DNA methylation-based forensic age prediction using artificial neural networks and next generation sequencing

Forensic Science International: Genetics

Volumn 28, Issue , 2017, Pages 225-236

  Vidaki, Athina ^a   Ballard, David ^a   Aliferi, Anastasia ^a   Miller, Thomas H ^a   Barron, Leon P ^a   Syndercombe Court, Denise ^a  

^a KING'S COLLEGE LONDON   (United Kingdom)

Author keywords

Artificial neural networks; Chronological age prediction; DNA methylation; Forensic epigenetics; Next generation sequencing

Indexed keywords

DNA;

ACCURACY; AGE DETERMINATION; AGING; ARTICLE; ARTIFICIAL NEURAL NETWORK; BODY FLUID; CPG ISLAND; DNA METHYLATION; EPIGENETIC REPRESSION; FORENSIC GENETICS; GENOME-WIDE ASSOCIATION STUDY; HUMAN; MACHINE LEARNING; MULTIPLE REGRESSION; NEXT GENERATION SEQUENCING; POLYMERASE CHAIN REACTION; PRIORITY JOURNAL; ADULT; AGED; BLOOD; CHEMISTRY; EPIGENETICS; GENETICS; HIGH THROUGHPUT SEQUENCING; MIDDLE AGED; MONOZYGOTIC TWINS; SALIVA;

ADULT; AGED; AGING; CPG ISLANDS; DNA; DNA METHYLATION; EPIGENOMICS; FORENSIC GENETICS; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MACHINE LEARNING; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); SALIVA; TWINS, MONOZYGOTIC;

EID: 85013906307     PISSN: 18724973     EISSN: 18780326     Source Type: Journal    
DOI: 10.1016/j.fsigen.2017.02.009     Document Type: Article

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