IDEAL, Intrinsically Disordered proteins with Extensive Annotations and Literature, is a collection of knowledge on experimentally verified intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). IDEAL contains manually curated annotations on IDPs in locations, structures, and functional sites such as protein binding regions and posttranslational modification sites together with references and structural domain assignments. Protean segment One of the unique phenomena seen in IDPs is so-called the coupled folding and binding, where a short flexible segment can bind to its binding partner with forming a specific structure to act as a molecular recognition element. IDEAL explicitly annotates these regions as protean segment (ProS) when unstructured and structured information are both available in the region. Access to the data All the entries are tabulated in the list and individual entries can be retrieved by using the search tool at the upper-right corner in this page. IDEAL also provides the BLAST search, which can find homologs in IDEAL. All the information in IDEAL can be downloaded in the XML file.

A comparison table of popular database documentation tools, including supported DBMS, documentation formats, ease of use, customization options, and pricing.

Liquid chromatography tandem mass spectrometry (LC–MS/MS) analysis of secreted proteins has contributed to our understanding of human disease and physiology but is limited by its need for accurate protein database annotation. Common assumptions used in proteomics of perfect protease specificity are inaccurate for secreted proteins, which are cleaved by numerous endogenous proteases. Here, we describe the generation of an optimized protein database that divides proteins into their individual biological chains and peptides to allow fast identification of semi-tryptic peptides from secreted proteins using fully tryptic searches. We applied this biologically annotated database to previously published human plasma proteome data sets containing either DIA or DDA data, using Spectronaut, DIA-NN, MaxDIA, and MaxQuant. Using our annotated database, we greatly reduced search times while achieving similar protein and peptide identifications compared to that obtained from standard approaches using semi-tryptic searches. Furthermore, our database enables the identification of biologically relevant semi-tryptic peptides using data analysis packages that are not capable of semi-tryptic searches. Together, these findings demonstrate that our annotated database is more capable than currently available databases for secreted protein analysis and is particularly useful for large-scale plasma proteome analysis.

The Alaska Geochemical Database Version 4.0 (AGDB4) contains geochemical data compilations in which each geologic material sample has one best value determination for each analyzed species, greatly improving efficiency of use. The relational database includes historical geochemical data archived in the USGS National Geochemical Database (NGDB), the Atomic Energy Commission National Uranium Resource Evaluation (NURE) Hydrogeochemical and Stream Sediment Reconnaissance databases, and the Alaska Division of Geological and Geophysical Surveys (DGGS) Geochemistry database. Data from the U.S. Bureau of Mines and the U.S. Bureau of Land Management are included as well. The data tables describe historical and new quantitative and qualitative geochemical analyses. The analytical results were determined by 120 laboratory and field analytical methods performed on 416,333 rock, sediment, soil, mineral, heavy-mineral concentrate, and oxalic acid leachate samples. The samples were collected as ...

Success.ai’s Company Data Solutions provide businesses with powerful, enterprise-ready B2B company datasets, enabling you to unlock insights on over 28 million verified company profiles. Our solution is ideal for organizations seeking accurate and detailed B2B contact data, whether you’re targeting large enterprises, mid-sized businesses, or small business contact data.

Success.ai offers B2B marketing data across industries and geographies, tailored to fit your specific business needs. With our white-glove service, you’ll receive curated, ready-to-use company datasets without the hassle of managing data platforms yourself. Whether you’re looking for UK B2B data or global datasets, Success.ai ensures a seamless experience with the most accurate and up-to-date information in the market.

Why Choose Success.ai’s Company Data Solution? At Success.ai, we prioritize quality and relevancy. Every company profile is AI-validated for a 99% accuracy rate and manually reviewed to ensure you're accessing actionable and GDPR-compliant data. Our price match guarantee ensures you receive the best deal on the market, while our white-glove service provides personalized assistance in sourcing and delivering the data you need.

Why Choose Success.ai?

• Best Price Guarantee: We offer industry-leading pricing and beat any competitor.
• Global Reach: Access over 28 million verified company profiles across 195 countries.
• Comprehensive Data: Over 15 data points, including company size, industry, funding, and technologies used.
• Accurate & Verified: AI-validated with a 99% accuracy rate, ensuring high-quality data.
• Real-Time Updates: Stay ahead with continuously updated company information.
• Ethically Sourced Data: Our B2B data is compliant with global privacy laws, ensuring responsible use.
• Dedicated Service: Receive personalized, curated data without the hassle of managing platforms.
• Tailored Solutions: Custom datasets are built to fit your unique business needs and industries.

