
Intellimas is a no code/low code software platform with a spreadsheet and form UI. Intellimas allows you to build web apps that can completely align with your business process. Intellimas is built for fast data entry, analytics, exception management, and easy retrieval of live data from other systems. The grid UI allows for an easy transition from spreadsheets. This comprehensive view, along with our form view, provide you with the flexibility to handle unlimited use cases.
Intellimas can be deployed on premise or on our cloud platform. Customers typically find many uses for Intellimas after the first rollout. Intellimas comes with configurable dashboards and a full reporting tool so the intelligence is at your fingertips. Revision history, configurable alerts, comprehensive workflow, and much more is available in the configuration engine for building out apps. Bring your simple and complex use cases and build them in Intellimas. It is a top software to replace your mega-spreadsheets and fill enterprise system gaps. Contact us for a demo and ask us about our free trial!
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RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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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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Biohub
Biohub serves as an accessible platform dedicated to advancing the understanding of protein biology. It offers users the ESM model family, which includes ESMC, ESMFold2, and ESM3, alongside interactive tools and resources tailored for developers involved in protein science research. ESMC stands out as a cutting-edge protein language model, meticulously trained on vast amounts of evolutionary sequence data, allowing it to create representations that elucidate key mechanisms underlying protein structure and function. This model facilitates various applications such as functional analysis, predicting structures, designing proteins, and investigating the evolutionary connections among different proteins. Meanwhile, ESMFold2 specializes in predicting high-resolution, all-atom 3D structures of biomolecular complexes from sequences, while offering the option of including multiple sequence alignments to improve accuracy for difficult targets. Additionally, ESM3 takes a holistic approach by simultaneously modeling sequence, structure, and function, thus enabling the generation of innovative proteins through conditioning on a blend of these aspects. This unique integration of tools and models empowers researchers to explore new frontiers in protein science.
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