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ASCEND is specifically designed for preclinical disease biology research
The platform is built by scientists for scientists to unravel disease biology, elevate decision-making, uncover novelty, and increase experimental productivity. We...
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Thank you for your interest in creating an account! Please email support@benchsci.com if you have any questions! 1. Go to signup/login page: app.benchsci.com Check out this article to learn more about eligibility to sign up for ...
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Access to the platform is dependent on the email address that you use to sign in. Typically, we rely on the domain of your institutional email address to determine eligibility. Scientists at academic and non-profit institutions can ac...
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ASCEND's web-based applications work on most modern browsers We support ECMAScript 6 (ES6 2015) Supported browsers: Google Chrome (recommended) Microsoft Edge Mozilla Firefox Safari If you ever experience strange behaviour, try ...
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Our users include a wide range of scientists in academia and industry from varying research backgrounds and experience More than 50 ,000 scientists at more than 4,500 institutions , including 16 top 20 pharma companies, use our technology t...
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Scientists can log into the ASCEND by BenchSci platform using email/password or through single-sign-on (SSO) 1. If you work for a company with an enterprise license — click your logo here to log in now: 2. If your logo is not listed, v...
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Similar to any web-based platform, a browser refresh or computer restart may fix the problem Here are some things you could try if you are having trouble loading a page, or are experiencing strange behaviour on the website: Try logging out a...
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We are happy to hear that the ASCEND by BenchSci platform has been useful for your research! Users can reference ASCEND the same way you would reference any website or database using your citation style of choice such as MLA or APA ...
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It's big. And it's only getting bigger! BenchSci has the world’s most powerful and comprehensive biomedical experiment-focused dataset and ontology, built using proprietary machine learning models that understand experiments like a Ph.D. sci...
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We analyze both open- and closed-access publications All of our open-access content includes articles published on PubMed Central within the last 15 years, including many papers that are subject to the National Institute of Health (NIH) 2...