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Analiza możliwości zastosowania metod sztucznej inteligencji w medycynie sądowej

Filipowicz E., Kwiecień J., Kłys M., Filipowicz B.

Bio-Algorithms and Med-Systems

2005

Vol. 1, no. 1/2

3--8

Artykuł opisuje zastosowanie nowych systemów bioinformatycznych w medycynie sądowej. Systemy biometryczne już znalazły zastosowanie między innymi w geometrycznej identyfikacji twarzy. Są one niezbędne w identyfikacji osobowej oraz w poszukiwaniu osób zaginionych. W ostatnich latach nastąpił bardzo szybki rozwój badań nad chromosomem Y, co pozwoliło na postęp w medycynie sądowej. Metody sztucznej inteligencji mogąbyć pomocne w badaniach spornego ojcostwa i ewolucji człowieka. Bioinformatyka oraz metody biologii molekularnej, metody multiplex PCR będą pełnić bardzo ważną funkcję w analizie sądowej DNA oraz w historycznych i genealogicznych badaniach.

This article reviews new bioinformatic systems in forensic medicine. Biometric systems are already used in forensic medicine for face geometry identification. They are necessary in personal identification and missing persons investigations. The field of Y-chromosome analysis and its application to forensic science has undergone rapid improvement in recent years. Artificial Intelligence is usefull in paternity testing and in human evolutionary study. Bioinformatic systems and multiplex PCR assay w ill play an important role in the future of forensic DNA typing and historical and genealogical research.

Sampling Properties of Estimators of Nucleotide Diversity at Discovered snp Sites

Renwick A., Bonnen P. E., Trikka D., Nelson D. L., Chakraborty R., Kimmel M.

International Journal of Applied Mathematics and Computer Science

2003

Vol. 13, no 3

385-394

SNP sites are generally discovered by sequencing regions of the human genome in a limited number of individuals. This may leave SNP sites present in the region, but containing rare mutant nucleotides, undetected. Consequently, estimates of nucleotide diversity obtained from assays of detected SNP sites are biased. In this research we present a statistical model of the SNP discovery process, which is used to evaluate the extent of this bias. This model involves the symmetric Beta distribution of variant frequencies at SNP sites, with an additional probability that there is no SNP at any given site. Under this model of allele frequency distributions at SNP sites, we show that nucleotide diversity is always underestimated. However, the extent of bias does not seem to exceed 10-15% for the analyzed data. We find that our model of allele frequency distributions at SNP sites is consistent with SNP statistics derived based on new SNP data at ATM, BLM, RQL and WRN gene regions. The application of the theory to these new SNP data as well as to the literature data at the LPL gene region indicates that in spite of ascertainment biases, the observed differences of nucleotide diversity across these gene regions are real. This provides interesting evidence concerning the heterogeneity of the rates of nucleotide substitution across the genome.

Single nucleotide polymorphisms applied in statistical inference of population growth

Polański A., Starosolski Z., Świerniak A., Kimmel M.

Biocybernetics and Biomedical Engineering

2003

Vol. 23, no. 4

45-61

We have evaluated probability distributions of estimates of parameters of population growth, based on data on frequencies of alleles of unlinked SNP sites in DNA, modeled with the use of time dependent coalescence process acting together with mutation of a very low intensity. Probability distributions of maximum likelihood estimates of the product parameter of the present population effective size and exponent coefficient, for exponential scenario, have atoms at zero and long tails to the right. For stepwise scenario, log likelihood functions typically exhibit very long lines, covering many decades of the scale, of almost the same value of log likelihood. Observational data from [14] are consistent with the hypothesis of the population growth.