Our database spans 195 countries and covers 28 million public and private company profiles, with detailed insights into each company’s structure, size, funding history, and key technologies. We provide B2B company data for businesses of all sizes, from small business contact data to large corporations, with extensive coverage in regions such as North America, Europe, Asia-Pacific, and Latin America.

Comprehensive Data Points: Success.ai delivers in-depth information on each company, with over 15 data points, including:

Company Name: Get the full legal name of the company. LinkedIn URL: Direct link to the company's LinkedIn profile. Company Domain: Website URL for more detailed research. Company Description: Overview of the company’s services and products. Company Location: Geographic location down to the city, state, and country. Company Industry: The sector or industry the company operates in. Employee Count: Number of employees to help identify company size. Technologies Used: Insights into key technologies employed by the company, valuable for tech-based outreach. Funding Information: Track total funding and the most recent funding dates for investment opportunities. Maximize Your Sales Potential: With Success.ai’s B2B contact data and company datasets, sales teams can build tailored lists of target accounts, identify decision-makers, and access real-time company intelligence. Our curated datasets ensure you’re always focused on high-value leads—those who are most likely to convert into clients. Whether you’re conducting account-based marketing (ABM), expanding your sales pipeline, or looking to improve your lead generation strategies, Success.ai offers the resources you need to scale your business efficiently.

Tailored for Your Industry: Success.ai serves multiple industries, including technology, healthcare, finance, manufacturing, and more. Our B2B marketing data solutions are particularly valuable for businesses looking to reach professionals in key sectors. You’ll also have access to small business contact data, perfect for reaching new markets or uncovering high-growth startups.

From UK B2B data to contacts across Europe and Asia, our datasets provide global coverage to expand your business reach and identify new markets. With continuous data updates, Success.ai ensures you’re always working with the freshest information.

Key Use Cases:

• Targeted Lead Generation: Build accurate lead lists by filtering data by company size, industry, or location. Target decision-makers in key industries to streamline your B2B sales outreach.
• Account-Based Marketing (ABM): Use B2B company data to personalize marketing campaigns, focusing on high-value accounts and improving conversion rates.
• Investment Research: Track company growth, funding rounds, and employee trends to identify investment opportunities or potential M&A targets.
• Market Research: Enrich your market intelligence initiatives by gain...

Premium B2C Consumer Database - 269+ Million US Records

Supercharge your B2C marketing campaigns with comprehensive consumer database, featuring over 269 million verified US consumer records. Our 20+ year data expertise delivers higher quality and more extensive coverage than competitors.

Core Database Statistics

Consumer Records: Over 269 million

Email Addresses: Over 160 million (verified and deliverable)

Phone Numbers: Over 76 million (mobile and landline)

Mailing Addresses: Over 116,000,000 (NCOA processed)

Geographic Coverage: Complete US (all 50 states)

Compliance Status: CCPA compliant with consent management

Targeting Categories Available

Demographics: Age ranges, education levels, occupation types, household composition, marital status, presence of children, income brackets, and gender (where legally permitted)

Geographic: Nationwide, state-level, MSA (Metropolitan Service Area), zip code radius, city, county, and SCF range targeting options

Property & Dwelling: Home ownership status, estimated home value, years in residence, property type (single-family, condo, apartment), and dwelling characteristics

Financial Indicators: Income levels, investment activity, mortgage information, credit indicators, and wealth markers for premium audience targeting

Lifestyle & Interests: Purchase history, donation patterns, political preferences, health interests, recreational activities, and hobby-based targeting

Behavioral Data: Shopping preferences, brand affinities, online activity patterns, and purchase timing behaviors

Multi-Channel Campaign Applications

Deploy across all major marketing channels:

Email marketing and automation

Social media advertising

Search and display advertising (Google, YouTube)

Direct mail and print campaigns

Telemarketing and SMS campaigns

Programmatic advertising platforms

Data Quality & Sources

Our consumer data aggregates from multiple verified sources:

Public records and government databases

Opt-in subscription services and registrations

Purchase transaction data from retail partners

Survey participation and research studies

Online behavioral data (privacy compliant)

