2010/10/20 by Vladimir A. Trifonov, Vladimir Trifonov, Trifonov, Vladimir +8 · 1 citation
Biochemistry, Genetics and Molecular Biology · Economics, Econometrics and Finance · Mathematics · #Applications (stat.AP) #Complex Systems and Time Series Analysis #Evolution and Genetic Dynamics #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Mathematics #Fractal and DNA sequence analysis #Probability (math.PR) #Quantitative Methods (q-bio.QM) #math.PR #q-bio.QM #stat.AP
paper · pdf · doi:10.48550/arxiv.1010.4328
16 pages, 4 figures
arxiv created 2010/10/20 · openalex publication_date 2010/10/20 · arxiv updated 2010/10/22 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28
Recent developments in extracting and processing biological and clinical data are allowing quantitative approaches to studying living systems. High-throughput sequencing, expression profiles, proteomics, and electronic health records are some examples of such technologies. Extracting meaningful information from those technologies requires careful analysis of the large volumes of data they produce. In this note, we present a set of distributions that commonly appear in the analysis of such data. These distributions present some interesting features: they are discontinuous in the rational numbers, but continuous in the irrational numbers, and possess a certain self-similar (fractal-like) structure. The first set of examples which we present here are drawn from a high-throughput sequencing experiment. Here, the self-similar distributions appear as part of the evaluation of the error rate of the sequencing technology and the identification of tumorogenic genomic alterations. The other examples are obtained from risk factor evaluation and analysis of relative disease prevalence and co-mordbidity as these appear in electronic clinical data. The distributions are also relevant to identification of subclonal populations in tumors and the study of the evolution of infectious diseases, and more precisely the study of quasi-species and intrahost diversity of viral populations.