Digital Discovery (DD)
Journal Descriptions
Digital Discovery welcomes both experimental and computational work on all topics related to the acceleration of discovery such as screening, robotics, databases and advanced data analytics, broadly defined, but anchored in chemistry. Digital Discovery is an open access journal that publishes both theoretical and experimental research at the intersection of chemistry, materials science and biotechnology. We focus on the development and application of machine learning, AI and automation tools to unravel scientific problems, and we put data first to ensure reproducibility and faster progress for everyone. The journal publishes research related to chemical, materials, biochemical, biomedical, or biophysical sciences and specific topics include: Artificial intelligence and other high throughput computational methodologies for molecular, materials and formulation design: Computer-assisted retrosynthesis Generative models for scientific design Machine learning classification and regression models Quantum algorithms for quantum simulation and data science as applied to molecular and materials discovery Modern molecular, materials, and biological representations Molecular, Materials and Chemo- and Bio-informatics Methods for Bayesian optimization and design of experiments Advances and applications of interpretable models Image recognition Natural language processing Literature mining tools
Digital Discovery (DD) is :-
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International, Peer-Reviewed, Open Access, Refereed, Chemistry, Data processing, Medical sciences, Machine learning , Online , Bi-Monthly Journal
- UGC Approved, ISSN Approved: P-ISSN E-ISSN: 2635-098X, Established: 2024,
- Provides Crossref DOI
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Indexed in: Scopus, WoS, DOAJ, PubMed
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Not indexed in UGC CARE
