Global App Testing
Global App Testing (GAT) allows tech teams to test in over 189 countries with over 60,000+ professional testers who use real devices and environments.
Enhance your testing process and increase release quality and speed whilst improving budget efficiency via the GAT platform, which is fully integrated to work seamlessly with your existing DevOps or CI/CD tools.
Whether you are looking for full time QA support, or to manage spikes in your release cycles, the GAT integration-led approach empowers you to manage your entire testing workflow from test launch to results analysis without leaving your existing tooling (such as Github, Jira, Testrail etc).
Through our integrated platform, we enable unscripted exploratory testing and scripted functional test case execution to be embedded within your CI/CD and SDLC processes, providing the perfect synergy with your automation testing tools.
Test results are returned in real time. Start receiving results in as little as 15 minutes with a full bug report delivered within a few hours, enabling quick feedback on critical issues and edge cases.
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Twilio
Use the language you already love to prototype ideas quickly, develop production-ready communications applications, and run serverless applications on one API-powered platform.
Twilio is a single fully-programmable platform with flexible APIs for any channel, built-in intelligence, and global infrastructure to support you at scale. Quickly integrate powerful APIs to start building solutions for SMS and WhatsApp messaging, voice, video, and email.
Browse documentation and SDKs in multiple coding languages, including Ruby, Python, PHP, Node.js, java, and C#, or jumpstart your first project with our open source code templates to quickly build production-ready communications apps. Consult our community of over 9 million developers for guidance and inspiration on your next project. Sign up and start building today.
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Partek Flow
Partek bioinformatics software offers robust statistical and visualization capabilities through a user-friendly interface that caters to researchers of varying expertise. This innovation allows users to navigate genomic data with unprecedented speed and ease, truly embodying our motto, "We turn data into discovery®." With pre-installed workflows and pipelines in a simple point-and-click format, even complex NGS and array analyses become accessible to all scientists. Our combination of custom and public statistical algorithms works seamlessly to transform NGS data into valuable biological insights. Engaging visual tools like genome browsers, Venn diagrams, and heat maps illuminate the intricacies of next-generation sequencing and array data with vibrant clarity. Additionally, our team of Ph.D. scientists is always available to provide support for NGS analyses whenever queries arise. Tailored to meet the demanding computational requirements of next-generation sequencing, the software also offers flexible options for installation and user management, ensuring a comprehensive solution for research needs. As a result, users can focus more on their research and less on technical challenges.
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Galaxy
Galaxy serves as an open-source, web-based platform specifically designed for handling data-intensive research in the biomedical field. For newcomers to Galaxy, it is advisable to begin with the introductory materials or explore the available help resources. You can also opt to set up your own instance of Galaxy by following the detailed tutorial and selecting from a vast array of tools available in the tool shed. The current Galaxy instance operates on infrastructure generously supplied by the Texas Advanced Computing Center. Furthermore, additional resources are mainly accessible through the Jetstream2 cloud, facilitated by ACCESS and supported by the National Science Foundation. Users can quantify, visualize, and summarize mismatches present in deep sequencing datasets, as well as construct maximum-likelihood phylogenetic trees. This platform also supports phylogenomic and evolutionary tree construction using multiple sequences, the merging of matching reads into clusters with the TN-93 method, and the removal of sequences from a reference that are within a specified distance of a cluster. Lastly, researchers can perform maximum-likelihood estimations to ascertain gene essentiality scores, making Galaxy a powerful tool for various applications in genomic research.
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