic outcomes and on the institutional factors that shape those outcomes. Since its beginning in 1983, the LIS has grown into a cooperative research project with a membership that includes countries in Europe, North America, and Australia. The database now contains information for more than 30 countries with datasets that span up to three decades. The LIS databank has a total of over 140 datasets covering the period 1968 to 2005. The primary objectives of the LIS are as follows: * Test the feasibility for creating a database containing social and economic data collected in household surveys from different countries; * Provide a method which allows researchers to use the data under restrictions required by the countries providing the data; * Create a system that allows research requests to be received from and returned to users at remote locations; and * Promote comparative research on the social and economic status of various populations and subgroups in different countries. Data Availability: The dataset is accessed globally via electronic mail networks. Extensive documentation concerning technical aspects of the survey data, variables list, and the social institutions of income provision in member countries are also available to users through the project Website. * Dates of Study: 1968-present * Study Features: International * Sample Size: 30+ Countries Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00150

Proper citation: Luxembourg Income Study (RRID:SCR_008732) Copy   

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http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000674.v1.p1

Human genetics data from an immense (78,000) and ethnically diverse population available for secondary analysis to qualified researchers through the database of Genotypes and Phenotypes (dbGaP). It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging. The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research. The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente''s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants'' health habits and backgrounds, providing researchers with an unparalleled research resource. As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.

Proper citation: Resource for Genetic Epidemiology Research on Adult Health and Aging (RRID:SCR_010472) Copy   

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http://www.nia.nih.gov/research/blog

Blog intended for grantees of the National Institute on Aging (NIA) at the NIH, as well as applicants for funding, those with an application in mind, application reviewers, and students pursuing careers in research on aging and Alzheimer's disease.

Proper citation: Inside NIA: A Blog for Researchers (RRID:SCR_012812) Copy   

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http://www.nitrc.org/projects/miitra/

Atlas for studies of older adult brain. Includes T1-weighted template of older adult brain and tissue probability maps. Exhibits high image sharpness, provides higher inter-subject spatial normalization accuracy compared to other standardized templates and similar normalization accuracy to well-constructed study-specific templates.

Proper citation: MIITRA atlas (RRID:SCR_017566) Copy   

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https://lsom.uthscsa.edu/dcsa/research/cores-facilities/optical-imaging/

Service resource which makes imaging technology available to investigators on UTHSCSA campus and neighboring scientific community. Core Optical Imaging Facility offers access to technology for imaging of living cells, tissues, and animals, consultation, education and assistance regarding theory and application of optical imaging techniques, technical advice on specimen preparation techniques and probe selection.

Proper citation: Texas University Health Science Center at San Antonio Long School of Medicine Department of Cell Systems and Anatomy Optical Imaging Core Facility (RRID:SCR_012171) Copy   

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https://github.com/parklab/NGSCheckMate

Software package for validating sample identity in next generation sequencing studies within and across data types. Used for identifying next generation sequencing data files from the same individual. Used for checking sample matching for NGS data.

Proper citation: NGSCheckMate (RRID:SCR_022994) Copy   

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https://miracl.readthedocs.io/en/latest/

Automated software resource that combines histologically cleared volumes with connectivity atlases and MRI, enabling analysis of histological features across multiple fiber tracts and networks, and their correlation with in vivo biomarkers.Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI. Open source pipeline for automated registration of mice clarity data to Allen reference atlas, segmentation and feature extraction of mice clarity data in 3D, registration of mice multimodal imaging data to Allen reference atlas, tract or label specific connectivity analysis based on Allen connectivity atlas,comparison of diffusion tensort imaging/tractography, virus tracing using CLARITY and Allen connectivity atlas, statistical analysis of CLARITY and Imaging data, atlas generation and label manipulation.

Proper citation: MIRACL (RRID:SCR_020945) Copy   

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https://alzped.nia.nih.gov

Publicly available, searchable, data resource that aims to increase transparency, reproducibility and translatability of preclinical efficacy studies of candidate therapeutics for Alzheimer’s disease. Knowledge platform for dissemination of data and analysis to scientists, from academic centers, industry, disease focused foundations. Provides quick access and visibility to integrated preclinical efficacy data from published and unpublished studies.

Proper citation: Alzheimer Disease Preclinical Efficacy Database (RRID:SCR_021230) Copy   

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https://github.com/nskvir/RepEnrich

Software tool to profile enrichment of next generation sequencing reads at transposable elements. Method to estimate repetitive element enrichment using high throughput sequencing data. Used to study genome wide transcriptional regulation of repetitive elements.RepEnrich2 is updated method to estimate repetitive element enrichment using high-throughput sequencing data.

Proper citation: RepEnrich (RRID:SCR_021733) Copy   

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https://github.com/evarol/HYDRA

Software tool as novel non-linear learning algorithm for simultaneous binary classification and subtype identification. Can handle imaging and non-imaging data and can find applications in exploratory analyses other than clustering of brain images.Software performs clustering of heterogenous disease patterns within patient group.

Proper citation: Heterogeneity through Discriminative Analysis (RRID:SCR_021958) Copy   

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https://github.com/SchapiroLabor/histoCAT

Software package to visualize and analyse multiplexed image cytometry data interactively.

Proper citation: histoCAT (RRID:SCR_026499) Copy   

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https://montilab.github.io/hypeR-docs/

Software R package that supports different types of gene set enrichment workflows. Offers multiple enrichment, visualization, and sharing methods in addition to novel features such as hierarchical geneset analysis and built-in markdown reporting.

Proper citation: hypeR (RRID:SCR_027229) Copy   

•   Source: SciCrunch Registry

https://github.com/dattalab/keypoint-moseq

Software application as machine learning-based platform for identifying behavioral modules from keypoint data without human supervision. Package provides tools for fitting MoSeq model to keypoint tracking data. Used to infer pose dynamics with keypoint data in addition to behavioral syllables.

Proper citation: Keypoint MoSeq (RRID:SCR_025032) Copy   

•   Source: SciCrunch Registry

https://mimedb.org

Database containing detailed information about small molecules produced by human microbiome. Provides metabolite data including structure, names, descriptions, chemical taxonomy, chemical ontology, physico-chemical data, spectra and contains detailed information about microbes that produce these chemicals, enzymatic reactions responsible for their production, bioactivity of chemicals and anatomical location of these chemicals and microbes. Many data fields in the database are hyperlinked to other databases including FooDB, HMDB, KEGG, PubChem, MetaCyc, ChEBI, UniProt, and GenBank. Database is FAIR compliant.The data in MiMeDB are released under the Creative Commons (CC) 4.0 License.

Proper citation: MiMeDB (RRID:SCR_025108) Copy   

•   Source: SciCrunch Registry