Technical Delivery Options

File Formats: CSV, Excel, JSON, XML formats available

Delivery Methods: Secure FTP, API integration, direct download

Processing: Real-time NCOA, email validation, phone verification

Custom Selections: 1,000+ selectable demographic and behavioral attributes

Minimum Orders: Flexible based on targeting complexity

Unique Value Propositions

Dual Spouse Targeting: Reach both household decision-makers for maximum impact

Cross-Platform Integration: Seamless deployment to major ad platforms

Real-Time Updates: Monthly data refreshes ensure maximum accuracy

Advanced Segmentation: Combine multiple targeting criteria for precision campaigns

Compliance Management: Built-in opt-out and suppression list management

Ideal Customer Profiles

E-commerce retailers seeking customer acquisition

Financial services companies targeting specific demographics

Healthcare organizations with compliant marketing needs

Automotive dealers and service providers

Home improvement and real estate professionals

Insurance companies and agents

Subscription services and SaaS providers

Performance Optimization Features

Lookalike Modeling: Create audiences similar to your best customers

Predictive Scoring: Identify high-value prospects using AI algorithms

Campaign Attribution: Track performance across multiple touchpoints

A/B Testing Support: Split audiences for campaign optimization

Suppression Management: Automatic opt-out and DNC compliance

Pricing & Volume Options

Flexible pricing structures accommodate businesses of all sizes:

Pay-per-record for small campaigns

Volume discounts for large deployments

Subscription models for ongoing campaigns

Custom enterprise pricing for high-volume users

Data Compliance & Privacy

VIA.tools maintains industry-leading compliance standards:

CCPA (California Consumer Privacy Act) compliant

CAN-SPAM Act adherence for email marketing

TCPA compliance for phone and SMS campaigns

Regular privacy audits and data governance reviews

Transparent opt-out and data deletion processes

Getting Started

Our data specialists work with you to:

1. Define your target audience criteria

2. Recommend optimal data selections

3. Provide sample data for testing

4. Configure delivery methods and formats

5. Implement ongoing campaign optimization

Why We Lead the Industry

With over two decades of data industry experience, we combine extensive database coverage with advanced targeting capabilities. Our commitment to data quality, compliance, and customer success has made us the preferred choice for businesses seeking superior B2C marketing performance.

Contact our team to discuss your specific targeting requirements and receive custom pricing for your marketing objectives.

Zambia Imports of silkworm cocoons suitable for reeling from China was US$559 during 2024, according to the United Nations COMTRADE database on international trade. Zambia Imports of silkworm cocoons suitable for reeling from China - data, historical chart and statistics - was last updated on November of 2025.

Comprehensive dataset containing 35 verified Ideal locations in Ukraine with complete contact information, ratings, reviews, and location data.

The aim of the Data Rescue & Curation Best Practices Guide is to provide an accessible and hands-on approach to handling data rescue and digital curation of at-risk data for use in secondary research. We provide a set of examples and workflows for addressing common challenges with social science survey data that can be applied to other social and behavioural research data. The goal of this guide and set of workflows presented is to improve librarians’ and data curators’ skills in providing access to high-quality, well-documented, and reusable research data. The aspects of data curation that are addressed throughout this guide are adopted from long-standing data library and archiving practices, including: documenting data using standard metadata, file and data organization; using open and software-agnostic formats; and curating research data for reuse.

Success.ai’s B2B Company Data API provides direct, on-demand access to in-depth firmographic insights for over 70 million companies worldwide. Covering key attributes such as industry classification, company size, revenue ranges, and geographic footprints, this API ensures your sales, marketing, and strategic planning efforts are informed by accurate, continuously updated, and AI-validated data.

Whether you’re evaluating new markets, refining your ICP (Ideal Customer Profile), or enhancing ABM campaigns, Success.ai’s B2B Company Data API delivers the intelligence needed to target the right organizations at the right time. Supported by our Best Price Guarantee, this solution empowers you to make data-driven decisions and gain a competitive edge in a complex global marketplace.

Why Choose Success.ai’s B2B Company Data API?

1. Comprehensive Global Coverage

   • Access profiles of over 70 million companies spanning multiple industries, sectors, and regions.
   • Confidently enter new markets, identify niche segments, and discover growth opportunities across the globe.

