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Flame:一个用于在生产环境中进行模型开发、托管和使用的开源框架。

Flame: an open source framework for model development, hosting, and usage in production environments.

作者信息

Pastor Manuel, Gómez-Tamayo José Carlos, Sanz Ferran

机构信息

Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences, Hospital del Mar Medical Research Institute (IMIM), Universitat Pompeu Fabra, Barcelona, Spain.

出版信息

J Cheminform. 2021 Apr 19;13(1):31. doi: 10.1186/s13321-021-00509-z.

Abstract

This article describes Flame, an open source software for building predictive models and supporting their use in production environments. Flame is a web application with a web-based graphic interface, which can be used as a desktop application or installed in a server receiving requests from multiple users. Models can be built starting from any collection of biologically annotated chemical structures since the software supports structural normalization, molecular descriptor calculation, and machine learning model generation using predefined workflows. The model building workflow can be customized from the graphic interface, selecting the type of normalization, molecular descriptors, and machine learning algorithm to be used from a panel of state-of-the-art methods implemented natively. Moreover, Flame implements a mechanism allowing to extend its source code, adding unlimited model customization. Models generated with Flame can be easily exported, facilitating collaborative model development. All models are stored in a model repository supporting model versioning. Models are identified by unique model IDs and include detailed documentation formatted using widely accepted standards. The current version is the result of nearly 3 years of development in collaboration with users from the pharmaceutical industry within the IMI eTRANSAFE project, which aims, among other objectives, to develop high-quality predictive models based on shared legacy data for assessing the safety of drug candidates.

摘要

本文介绍了Flame,一款用于构建预测模型并支持其在生产环境中使用的开源软件。Flame是一个具有基于网页的图形界面的网络应用程序,既可以用作桌面应用程序,也可以安装在接收多个用户请求的服务器中。由于该软件支持结构归一化、分子描述符计算以及使用预定义工作流程生成机器学习模型,因此可以从任何经过生物学注释的化学结构集合开始构建模型。可以从图形界面定制模型构建工作流程,从本地实现的一系列先进方法中选择要使用的归一化类型、分子描述符和机器学习算法。此外,Flame实现了一种机制,允许扩展其源代码,添加无限制的模型定制。使用Flame生成的模型可以轻松导出,便于进行协作式模型开发。所有模型都存储在支持模型版本控制的模型存储库中。模型由唯一的模型ID标识,并包含使用广泛接受的标准格式化的详细文档。当前版本是与制药行业的用户在IMI eTRANSAFE项目中合作近3年的成果,该项目的目标之一是基于共享的遗留数据开发高质量的预测模型,以评估候选药物的安全性。

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