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...
Glavni autori: | Pflughaupt, P, Abdullah, A, Masuda, K, Sahakyan, A |
---|---|
Format: | Journal article |
Jezik: | English |
Izdano: |
Oxford University Press
2024
|
Slični predmeti
Slični predmeti
-
Towards the genomic sequence code of DNA fragility
od: Pflughaupt, PK
Izdano: (2024) -
Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
od: Masuda, K, i dr.
Izdano: (2024) -
Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
od: Kairi Masuda, i dr.
Izdano: (2024-08-01) -
Generalised interrelations among mutation rates drive the genomic compliance of Chargaff's second parity rule
od: Pflughaupt, P, i dr.
Izdano: (2023) -
Machine learning model for sequence-driven DNA G-quadruplex formation
od: Sahakyan, A, i dr.
Izdano: (2017)