Single-Cell RNA Data Portal for Alzheimer's Disease

The single cell Alzheimer's Disease Data Portal is an aggregated data portal created as part of the Enfield EU Funded program for the single-cell Generative Pretrained Transformer (scGPT-AD) model research. The data portal contains data from the ssREAD data portal, along with single-cell AD data from latest studies (dharsini et al, pan et al, rexach et al). The data from the individual studies where accessed through the cellXgene data portal, a vast portal for single cell data. The data have been uploaded in two seperate .zip files (part1, part2).

The single cell data follow the Annotated Data format. The core data for each sample is the gene-expression matrix, which refers to the level of expression of each gene in a single cell. Additionally, the dataset contains the `.obs` attributed which includes core cell metadata for each of the sample (cell type, brain region, braak stage, donor age, disease condition, donor gender, etc.), along with the gene names accessed via `.var` attribute.

The source data have been processed to create a unified data portal ready to be used as training dataset for a Transformer model. The main processing steps were:

• convert ssREAD data from `.qsave` format to `.h5ad` format that aligns with the AnnData framework
• discard some unprocessable data samples
• standardize metadata column names
• process categorical data to create a unified namespace (e.g.: merge `microglia` and `microgrial` cell type names into one)
• discard dimensionality reduction and clustering attributes, to make a lightweight version of the data portal, since they are not meant to be used in Transformer model training

Aggregated Data Statistics

Characteristics of Dataset grouped by Data Source

The Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) consortium strives to gain a deep molecular and cellular understanding of the early pathogenesis of Alzheimer's disease and is funded by the National Institutes on Aging (NIA U19AG060909). The SEA-AD datasets available here comprise single cell profiling (transcriptomics and epigenomics) and quantitative neuropathology. To explore gene expression and chromatin accessibility information, the single-cell profiling data includes: snRNAseq and snATAC-seq data from the SEA-AD donor cohort (aged brains which span the spectrum of Alzheimer's Disease pathology) and neurotypical reference brains. To explore key pathological proteins and cell types of interest to Alzheimer's disease, the neuropathology data includes: full resolution brightfield images, images processed and segmented in HALO image analysis software, image annotations, and quantification summary files for the relevant stains including Abeta (6E10), IBA1, a-Synuclein, GFAP, H&E-LFB, NeuN, pTau(AT8), and pTDP43.

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.

The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) is a national genetics data repository facilitating access to genotypic and phenotypic data for Alzheimer's disease (AD). Data include GWAS, whole genome (WGS) and whole exome (WES), expression, RNA Seq, and CHIP Seq analyses. Data for the Alzheimer’s Disease Sequencing Project (ADSP) are available through a partnership with dbGaP (ADSP at dbGaP). Results are integrated and annotated in the searchable genomics database that also provides access to a variety of software packages, analytic pipelines, online resources, and web-based tools to facilitate analysis and interpretation of large-scale genomic data. Data are available as defined by the NIA Genomics of Alzheimer’s Disease Sharing Policy and the NIH Genomics Data Sharing Policy. Investigators return secondary analysis data to the database in keeping with the NIAGADS Data Distribution Agreement.

Longitudinal study of pre-symptomatic Alzheimer's Disease. Longitudinal data from 348 participants are available. This includes multi-modal MRI images, neuropsychological tests, neurosensory assessments, general medical history, genetics and cerebrospinal fluid proteins levels.

Longitudinal study of pre-symptomatic Alzheimer's Disease

Collection of field observations shared by citizens. The observations are uploaded to GBIF at a resolution of 1x1 km, except for some species of conservation concern for which data are shown at 10x10 km resolution. Data refers to terrestrial vertebrates (including freshwater fishes), dragonflies, butterflies, moths, crickets, grasshoppers, cicadas, saproxil coleopters, freshwater bivalves, decapods, snails, slugs and orchids. The dataset includes one record of every observed species in every UTM 1x1 km or 10x10 km, selected randomly from the global data registered in www.ornitho.ad

Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) is currently one of the powerful tools for the clinical diagnosis of dementia such as Alzheimer's Disease (AD). Meanwhile, MR imaging, being non-radioactive and having high contrast resolution, is highly accessible in clinical settings. Therefore, this dataset intends to use FDG-PET images as the Ground Truth for evaluating AD, for the development of predicting AD patients using MR images. This dataset includes an AD group and a control group (Healthy Group). The determination of the image diagnosis group is made by neurology specialists based on comprehensive judgment using clinically relevant information. Each set of data contains one set of MRI T1 images and one set of FDG-PET images. The image format is DICOM, and all images have been anonymized. To obtain the clinical information and related documentation, please contact the administrator.

