Towards the genomic sequence code of DNA fragility for machine learning
Genomic DNA breakages and the subsequent insertion and deletion mutations are important contributors to genome instability and linked diseases. Unlike the research in point mutations, the relationship between DNA sequence context and the propensity for strand breaks remains elusive. Here, by analyzi...
Hoofdauteurs: | Pflughaupt, P, Abdullah, A, Masuda, K, Sahakyan, A |
---|---|
Formaat: | Journal article |
Taal: | English |
Gepubliceerd in: |
Oxford University Press
2024
|
Gelijkaardige items
-
Towards the genomic sequence code of DNA fragility
door: Pflughaupt, PK
Gepubliceerd in: (2024) -
Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
door: Masuda, K, et al.
Gepubliceerd in: (2024) -
Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
door: Kairi Masuda, et al.
Gepubliceerd in: (2024-08-01) -
Generalised interrelations among mutation rates drive the genomic compliance of Chargaff's second parity rule
door: Pflughaupt, P, et al.
Gepubliceerd in: (2023) -
Machine learning model for sequence-driven DNA G-quadruplex formation
door: Sahakyan, A, et al.
Gepubliceerd in: (2017)