[Example] Pipeline Pilot Prediction of Physical Properties of Organic Molecules
Pipeline Pilot
Application of Material Informatics (MI) to the Prediction of Physical Properties of Organic Molecules: Introduction to Case Studies Using the "Pipeline Pilot" Tool.
◇A Case Study on the Application of Material Informatics (MI) to Predict the Physical Properties of Organic Molecules - Utilizing the "Pipeline Pilot" tool, we will introduce a case study estimating the lipophilicity and hydrophilicity of organic molecules. <Overview> - Pipeline Pilot has various functions, including data transfer, access to other software, and database construction using RestAPI. - Efficient and easy use of data significantly lowers the barrier to the introduction of material informatics. - We will present a case study utilizing Pipeline Pilot for machine learning and data collection to estimate the lipophilicity and hydrophilicity of organic molecules. Pipeline Pilot supports a wide range of fields and is a powerful data mining tool that enables data analysis using data processing and machine learning, as well as seamless integration with other applications. 【Features】 ■ Intuitive user interface ■ Support for a wide range of fields ■ Seamless integration with other software *If you have any questions or concerns, please feel free to contact us at sales@wavefront.co.jp.
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basic information
Pipeline Pilot is a data mining tool that enables large-scale data processing and analysis, automation of tasks, and visualization of workflows. It is also an ideal tool for materials informatics. 【Features】 ■ Intuitive user interface ■ Support for a wide range of fields ■ Seamless integration with other software If you have any questions or concerns, please feel free to contact us.
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P5
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Applications/Examples of results
For more details, please feel free to contact us. Wavefront Inc. Sales Department MAIL: sales@wavefront.co.jp
Detailed information
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The features of Pipeline Pilot are: - A platform for data analysis - Pipeline Pilot supports a wide range of fields, including data processing, data analysis using machine learning, and integration with other applications. - It is optimal as a tool for utilizing "materials informatics."
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