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D Drasdo

Publications and source records attributed to D Drasdo.

6 recordsLinked to original sources
PubMed2006

Individual cell-based models of the spatial-temporal organization of multicellular systems--achievements and limitations.

Computational approaches of multicellular assemblies have reached a stage where they may contribute to unveil the processes that underlie the organization of tissues and multicellular aggregates. In this article, we briefly review and present some new results on a number of 3D lattice free individual cell-based mathematical models of epithelial cell populations. The models we consider here are parameterized by bio-physical and cell-biological quantities on the level of an individual cell. Eventually, they aim at predicting the dynamics of the biological processes on the tissue level. We focus on a number of systems, the growth of cell populations in vitro, and the spatial-temporal organization of regenerative tissues. For selected examples we compare different model approaches and show that the qualitative results are robust with respect to many model details. Hence, for the qualitative features and largely for the quantitative features many model details do not matter as long as characteristic biological features and mechanisms are correctly represented. For a quantitative prediction, the control of the bio-physical and cell-biological parameters on the molecular scale has to be known. At this point, slide-based cytometry may contribute. It permits to track the fate of cells and other tissue subunits in time and validated the organization processes predicted by the mathematical models.

Animals↗
PubMed2000

Buckling instabilities of one-layered growing tissues.

Growth and folding in one-layered model tissue sheets are studied in a stochastic, lattice-free single cell model which considers the discrete cellular structure of the tissue, and in a coarse grained analytical approach. The polarity of the one-layered tissue is considered by a bending term. Cell division gives rise to a locally increasing metric. An exponential and a power-law growth regime are identified. In both regimes, folding occurs as soon as the bending contribution becomes too small to compensate the destabilizing effect of the cell proliferation. The potential biological relevance is discussed.

Algorithms↗
PubMed2000

Modeling the interplay of generic and genetic mechanisms in cleavage, blastulation, and gastrulation.

Early development of multicellular organisms is marked by a rapid initial increase in their cell numbers, accompanied by spectacular morphogenetic processes leading to the gradual formation of organs of characteristic shapes. During morphogenesis, through differentiation under strict genetic control, cells become more and more specialized. Morphogenesis also requires coordinated cell movement and elaborate interactions between cells, governed by fundamental physical or generic principles. As a consequence, early development must rely on an intricate interplay of generic and genetic mechanisms. We present the results of computer simulations of the first nontrivial morphogenetic transformations in the life of multicellular organisms: initial cleavages, blastula formation, and gastrulation. The same model, which is based on the physical properties of individual cells and their interactions, describes all these processes. The genetic code determines the values of the model parameters. The model accurately reproduces the major steps of early development. It predicts that physical constraints strongly influence the timing of gastrulation. Gastrulation must occur prior to the appearance of dynamical instability, which would destabilize and eventually derail normal development. Within our model, to avoid the instability, we suddenly change the values of some of the model parameters. We interpret this change as a consequence of specific gene activity. After changing the physical characteristics of some cells, normal development resumes, and gastrulation proceeds.

Algorithms↗
PubMed1998

A statistical theory of sequence alignment with gaps.

A statistical theory of local alignment algorithms with gaps is presented. Both the linear and logarithmic phases, as well as the phase transition separating the two phases, are described in a quantitative way. Markov sequences without mutual correlations are shown to have scale-invariant alignment statistics. Deviations from scale invariance indicate the presence of mutual correlations detectable by alignment algorithms. Conditions are obtained for the optimal detection of a class of mutual sequence correlations.

Algorithms↗
PubMedDate not supplied

Scaling laws and similarity detection in sequence alignment with gaps.

We study the problem of similarity detection by sequence alignment with gaps, using a recently established theoretical framework based on the morphology of alignment paths. Alignments of sequences without mutual correlations are found to have scale-invariant statistics. This is the basis for a scaling theory of alignments of correlated sequences. Using a simple Markov model of evolution, we generate sequences with well-defined mutual correlations and quantify the fidelity of an alignment in an unambiguous way. The scaling theory predicts the dependence of the fidelity on the alignment parameters and on the statistical evolution parameters characterizing the sequence correlations. Specific criteria for the optimal choice of alignment parameters emerge from this theory. The results are verified by extensive numerical simulations.

Algorithms↗