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Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
- Source :
- Scientific Data, Vol 11, Iss 1, Pp 1-9 (2024)
- Publication Year :
- 2024
- Publisher :
- Nature Portfolio, 2024.
-
Abstract
- Abstract We are witnessing a steep increase in model development initiatives in genomics that employ high-end machine learning methodologies. Of particular interest are models that predict certain genomic characteristics based solely on DNA sequence. These models, however, treat the DNA as a mere collection of four, A, T, G and C, letters, dismissing the past advancements in science that can enable the use of more intricate information from nucleic acid sequences. Here, we provide a comprehensive database of quantum mechanical (QM) and geometric features for all the permutations of 7-meric DNA in their representative B, A and Z conformations. The database is generated by employing the applicable high-cost and time-consuming QM methodologies. This can thus make it seamless to associate a wealth of novel molecular features to any DNA sequence, by scanning it with a matching k-meric window and pulling the pre-computed values from our database for further use in modelling. We demonstrate the usefulness of our deposited features through their exclusive use in developing a model for A->C mutation rates.
- Subjects :
- Science
Subjects
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 11
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- Scientific Data
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.991cf338d304054a75581e99272e63f
- Document Type :
- article
- Full Text :
- https://doi.org/10.1038/s41597-024-03772-5