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https://github.com/HussainiLab/hfoGUI

Graphical user interface to visualize EEG data. The applications can vary from scoring High Frequency Oscillations, to observing Theta and Gamma Synchrony.

Proper citation: hfoGUI (RRID:SCR_016726) Copy   

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https://www.synapse.org/ampad

Repository for distribution of various types of molecular data from human, cell-based and animal model biosamples, analytical results and research tools generated through multiple NIA-supported programs. Currently Portal supports AMP-AD Target Discovery and Preclinical Validation and MOVE-AD Consortia and translational center, MODEL-AD.

Proper citation: AMP-AD Knowledge Portal (RRID:SCR_016316) Copy   

•   Source: SciCrunch Registry

https://github.com/automaticanalysis/automaticanalysis

Integration framework for major open source packages in neuroimaging including SPM, FSL, FreeSurfer, EEGLAB, and Fieldtrip. Efficient neuroimaging workflows and parallel processing using Matlab and XML. Addresses challenges of processing multimodal datasets, like combining anatomy, functional MRI, diffusion, and EEG, to yield integrated views of brain. Allows to design, execute, and share pipelines utilizing multiple open source packages. Supports parallelized execution to address challenges of large cohort studies and provides quality control offering group statistics and reporting facilities to help identify outlier subjects and erroneous processing steps.

Proper citation: Automatic Analysis (RRID:SCR_003560) Copy   

•   Source: SciCrunch Registry

http://www.adgenetics.org/

Consortium to conduct genome-wide association studies (GWAS) to identify genes associated with an increased risk of developing late-onset Alzheimer''''s disease (LOAD). The goal of the ADGC is to identify genetic variants associated with risk for AD. It plans to do this through the following collaborative goals: # Identify genes responsible for AD susceptibility # Identify AD sub-phenotype genes rate-of-progression plaque / tangle load / distribution biomarker variability # Generate a genetic data resource for the AD research community Data generated by ADGC is available at the following website: https://www.niagads.org/content/alzheimers-disease-genetics-consortium-adgc-collection

Proper citation: Alzheimers Disease Genetics Consortium (RRID:SCR_004004) Copy   

•   Source: SciCrunch Registry

https://www.uab.edu/medicine/alzheimers/

The UAB Alzheimer's Disease Center provides comprehensive treatment for Alzheimer's patients while also promoting research for the prevention and cure of Alzheimer's disease and related disorders. The ADC is an interdisciplinary program of scientists working in areas including neurology, psychiatry, genetics, and psychology. The Center provides comprehensive treatment and promotes research for the prevention and/or cure of Alzheimer's disease and other related disorders with memory loss and impaired cognition. A major emphasis of research is the maintenance of a clinical research database comprised of neurological, medical, and neuropsychological test data from participants seen in the ADRC Clinical study since 1999, many of whom have been followed for several years in the study.

Proper citation: UAB Alzheimer's Disease Center (RRID:SCR_004305) Copy   

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https://adrc.mc.duke.edu/index.php

An Alzheimer's disease center (ADC) that offers support services for families caring for persons with memory disorders, community outreach and education programs, in addition to its clinical and basic research activities. Information on current scientific and clinical findings is offered to the general public, medical and scientific community. An important emphasis of the Bryan ADRC is to advance basic medical discovery concerning AD and related dementias. This basic science mission is facilitated through the DNA cell repository located in the Institute of Genome Sciences and Policy (IGSP) and the Bryan ADRC brain donation program of the Kathleen Price Bryan Brain Bank. These affiliated Bryan ADRC programs provide a source of fresh brain tissue.

Proper citation: Joseph and Kathleen Bryan Alzheimer's Disease Research Center (RRID:SCR_005025) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/icpsrweb/NACDA/

Archive of data relevant to gerontological and aging research. Used to advance research on aging. Subjects include demographic, social, economic, and psychological characteristics of older adults, physical health and functioning of older adults, and health care needs of older adults. NACDA staff represents team of professional researchers, archivists and technicians who work together to obtain, process, distribute, and promote data relevant to aging research.

