The effect of a user selected number of contributors within the LR assignment

[1]  Hinda Haned,et al.  Automated estimation of the number of contributors in autosomal short tandem repeat profiles using a machine learning approach. , 2019, Forensic science international. Genetics.

[2]  Øyvind Bleka,et al.  A comparative study of qualitative and quantitative models used to interpret complex STR DNA profiles. , 2016, Forensic science international. Genetics.

[3]  Jo-Anne Bright,et al.  Population data on the expanded CODIS core STR loci for eleven populations of significance for forensic DNA analyses in the United States. , 2016, Forensic science international. Genetics.

[4]  Jo-Anne Bright,et al.  The effect of varying the number of contributors in the prosecution and alternate propositions. , 2019, Forensic science international. Genetics.

[5]  James Curran,et al.  Searching mixed DNA profiles directly against profile databases. , 2014, Forensic science international. Genetics.

[6]  Duncan A. Taylor,et al.  A sensitivity analysis to determine the robustness of STRmix™ with respect to laboratory calibration. , 2018, Forensic Science International: Genetics.

[7]  Peter Gill,et al.  DNA commission of the International society for forensic genetics: Assessing the value of forensic biological evidence - Guidelines highlighting the importance of propositions. Part II: Evaluation of biological traces considering activity level propositions. , 2020, Forensic science international. Genetics.

[8]  Carissa M Krane,et al.  Empirical analysis of the STR profiles resulting from conceptual mixtures. , 2005, Journal of forensic sciences.

[9]  W R Mayr,et al.  DNA commission of the International Society of Forensic Genetics: Recommendations on the interpretation of mixtures. , 2006, Forensic science international.

[10]  John Buckleton,et al.  Uncertainty in the number of contributors for the European Standard Set of loci. , 2014, Forensic science international. Genetics.

[11]  Klaas Slooten.  Accurate assessment of the weight of evidence for DNA mixtures by integrating the likelihood ratio. , 2017, Forensic science international. Genetics.

[12]  Duncan Taylor,et al.  The interpretation of single source and mixed DNA profiles. , 2013, Forensic science international. Genetics.

[13]  Duncan Taylor,et al.  Developing allelic and stutter peak height models for a continuous method of DNA interpretation. , 2013, Forensic science international. Genetics.

[14]  Duncan Taylor,et al.  Evaluation of forensic genetics findings given activity level propositions: A review. , 2018, Forensic science international. Genetics.

[15]  Duncan A. Taylor,et al.  Internal validation of STRmix™ - A multi laboratory response to PCAST. , 2018, Forensic science international. Genetics.

[16]  Jo-Anne Bright,et al.  The effect of the uncertainty in the number of contributors to mixed DNA profiles on profile interpretation. , 2014, Forensic science international. Genetics.

[17]  F Taroni,et al.  Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method. , 2012, Forensic science international. Genetics.

[18]  Bruce Budowle,et al.  NIST interlaboratory studies involving DNA mixtures (MIX13): A modern analysis. , 2018, Forensic science international. Genetics.

[19]  Thore Egeland,et al.  About the number of contributors to a forensic sample. , 2016, Forensic science international. Genetics.

[20]  K Slooten,et al.  Contributors are a nuisance (parameter) for DNA mixture evidence evaluation. , 2018, Forensic science international. Genetics.

[21]  Michael A. Marciano,et al.  PACE: Probabilistic Assessment for Contributor Estimation- A machine learning-based assessment of the number of contributors in DNA mixtures. , 2017, Forensic science international. Genetics.

[22]  H Haned,et al.  The predictive value of the maximum likelihood estimator of the number of contributors to a DNA mixture. , 2011, Forensic science international. Genetics.

[23]  William C. Thompson,et al.  Using graphical probability analysis (Bayes Nets) to evaluate a conditional DNA inclusion , 2011 .

[24]  Duncan Taylor,et al.  Performance of a method for weighting a range in the number of contributors in probabilistic genotyping. , 2020, Forensic science international. Genetics.

[25]  Duncan Taylor,et al.  Interpreting forensic DNA profiling evidence without specifying the number of contributors. , 2014, Forensic science international. Genetics.

[26]  T. Egeland,et al.  Estimating the number of contributors to a DNA profile , 2003, International Journal of Legal Medicine.

[27]  Christophe Champod,et al.  A template for constructing Bayesian networks in forensic biology cases when considering activity level propositions. , 2018, Forensic science international. Genetics.

[28]  Muriel Medard,et al.  NOCIt: a computational method to infer the number of contributors to DNA samples analyzed by STR genotyping. , 2015, Forensic science international. Genetics.

[29]  Jo-Anne Bright,et al.  Uncertainty in the number of contributors in the proposed new CODIS set. , 2015, Forensic science international. Genetics.

[30]  Hinda Haned,et al.  Estimating the Number of Contributors to Forensic DNA Mixtures: Does Maximum Likelihood Perform Better Than Maximum Allele Count? , 2011, Journal of forensic sciences.

[31]  Duncan Taylor,et al.  The 'factor of two' issue in mixed DNA profiles. , 2014, Journal of theoretical biology.

[32]  Susan Pope,et al.  Is it to the advantage of a defendant to infer a greater number of contributors to a questioned sample than is necessary to explain the observed DNA profile? , 2014, Science & justice : journal of the Forensic Science Society.

[33]  John M Butler,et al.  NIST interlaboratory studies involving DNA mixtures (MIX05 and MIX13): Variation observed and lessons learned. , 2018, Forensic science international. Genetics.

[34]  Catherine M. Grgicak,et al.  A large-scale dataset of single and mixed-source short tandem repeat profiles to inform human identification strategies: PROVEDIt. , 2018, Forensic science international. Genetics.