Mark Barash , Dennis McNevin , Vladimir Fedorenko , Pavel Giverts
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Machine learning applications in forensic DNA profiling: A critical review
Machine learning (ML) is a range of powerful computational algorithms capable of generating predictive models via intelligent autonomous analysis of relatively large and often unstructured data. ML has become an integral part of our daily lives with a plethora of applications, including web, business, automotive industry, clinical diagnostics, scientific research, and more recently, forensic science. In the field of forensic DNA, the manual analysis of complex data can be challenging, time-consuming, and error-prone. The integration of novel ML-based methods may aid in streamlining this process while maintaining the high accuracy and reproducibility required for forensic tools. Due to the relative novelty of such applications, the forensic community is largely unaware of ML capabilities and limitations. Furthermore, computer science and ML professionals are often unfamiliar with the forensic science field and its specific requirements. This manuscript offers a brief introduction to the capabilities of machine learning methods and their applications in the context of forensic DNA analysis and offers a critical review of the current literature in this rapidly developing field.
期刊介绍:
Forensic Science International: Genetics is the premier journal in the field of Forensic Genetics. This branch of Forensic Science can be defined as the application of genetics to human and non-human material (in the sense of a science with the purpose of studying inherited characteristics for the analysis of inter- and intra-specific variations in populations) for the resolution of legal conflicts.
The scope of the journal includes:
Forensic applications of human polymorphism.
Testing of paternity and other family relationships, immigration cases, typing of biological stains and tissues from criminal casework, identification of human remains by DNA testing methodologies.
Description of human polymorphisms of forensic interest, with special interest in DNA polymorphisms.
Autosomal DNA polymorphisms, mini- and microsatellites (or short tandem repeats, STRs), single nucleotide polymorphisms (SNPs), X and Y chromosome polymorphisms, mtDNA polymorphisms, and any other type of DNA variation with potential forensic applications.
Non-human DNA polymorphisms for crime scene investigation.
Population genetics of human polymorphisms of forensic interest.
Population data, especially from DNA polymorphisms of interest for the solution of forensic problems.
DNA typing methodologies and strategies.
Biostatistical methods in forensic genetics.
Evaluation of DNA evidence in forensic problems (such as paternity or immigration cases, criminal casework, identification), classical and new statistical approaches.
Standards in forensic genetics.
Recommendations of regulatory bodies concerning methods, markers, interpretation or strategies or proposals for procedural or technical standards.
Quality control.
Quality control and quality assurance strategies, proficiency testing for DNA typing methodologies.
Criminal DNA databases.
Technical, legal and statistical issues.
General ethical and legal issues related to forensic genetics.