Papers describing the mathematics, validation and application of DBLR™:
 K. Slooten, Identifying common donors in DNA mixtures, with applications to database searches. Forensic Science International: Genetics. 2017; 26:40-7.
 M. Kruijver, J.-A. Bright, H. Kelly, J. Buckleton, Exploring the probative value of mixed DNA profiles. Forensic Science International: Genetics. 2019; 41: 1-10.
 J.-A. Bright, D. Taylor, Z. Kerr, J. Buckleton, M. Kruijver, The efficacy of DNA mixture to mixture matching. Forensic Science International: Genetics. 2019; 41: 64-71.
 D. Taylor, E. Rowe, M. Kruijver, D. Abarno, J.-A. Bright, J. Buckleton, Inter-sample contamination detection using mixture deconvolution comparison. Forensic Science International: Genetics. 2019; 160-167.
 J.-A. Bright, M. Jones Dukes, S.N. Pugh, I.W. Evett, J.S. Buckleton, Applying calibration to LRs produced by a DNA interpretation software. Australian Journal of Forensic Sciences. 2019; 1-7 https://doi.org/10.1080/00450618.2019.1682668(external link).
 Taylor D, Kruijver M. Combining evidence across multiple mixed DNA profiles for improved resolution of a donor when a common contributor can be assumed. Forensic Science International: Genetics 2020; 49.
 H. Kelly, Z. Kerr, K. Cheng, M. Kruijver, J.-A. Bright, Developmental validation of a software implementation of a flexible framework for the assignment of likelihood ratios for forensic investigations. Forensic Science International: Reports. 2021; Volume 4, 100231 https://www.sciencedirect.com/science/article/pii/S2665910721000621?via%3Dihub(external link)
 M. Kruijver, D. Taylor, J.-A. Bright, Evaluating DNA evidence possibly involving multiple (mixed) samples, common donors and related contributors, Forensic Science International: Genetics. 2021; 54 https://doi.org/10.1016/j.fsigen.2021.102532.