Forensic Genetic Approaches for Identification of Human Skeletal Remains - Challenges, Best Practices, and Emerging Technologies (Hardcover)

Forensic Genetic Approaches for Identification of Human Skeletal Remains: Challenges, Best Practices, and Emerging Technologies provides best practices on processing bone samples for DNA testing. The book outlines forensic genetics tools that are available for the identification of skeletal remains in contemporary casework and historical/archaeological investigations. Although the book focuses primarily on the use of DNA for direct identification or kinship analyses, it also highlights complementary disciplines often used in concert with genetic data to make positive identifications, such as forensic anthropology, forensic odontology, and forensic art/sculpting. Unidentified human remains are often associated with tragic events, such as fires, terrorist attacks, natural disasters, war conflicts, genocide, airline crashes, homicide, and human rights violations under oppressive totalitarian regimes. In these situations, extensive damage to soft tissues often precludes the use of such biological samples in the identification process. In contrast, bone material is the most resilient, viable sample type for DNA testing. DNA recovered from bone often is degraded and in low quantities due to the effects of human decomposition, environmental exposure, and the passage of time. The complexities of bone microstructure and its rigid nature make skeletal remains one of the most challenging sample types for DNA testing.

General

Imprint:	Academic Press Inc
Country of origin:	United States
Release date:	November 2022
First published:	2023
Editors:	Angie Ambers
Dimensions:	191 x 235mm (L x W)
Format:	Hardcover
Pages:	626
ISBN-13:	978-0-12-815766-4
Categories:	Books > Social sciences > General Books > Medicine > Other branches of medicine > Pathology > General Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Genetics (non-medical) > General Promotions
LSN:	0-12-815766-6
Barcode:	9780128157664

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