Proper citation: National Archive of Computerized Data on Aging (NACDA) (RRID:SCR_005876) Copy   

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https://neurobiobank.nih.gov/

National resource for investigators utilizing human post-mortem brain tissue and related biospecimens for their research to understand conditions of the nervous system. Federated network of brain and tissue repositories in the United States that collects, evaluates, stores, and makes available to researchers, brain and other tissues in a way that is consistent with the highest ethical and research standards. The NeuroBioBank ensures protection of the privacy and wishes of donors. Provides information to the public about the need for tissue donation and how to register as a donor.

Proper citation: NIH NeuroBioBank (RRID:SCR_003131) Copy   

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http://adni-info.org/

Database of the results of the ADNI study. ADNI is an initiative to develop biomarker-based methods to detect and track the progression of Alzheimer's disease (AD) that provides access to qualified scientists to their database of imaging, clinical, genomic, and biomarker data.

Proper citation: ADNI - Alzheimer's Disease Neuroimaging Initiative (RRID:SCR_003007) Copy   

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http://www.nltcs.aas.duke.edu/index.htm

A data set of a longitudinal survey designed to study changes in the health and functional status of older Americans (aged 65+). It also tracks health expenditures, Medicare service use, and the availability of personal, family, and community resources for caregiving. The survey began in 1982, and follow-up surveys were conducted in 1984, 1989, 1994, 1999, and 2004. The surveys are of the entire Medicare-enrolled aged population with a particular emphasis on the functionally impaired. As sample persons are followed through the Medicare record system, virtually 100% of cases can be longitudinally tracked so that declines, as well as increases, in disability may be identified as well as exact dates of death. NLTCS sample persons are followed until death and are permanently and continuously linked to the Medicare record system from which they are drawn. Linkage to the Medicare Part A and B service use records extends from 1982 to 2004, so that detailed Medicare expenditures and types of service use may be studied. Through the careful application of methods to reduce non-sampling error, the surveys provide nationally representative data on: * The prevalence and patterns of functional limitations, both physical and cognitive; * Longitudinal and cohort patterns of change in functional limitation and mortality over 22 years; * Medical conditions and recent medical problems; * Health care services used; * The kind and amount of formal and informal services received by impaired individuals and how it is paid for; * Demographic and economic characteristics like age, race, sex, marital status, education, and income and assets; * Out-of-pocket expenditures for health care services and other sources of payment; * Housing and neighborhood characteristics. In each of the six surveys, large samples (N~20,000) of the oldest-old population (i.e., those 85 and over) are obtained. The survey data (i.e., detailed community and institutional interviews. The linkage to Medicare enrollment files between 1982 and 2004 was 100%, i.e., there was complete follow-up of all cases (including survey non-respondents) for Medicare eligibility (and for most years, detailed Part A and B use), mortality, and date of death. Medicare mortality records (and dates of death) are available for 1982 to 2005. The number of deaths (i.e., about 32,000 from 1982 to 2005) is large enough that detailed mortality analyses can be done. Over the 22 years spanned by the six surveys, a total of 49,242 distinct individuals were followed from and linked to Medicare records. Data Availability: The data are available through ICPSR as Study No. 9681. The data are available only on CD-ROM and only upon completion of a signed Data Use Agreement. Continuously linked Medicare data (1982 through 2004) for the National Long Term Care Surveys are only available from CMS. * Dates of Study: 1982-2004 * Study Features: Longitudinal, Anthropometric Measures * Sample Size: ** 1982: 20,485 ** 1984: 25,401 ** 1989: 17,565 ** 1994: 19,171 ** 1999: 19,907 ** 2004: 20,474 Link: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09681

Proper citation: National Long Term Care Survey (RRID:SCR_008943) Copy   

•   Source: SciCrunch Registry

http://www.ohsu.edu/xd/research/centers-institutes/neurology/alzheimers/research/data-tissue/biomarkers-genetics.cfm

A center that works with the Oregon Alzheimer's Disease Center's Data Core, and collects and stores tissue samples, family history and genotype data of various populations. These include samples and data from subjects from the following sources: OADC clinical studies, the Oregon Brain Aging Study, the Community Brain Donor Program, the Preventing Cognitive Decline with Alternative Therapies program (informally called the Dementia Prevention Study or DPS), the African American Dementia and Aging Project, and the Klamath Exceptional Aging Project. The collected data samples include genomic DNA, lymphoblast cell lines, genome-wide and candidate region SNP marker data, APOE, AD candidate gene markers.

