Title :
Geometrical probability approach for analysis of 3D chromatin structure in interphase cell nuclei
Author :
Gladilin, E. ; Goetze, S. ; Mateos-Langerak, J. ; van Driel, R. ; Rohr, K. ; Eils, R.
Author_Institution :
Theor. Bioinformatics, German Cancer Res. Center, Heidelberg
Abstract :
Investigation of 3D chromatin structure in interphase cell nuclei is important for the understanding of genome function. For a reconstruction of the 3D architecture of the human genome, systematic fluorescent in situ hybridization in combination with 3D confocal laser scanning microscopy is applied. The position of two or three genomic loci plus the overall nuclear shape were simultaneously recorded, resulting in statistical series of pair and triple loci combinations probed along the human chromosome 1 q-arm. For interpretation of statistical distributions of geometrical features (e.g. distances, angles, etc.) resulting from finite point sampling experiments, a Monte-Carlo-based approach to numerical computation of geometrical probability density functions (PDFs) for arbitrarily-shaped confined spatial domains is developed. Simulated PDFs are used as bench marks for evaluation of experimental PDFs and quantitative analysis of dimension and shape of probed 3D chromatin regions. Preliminary results of our numerical simulations show that the proposed numerical model is capable to reproduce experimental observations, and support the assumption of confined random folding of 3D chromatin fiber in interphase cell nuclei
Keywords :
Monte Carlo methods; biology computing; cellular biophysics; genetics; sampling methods; statistical distributions; 3D chromatin structure analysis; 3D confocal laser scanning microscopy; Monte-Carlo approach; finite point sampling; genome function; geometrical probability approach; geometrical probability density functions; interphase cell nuclei; statistical distributions; Bioinformatics; Biological cells; Distributed computing; Fluorescence; Genomics; Humans; Microscopy; Sampling methods; Shape; Statistical distributions;
Conference_Titel :
Computational Intelligence and Bioinformatics and Computational Biology, 2007. CIBCB '07. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0710-9
DOI :
10.1109/CIBCB.2007.4221214