2. AI-Validated Accuracy

   • Benefit from 99% data accuracy through AI-driven validation, ensuring every insight is reliable and actionable.
   • Trust that your decisions are backed by current, high-quality information, minimizing risk and guesswork.

3. Continuous Data Updates

   • Real-time refreshes keep you aligned with evolving market conditions, organizational changes, and industry dynamics.
   • Always operate with the most relevant data, ensuring your outreach and strategies remain timely and impactful.

4. Ethical and Compliant

   • Fully adheres to GDPR, CCPA, and other global data privacy regulations, ensuring responsible and lawful data usage for all applications.

Data Highlights:

• 70M+ Verified Company Profiles: Leverage a vast database to discover new accounts, refine targeting, and guide strategic initiatives.
• Firmographic Insights: Gain visibility into industry classifications, company sizes, revenue tiers, and regional footprints.
• Continuously Updated: Stay current with market expansions, mergers, and new entrants, seizing opportunities early.
• Best Price Guarantee: Optimize ROI by accessing top-tier data at the most competitive prices on the market.

Key Features of the B2B Company Data API:

1. On-Demand Data Enrichment

   • Instantly enhance CRM records or marketing databases with verified company profiles, eliminating guesswork.
   • Maintain data hygiene and ensure teams always work with accurate, current intelligence.

2. Advanced Filtering and Query Capabilities

   • Query the API to segment companies by industry, location, employee count, or revenue.
   • Zero in on the precise accounts that match your ideal customer profile, improving conversion and engagement rates.

3. Real-Time Validation and Reliability

   • Rely on continuous data refreshes and AI validation for impeccable data integrity.
   • Reduce wasted effort and improve decision-making backed by trustworthy insights.

4. Scalable and Flexible Integration

   • Seamlessly integrate the API into CRMs, analytics tools, or marketing platforms, streamlining workflows.
   • Adjust parameters as market conditions evolve, ensuring your data needs always match your strategic priorities.

Strategic Use Cases:

1. Account-Based Marketing (ABM)

   • Identify high-value accounts aligned with your ICP using firmographic data.
   • Deliver personalized outreach, increasing engagement, deal size, and overall ABM success.

2. Market Expansion and Product Launches

   • Enter new markets with confidence by identifying industry leaders, rising players, and underserved segments.
   • Validate product-market fit and refine go-to-market strategies using data-driven insights.

3. Competitive Benchmarking and Analysis

   • Monitor industry landscapes and track competitor growth to anticipate trends and pivot strategies proactively.
   • Stay ahead of market shifts by aligning solutions with evolving customer needs.

4. Partner and Supplier Sourcing

   • Discover reliable partners, suppliers, or distributors based on firmographic filters.
   • Strengthen supply chains, reduce risks, and ensure stable growth through informed partner selection.

Why Choose Success.ai?

1. Best Price Guarantee

   • Access premium-quality B2B company data at industry-leading prices, maximizing ROI for data-driven initiatives.

2. Seamless Integration

   • Incorporate the API into existing workflows easily, eliminating manual data imports and siloed processes.

3. Data Accuracy with AI Validation

   • Rely on 99% accuracy to guide data-driven choices, refine targeting, and improve conversion rates.

4. Customizable and Scalable Solutions

   • Tailor datasets to focus on particular industries, regions, or company sizes, adapting as your goals shift.

Additi...

Comprehensive dataset containing 104 verified Supermercado Ideal locations in Brazil with complete contact information, ratings, reviews, and location data.

Ideal S A Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

The Storms dataset, a subset of the NOAA (National Oceanic and Atmospheric Administration) Atlantic hurricane database best track data, encompasses information about tropical storms measured at different time points over the years. The dataset contains 13 variables, including:  name: The name of the tropical storm.  year: The year in which the storm occurred.  month: The month in which the storm occurred.  day: The day on which the storm occurred.  hour: The hour at which the storm was recorded.  lat: Latitude coordinates of the storm.  long: Longitude coordinates of the storm.  status: The status of the storm (e.g., tropical depression, tropical storm, hurricane).  category: The category of the storm.  wind: Wind speed associated with the storm.  pressure: Atmospheric pressure associated with the storm.  tropicalstorm_force_diameter: Diameter of tropical storm force winds.  hurricane_force_diameter: Diameter of hurricane-force winds.

If you found the dataset useful, your upvote will help others discover it. Thanks for your support!