Proper citation: Layton Center Biomarkers and Genetics (RRID:SCR_008824) Copy   

•   Source: SciCrunch Registry

http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/09915/version/3

A data set and sister study to the Established Populations for Epidemiologic Study of the Elderly (EPESE). It complements the findings of the three other EPESE sites (East Boston, MA; New Haven, CT; and north-central North Carolina) and has common items and methods in many domains. The target population was all persons 65 years and older in two rural counties in east central Iowa: Iowa and Washington counties. In 1981 a census of older persons in the target area was conducted by the investigators, creating an ascertainment list having 99% of the persons identified in the previous year by the US Decennial Census. The baseline survey was conducted between December 1991 and August 1992. Overall, 3,673 persons, or 80% of the target population were interviewed: 65-69 (N = 986), 70-74 (N = 988), 75-79 (N = 815), 80-84 (N = 523), and 85+ (N = 361). The population is virtually entirely Caucasian. Subsequently, personal follow-up surveys were conducted 3, 6, and 10 years after the baseline survey. Telephone surveys were conducted 1, 2, 4, 5, and 7 years after the baseline survey. Data collected from respondents included information about demographics, major health conditions, health care utilization, hearing and vision, weight and height, elements of nutrition, sleep problems, depressive and anxiety symptoms, alcohol and tobacco use, cognitive performance and dementia screening, incontinence measures, life satisfaction index, social networks and support, worries, medication use, activities of daily living, dental problems, satisfaction with medical care, life events, brief economic status, automobile driving habits, multiple measures of physical and disability status, and blood pressure. At follow-up #6, there were a series of physical function performance tests, the so-called NIA-MacArthur Battery, and blood was drawn for biochemical tests and potentially other determinations. In addition, some datasets were linked to the EPESE dataset under appropriate restrictions, including Iowa state driving records and clinical diagnoses and medical care utilization from the Centers for Medicare and Medicaid Services. Data Availability: The dataset has been shared with several investigative teams under special arrangement with the Principal Investigator. Early surveys are available from ICPSR. A small storage of blood is available for exploratory analyses. * Dates of Study: 1991-2001 * Study Features: Longitudinal, Anthropometric Measures, Biomarkers * Sample Size: 1991-2: 3,673 (baseline) Link: EPESE 1981-93 ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/09915

Proper citation: Iowa 65+ Rural Health Study (RRID:SCR_008937) Copy   

•   Source: SciCrunch Registry

http://www.norc.org/Research/Projects/Pages/national-social-life-health-and-aging-project.aspx

