Forensic DNA and bioinformatics
نویسندگان
چکیده
The field of forensic science is increasingly based on biomolecular data and many European countries are establishing forensic databases to store DNA profiles of crime scenes of known offenders and apply DNA testing. The field is boosted by statistical and technological advances such as DNA microarray sequencing, TFT biosensors, machine learning algorithms, in particular Bayesian networks, which provide an effective way of evidence organization and inference. The aim of this article is to discuss the state of art potentialities of bioinformatics in forensic DNA science. We also discuss how bioinformatics will address issues related to privacy rights such as those raised from large scale integration of crime, public health and population genetic susceptibility-to-diseases databases.
منابع مشابه
Impact of allelic dropout on evidential value of forensic DNA profiles using RMNE
MOTIVATION Two methods are commonly used to report on evidence carried by forensic DNA profiles: the 'Random Man Not Excluded' (RMNE) approach and the likelihood ratio (LR) approach. It is often claimed a major advantage of the LR method that dropout can be assessed probabilistically. RESULTS In this article, a new RMNE measure is proposed that like-wise accounts for allelic dropout in an obs...
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ورودعنوان ژورنال:
- Briefings in bioinformatics
دوره 8 2 شماره
صفحات -
تاریخ انتشار 2007