This dataset simulates customer behavior for a fictional telecommunications company. It contains demographic information, account details, services subscribed to, and whether the customer ultimately churned (stopped using the service) or not. The data is synthetically generated but designed to reflect realistic patterns often found in telecom churn scenarios.

Purpose:

The primary goal of this dataset is to provide a clean and straightforward resource for beginners learning about:

• Exploratory Data Analysis (EDA): Understanding customer characteristics and identifying potential drivers of churn through visualization and statistical summaries.
• Data Preprocessing: Handling categorical features (like converting text to numbers) and scaling numerical features.
• Classification Modeling: Building and evaluating simple machine learning models (like Logistic Regression or Decision Trees) to predict customer churn.

Features:

The dataset includes the following columns:

• CustomerID: Unique identifier for each customer.
• Age: Customer's age in years.
• Gender: Customer's gender (Male/Female).
• Location: General location of the customer (e.g., New York, Los Angeles).
• SubscriptionDurationMonths: How many months the customer has been subscribed.
• MonthlyCharges: The amount the customer is charged each month.
• TotalCharges: The total amount the customer has been charged over their subscription period.
• ContractType: The type of contract the customer has (Month-to-month, One year, Two year).
• PaymentMethod: How the customer pays their bill (e.g., Electronic check, Credit card).
• OnlineSecurity: Whether the customer has online security service (Yes, No, No internet service).
• TechSupport: Whether the customer has tech support service (Yes, No, No internet service).
• StreamingTV: Whether the customer has TV streaming service (Yes, No, No internet service).
• StreamingMovies: Whether the customer has movie streaming service (Yes, No, No internet service).
• Churn: (Target Variable) Whether the customer churned (1 = Yes, 0 = No).

Data Quality:

This dataset is intentionally clean with no missing values, making it easy for beginners to focus on analysis and modeling concepts without complex data cleaning steps.

Inspiration:

Understanding customer churn is crucial for many businesses. This dataset provides a sandbox environment to practice the fundamental techniques used in churn analysis and prediction.

This data study includes South African Social Accounting Matrix (SAM) for the year 2009. The national SAM is built using official supply-use tables, national accounts, state budgets, and balance of payments, and so provides a detailed representation of the South African economy. It separates 49 activities and 85 commodities; labor is disaggregated by education level; and households by per capita expenditure deciles. Information on labor is d rawn from the 2009 Quarterly Labor Force Survey and on households from the 2005 Income and Expenditure Survey. Finally, the SAM identifies government, investment and foreign accounts. It is therefore an ideal database for conducting economywide impact assessments, including SAM-based multiplier analysis and computable general equilibrium (CGE) modeling.

This data set contains enthalpies of formation, entropies, heat capacities, and thermal enthalpies for about 400 compounds available in the NIST TRC SOURCE database. The enthalpies of formation are computed using the ab initio-based protocol reported in the references below. The other properties are calculated by statistical thermodynamics using the "rigid rotor - harmonic oscillator" approximation. The conformational contributions are found by the Gibbs energy averaging of the properties of the conformers.

The Tufts Face Database is a comprehensive collection of human face images, ideal for facial recognition, biometric verification, and computer vision model training. It includes diverse data by ethnicity, age, gender, and region for robust AI development.

The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image. It is a good database for people who want to try learning techniques and pattern recognition methods on real-world data while spending minimal efforts on preprocessing and formatting. The original black and white (bilevel) images from NIST were size normalized to fit in a 20x20 pixel box while preserving their aspect ratio. The resulting images contain grey levels as a result of the anti-aliasing technique used by the normalization algorithm. the images were centered in a 28x28 image by computing the center of mass of the pixels, and translating the image so as to position this point at the center of the 28x28 field. With some classification methods (particuarly template-based methods, such as SVM and K-nearest neighbors),

Summary of the utilized cancer datasets.

Context

Recommendation systems are used everywhere now a days. Netflix , Amazon Prime , YouTube , Online shopping sites etc. Datasets like this are great way to start working on Recommendation system. The Dataset was created from the official API provied by TMDB

Content

What's inside is more than just rows and columns. This is the dataset for 10000 Popular movies based on the TMDB ratings. Ideal database to start off with Recommendation algorithms.

Origin

The code which was used to extract this dataset can be found here - Creating Dataset of top 10000 popular movies

Update

Added Overview , Revenue , Runtime, tagline column for each movie.