ChemML: A machine learning and informatics program package for the analysis, mining, and modeling of chemical and materials data. (30th January 2020)

• Record Type: Journal Article
• Authors: Haghighatlari, Mojtaba; Vishwakarma, Gaurav; Altarawy, Doaa; Subramanian, Ramachandran; Kota, Bhargava U.; Sonpal, Aditya; Setlur, Srirangaraj; Hachmann, Johannes
• Is Part Of: Wiley interdisciplinary reviews. Volume 10:Number 4(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-01-30
• Subjects: data‐driven research -- data science -- informatics -- machine learning -- program package; Chemistry, Physical and theoretical -- Periodicals; Cheminformatics -- Periodicals; Biochemistry -- Periodicals; 541.220285
• DOI: 10.1002/wcms.1458
• Languages: English
• ISSNs: 1759-0876

Abstract

Abstract: ChemML is an open machine learning (ML) and informatics program suite that is designed to support and advance the data‐driven research paradigm that is currently emerging in the chemical and materials domain. ChemML allows its users to perform various data science tasks and execute ML workflows that are adapted specifically for the chemical and materials context. Key features are automation, general‐purpose utility, versatility, and user‐friendliness in order to make the application of modern data science a viable and widely accessible proposition in the broader chemistry and materials community. ChemML is also designed to facilitate methodological innovation, and it is one of the cornerstones of the software ecosystem for data‐driven in silico research. This article is categorized under: Software > Simulation Methods Computer and Information Science > Chemoinformatics Structure and Mechanism > Computational Materials Science Software > Molecular Modeling Abstract : The ChemML Program Package.