Towards the genomic sequence code of DNA fragility for machine learning

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...

Deskribapen osoa

Xehetasun bibliografikoak
Egile Nagusiak:	Pflughaupt, P, Abdullah, A, Masuda, K, Sahakyan, A
Formatua:	Journal article
Hizkuntza:	English
Argitaratua:	Oxford University Press 2024

Antzeko izenburuak

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Quantum mechanical electronic and geometric parameters for DNA k-mers as features for machine learning
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nork: Kairi Masuda, et al.
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Generalised interrelations among mutation rates drive the genomic compliance of Chargaff's second parity rule
nork: Pflughaupt, P, et al.
Argitaratua: (2023)

Machine learning model for sequence-driven DNA G-quadruplex formation
nork: Sahakyan, A, et al.
Argitaratua: (2017)

Machine learning model for sequence-driven DNA G-quadruplex formation
nork: Aleksandr B. Sahakyan, et al.
Argitaratua: (2017-11-01)

Decoding the Human Genome: Machine Learning Techniques for DNA Sequencing Analysis
nork: C. Sravani, et al.
Argitaratua: (2023-01-01)

Whole genome experimental maps of DNA G-quadruplexes in multiple species
nork: Marsico, G, et al.
Argitaratua: (2019)

A Fragile Image Watermarking Scheme in DWT Domain Using Chaotic Sequences and Error-Correcting Codes
nork: Andy M. Ramos, et al.
Argitaratua: (2023-03-01)

Classification of fragile states based on machine learning
nork: Li Yuquan, et al.
Argitaratua: (2018-01-01)

BLM prevents instability of structure-forming DNA sequences at common fragile sites.
nork: Hailong Wang, et al.
Argitaratua: (2018-11-01)

Machine Learning and Safe and Inclusive Architecture for Fragile Users
nork: Antonio Magarò, et al.
Argitaratua: (2019-06-01)

Prediction of subsequent fragility fractures: application of machine learning
nork: Mozhdeh Zabihiyeganeh, et al.
Argitaratua: (2024-06-01)

SPLICE: A technique for generating in vitro spliced coding sequences from genomic DNA
nork: Wayne L. Davies, et al.
Argitaratua: (2007-12-01)

Sequencing of Genomic DNA
nork: Ulrich Mahlknecht, et al.
Argitaratua: (1999-09-01)

Mitigating Temporal Fragility in the XY Surface Code
nork: Pei-Kai Tsai, et al.
Argitaratua: (2024-07-01)

Universal Features for the Classification of Coding and Non-Coding DNA Sequences
nork: Nicolas Carels, et al.
Argitaratua: (2009-06-01)

Universal Features for the Classification of Coding and Non-coding DNA Sequences
nork: Nicolas Carels, et al.
Argitaratua: (2009-01-01)

Fragile DNA contributes to repeated evolution
nork: Claudius F. Kratochwil, et al.
Argitaratua: (2019-02-01)

Strand-specific Single-stranded DNA Sequencing (4S-seq) of E. coli genomes
nork: Takahiro Masuda, et al.
Argitaratua: (2019-08-01)

REPETITIVE DNA SEQUENCES IN THE GENOMES OF PLANTS
nork: A. B. Shcherban
Argitaratua: (2015-01-01)

DNA watermarks in non-coding regulatory sequences
nork: Pyka Martin, et al.
Argitaratua: (2009-07-01)

Functions of human non-coding dna sequences
nork: Stupar Milanko, et al.
Argitaratua: (2011-01-01)

Genome-wide identification of coding and non-coding conserved sequence tags in human and mouse genomes
nork: Maggi Giorgio P, et al.
Argitaratua: (2008-06-01)

A machine learning approach for accurate and real-time DNA sequence identification
nork: Yiren Wang, et al.
Argitaratua: (2021-07-01)

Inconsistencies in Neanderthal genomic DNA sequences.
nork: Jeffrey D Wall, et al.
Argitaratua: (2007-10-01)

A New Method to Convert the DNA Sequence of Human to a QR Code
nork: Sadoon Abdullah, et al.
Argitaratua: (2019-12-01)

DNA sequence driven machine learning for modelling replication timing
nork: Ashford, J
Argitaratua: (2023)

A spontaneous ring-opening reaction leads to a repair‐resistant thymine oxidation product in genomic DNA
nork: Sahakyan, A, et al.
Argitaratua: (2019)

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data
nork: Yang, Y, et al.
Argitaratua: (2017)

Machine learning enables detection of early-stage colorectal cancer by whole-genome sequencing of plasma cell-free DNA
nork: Nathan Wan, et al.
Argitaratua: (2019-08-01)

Seismic Fragility Estimation Based on Machine Learning and Particle Swarm Optimization
nork: Qingzhao Kong, et al.
Argitaratua: (2024-04-01)

Rapid in vitro splicing of coding sequences from genomic DNA by isothermal recombination reaction-based PCR
nork: Wenxuan Chen, et al.
Argitaratua: (2016-09-01)

Genetic Code Analysis Toolkit: A novel tool to explore the coding properties of the genetic code and DNA sequences
nork: K. Kraljić, et al.
Argitaratua: (2018-01-01)

DNA topoisomerases participate in fragility of the oncogene RET.
nork: Laura W Dillon, et al.
Argitaratua: (2013-01-01)

Cataloging coding sequence variations in human genome databases.
nork: Hong-Hee Won, et al.
Argitaratua: (2008-01-01)

Machine learning-based detection of immune-mediated diseases from genome-wide cell-free DNA sequencing datasets
nork: Huiwen Che, et al.
Argitaratua: (2022-09-01)

Towards a Measure of Financial Fragility
nork: Tsomocos, D, et al.
Argitaratua: (2007)

Towards a measure of financial fragility
nork: Aspachs, O, et al.
Argitaratua: (2006)

Detecting overlapping coding sequences in virus genomes
nork: Brown Chris M, et al.
Argitaratua: (2006-02-01)