NACC’s Uniform Data Set (UDS), collected since 2005, is widely regarded as the gold standard by the field. This longitudinal, multi-domain neurocognitive and phenotypic dataset includes robust, criteria-based diagnoses, providing a valuable foundation for grounding other studies. UDS data collection instruments are trusted benchmarks in Alzheimer’s disease and related dementias (AD/ADRD) clinical phenotypic assessments globally.

The Historical Urban Population, 3700 BC - AD 2000, originally developed by the Yale School of Forestry & Environmental Studies, is the first spatially explicit global data set containing location and size of urban populations over the last 6,000 years. The data set was created by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data. Each data point consists of a city name, latitude, longitude, year, population, and a reliability ranking to assess the geographic uncertainty of each data point. Despite spatial and temporal gaps, no other geocoded data set at this resolution exists. It can therefore be used to investigate long-term historical urbanization trends and patterns, evaluate the current era of urbanization, and build a richer record of urban population through history.

The ability to investigate therapeutic interventions in animal models of neurodegenerative diseases depends on extensive characterization of the model(s) being used. There are numerous models that have been generated to study Alzheimer’s disease (AD) and the underlying pathogenesis of the disease. While transgenic models have been instrumental in understanding AD mechanisms and risk factors, they are limited in the degree of characteristics displayed in comparison with AD in humans, and the full spectrum of AD effects has yet to be recapitulated in a single mouse model. The Model Organism Development and Evaluation for Late-Onset Alzheimer’s Disease (MODEL-AD) consortium was assembled by the National Institute on Aging (NIA) to develop more robust animal models of AD with increased relevance to human disease, standardize the characterization of AD mouse models, improve preclinical testing in animals, and establish clinically relevant AD biomarkers, among other aims toward enhancing the translational value of AD models in clinical drug design and treatment development. Here we have conducted a detailed characterization of the 5XFAD mouse, including transcriptomics, electroencephalogram, in vivo imaging, biochemical characterization, and behavioral assessments. The data from this study is publicly available through the AD Knowledge Portal.

We used auditory stimuli of different durations (AD) and frequencies (AF). In AD, 10 types of pure sinusoidal tones (1 ms rise/fall) with different durations (10, 25, 50, 75, 100, 125, 150, 175, 200, and 225 ms; 1000 Hz; 2000 stimuli in total) were randomly presented with an equal probability of 10%. In AF, 10 types of tones with different frequencies (700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, and 1600 Hz; 50 ms; 1000 stimuli in total) were presented with an equal probability of 10%.
Epidural ECoG recordings were taken in the passive listening condition while monkeys were in awake and ketamine (30 mg/kg i.m.) administrated conditions. ECoG data were sampled at 1KHz.
Data format information can be found on TychoWiki.

This dataset contains Saudi Arabia Postal Services at Makkah Post Offices During the Hajj (1-15 -12) for 1999 - 2008. Data from General Authority for Statistics . Export API data for more datasets to advance energy economics research.

This competition involves advertisement data provided by BuzzCity Pte. Ltd. BuzzCity is a global mobile advertising network that has millions of consumers around the world on mobile phones and devices. In Q1 2012, over 45 billion ad banners were delivered across the BuzzCity network consisting of more than 10,000 publisher sites which reach an average of over 300 million unique users per month. The number of smartphones active on the network has also grown significantly. Smartphones now account for more than 32% phones that are served advertisements across the BuzzCity network. The "raw" data used in this competition has two types: publisher database and click database, both provided in CSV format. The publisher database records the publisher's (aka partner's) profile and comprises several fields:

publisherid - Unique identifier of a publisher. Bankaccount - Bank account associated with a publisher (may be empty) address - Mailing address of a publisher (obfuscated; may be empty) status - Label of a publisher, which can be the following: "OK" - Publishers whom BuzzCity deems as having healthy traffic (or those who slipped their detection mechanisms) "Observation" - Publishers who may have just started their traffic or their traffic statistics deviates from system wide average. BuzzCity does not have any conclusive stand with these publishers yet "Fraud" - Publishers who are deemed as fraudulent with clear proof. Buzzcity suspends their accounts and their earnings will not be paid

On the other hand, the click database records the click traffics and has several fields:

id - Unique identifier of a particular click numericip - Public IP address of a clicker/visitor deviceua - Phone model used by a clicker/visitor publisherid - Unique identifier of a publisher adscampaignid - Unique identifier of a given advertisement campaign usercountry - Country from which the surfer is clicktime - Timestamp of a given click (in YYYY-MM-DD format) publisherchannel - Publisher's channel type, which can be the following: ad - Adult sites co - Community es - Entertainment and lifestyle gd - Glamour and dating in - Information mc - Mobile content pp - Premium portal se - Search, portal, services referredurl - URL where the ad banners were clicked (obfuscated; may be empty). More details about the HTTP Referer protocol can be found in this article. Related Publication: R. J. Oentaryo, E.-P. Lim, M. Finegold, D. Lo, F.-D. Zhu, C. Phua, E.-Y. Cheu, G.-E. Yap, K. Sim, M. N. Nguyen, K. Perera, B. Neupane, M. Faisal, Z.-Y. Aung, W. L. Woon, W. Chen, D. Patel, and D. Berrar. (2014). Detecting click fraud in online advertising: A data mining approach, Journal of Machine Learning Research, 15, 99-140.