A longitudinal, population-based study of health and social factors, aiming to understand the well-being of older, community-dwelling Americans by examining the interactions among physical health and illness, medication use, cognitive function, emotional health, sensory function, health behaviors, social connectedness, sexuality, and relationship quality. NSHAP provides policy makers, health providers, and individuals with useful information and insights into these factors, particularly on social and intimate relationships. The study contributes to finding new ways to improve health as people age. In 2005 and 2006, NORC and Principal Investigators at the University of Chicago conducted the first wave of NSHAP, completing more than 3,000 interviews with a nationally representative sample of adults aged 57 to 85. In 2010 and 2011, nearly 3,400 interviews were completed for Wave 2 with these Wave 1 Respondents, Wave 1 Non-Interviewed Respondents, and their spouses or cohabiting romantic partners. The second wave of NSHAP is essential to understanding how social and biological characteristics change. NSHAP, by eliciting a variety of information from respondents over time, provides data that will allow researchers in a number of fields to examine how specific factors may or may not affect each other across the life course. For both waves, data collection included three measurements: in-home interviews, biomeasures, and leave-behind respondent-administered questionnaires. The face-to-face interviews and biomeasure collection took place in respondents'''' homes. NSHAP uses a national area probability sample of community residing adults born between 1920 and 1947 (aged 57 to 85 at the time of the Wave 1 interview), which includes an oversampling of African-Americans and Hispanics. The NSHAP sample is built on the foundation of the national household screening carried out by the Health and Retirement Study (HRS) in 2004. Through a collaborative agreement, HRS identified households for the NSHAP eligible population. A sample of 4,400 people was selected from the screened households. NSHAP made one selection per household. Ninety-two percent of the persons selected for the NSHAP interview were eligible. For Wave 2 in 2010 and 2011, NSHAP returned to Wave 1 Respondents and eligible non-interviewed respondents from Wave 1 (Wave 1 Non-Interviewed Respondents). NSHAP also extended the Wave 2 sample to include the cohabiting spouses and romantic partners of Wave 1 Respondents and Wave 1 Non-Interviewed Respondents. Partners were considered to be eligible to participate in NSHAP if they resided in the household with the Wave 1 Respondent/Wave 1 Non-Interviewed Respondent at the time of the Wave 2 interview and were at least 18 years of age. Wave I biomeasures: height; weight; waist circumference; blood pressure; smell; taste; vision; touch; respondent-administered vaginal swabs; oral mucosal transudate (OMT) for HIV-1 antibody screening; saliva; ����??get up and go����??; and blood spots. Technological advances in biomeasure collection methods have decreased respondent burden and increased ease of collection, storage, and yield of various biomeasures for the second wave of NSHAP. Wave II biomeasures: anthropometrics, including height, hip and waist circumference, and weight; cardiovascular function, including blood pressure, heart rate variability, and pulse; 2 of the 3 components of the short physical performance battery (SPPB) including chair stands and a timed walk; sensory function including smell; and actigraphy. In addition, we collect dried blood spots, microtainer blood, passive drool and salivettes, urine, and respondent-administered vaginal swabs, each of which are analyzed using multiple assays for a variety of measures and rationales. Furthermore, we assess respondents����?? cognition using the Montreal Cognitive Assessment (MoCA). Data Availability: NSHAP data made available to the public does not contain any identifiable respondent information and uses code numbers instead of names for all data. De-identified data from the 2005 and 2006 interviews are available to researchers through the National Archive of Computerized Data on Aging, located within Inter-University Consortium for Political and Social Research (ICPSR). Data from the Wave 2 interviews in 2010 and 2011 will be available in the summer of 2012. * Dates of Study: 2005-2006, 2010-2011 * Study Features: Biospecimens, Anthropometric Measures * Sample Size: ** Wave 1: 3,005 ** Wave 2: 3,377 Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/20541

Proper citation: National Social Life Health and Aging Project (NSHAP) (RRID:SCR_008950) Copy   

•   Source: SciCrunch Registry

http://picsl.upenn.edu/software/histolozee/

Software tool that integrates histology reconstruction, MRI co-registration, and manual segmentation tools in easy-to-use and intuitive interface. Permits real-time interaction with complex and large histology datasets during co-registration steps of histology reconstruction. Software tool for interactively mapping 2D and 3D molecular and anatomical histology into Common Coordinate Frameworks. Has simple, interactive registration workflows that connect user images with CCFs.

Proper citation: HistoloZee (RRID:SCR_019263) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   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://fmug.amaral.northwestern.edu/

Software data-driven tool to identify understudied genes and characterize their tractability. Users submit list of human genes and can filter these genes down based on list of factors. Code to generate Find My Understudied Genes app for Windows, iOS and macOS platforms.

Proper citation: Find My Understudied Genes (RRID:SCR_025047) Copy   

•   Source: SciCrunch Registry

https://sea-ad.shinyapps.io/ACEapp/

Web application for comparing cell type assignments and other cell-based annotations (e.g., donor demographics, anatomic locations, batch variables, and quality control metrics). Used for connecting brain cell types across studies of health and Alzheimer's Disease.

Proper citation: Annotation Comparison Explorer (RRID:SCR_026496) Copy   

•   Source: SciCrunch Registry