This ad hoc release provides information on prescriptions prescribed in England and dispensed in Scotland monthly between June 2023 and June 2024. The NHSBSA receive prescription data from NHS Scotland of English prescribing dispensed in Scotland and is held in the NHSBSA Data Warehouse. This dataset is published within the English prescribing data (EPD) | NHSBSA, however, due to technical issues, June 2023 - June 2024 of prescribing data has not been included. To support users who may require this information NHSBSA have made this available as an ad hoc release. Prescription data from July 2024 onwards will begin to reappear in the English Prescribing Dataset from September 2024 data release. Alternatively, this can be obtained from ePACT2 | NHSBSA provided you have access to create your own analysis, further information on gaining access and any training requirements can be found by Registering for ePACT2 | NHSBSA.

The Web Portal Operation industry is highly concentrated, with three companies controlling almost the entire industry; the largest company in the industry, Alphabet Inc, has a market share greater than 90% in 2025. This market concentration has fostered significant advertising revenue but made it exceedingly difficult for smaller web portals to survive. Yet, the presence of local champions like Yandex in Russia and Seznam in the Czech Republic demonstrates that regional portals can find niches, particularly where differentiated content or national digital policies shape market dynamics. Search engines generate most, if not all, of their revenue from advertising. Technological growth has led to more households being connected to the internet and a boom in e-commerce has made the industry increasingly innovative. Over the past decade, a boost in the percentage of households with internet access across Europe has supported revenue expansion, while strengthening technological integration with daily life has boosted demand for web portals. Industry revenue is expected to swell at a compound annual rate of 17.4% over the five years through 2025, including growth of 15% in 2025, to reach €74.9 billion. While profit is high, it is projected to dip amid hiking operational pressures, changing advertising dynamics and heightened regulatory compliance costs. A greater proportion of transactions being carried out online has driven innovation in targeted digital advertising, with declines in rival advertising formats like print media and television expanding the focus on digital marketing as a core strategy. Market leaders have maintained dominance via exclusive agreements, like Google’s multi-billion-euro deals to remain the default search engine on Apple and Android devices, embedding themselves deeper into users’ daily digital interactions. At the same time, the rise of privacy-first search engines like DuckDuckGo, Ecosia and Qwant reflects shifting consumer attitudes toward data privacy and environmental impact. However, Google's status as the default search provider on most mainstream platforms, coupled with robust integration through Chrome and Google's broader ecosystem, has significantly constrained market entry for competitors, perpetuating the industry’s concentration. The rise of the mobile advertising market and the proliferation of mobile devices mean there are plenty of opportunities for search engines, which are expected to capitalise on these trends further moving forward. Smartphones could disrupt the industry's status quo, as the rising popularity of devices that don’t use Google as the default engine benefits other web portals. Technological advancements that incorporate user data are likely to make it easier to tailor advertisements and develop new ways of using consumer data. Initiatives like the European Search Perspective (EUSP) joint venture between Ecosia and Qwant signal the beginnings of intensified competition, especially around privacy and regional digital sovereignty. Nonetheless, industry growth is set to continue, fuelled by surging demand for localised, targeted digital advertising and heightened investment in mobile marketing. Industry revenue is forecast to jump at a compound annual rate of 20.4% over the five years through 2030 to reach €189.7 billion.

This dataset contains Saudi Arabia Rolling Stock by Type for 2008-2013. Data from General Authority for Statistics . Export API data for more datasets to advance energy economics research.

Listing of all active businesses currently registered with the Office of Finance. An "active" business is defined as a registered business whose owner has not notified the Office of Finance of a cease of business operations. Update Interval: Monthly.

Government boundaries of North Dakota, U.S.A. Includes North Dakota counties, cities, tribal lands, PLSS and other administrative boundaries that is provided by data stewards for North Dakota state agencies and commissions.

These data include genotypes and covariates part of the data generated from 463 prefrontal cortex brain samples (310 Late Onset Alzheimer's Disease patients, 153 control) in the frames of Harvard Brain Tissue Research Center study. The data from the HBTRC set (previously accessible via https://synapse.sagebase.org/#Synapse:syn4505) is being made available through the AMP-AD Knowledge Portal at https://www.synapse.org/#!Synapse:syn3159435. This is a copy of the originally available data set. Data set was used to produce HBTRC epistasis data set https://doi.org/10.6084/m9.figshare.5234689 that is a part of the integrated data collection HENA https://doi.org/10.6084/m9.figshare.c.4469240