725 research outputs found
Modeling the evolution space of breakage fusion bridge cycles with a stochastic folding process
Breakage-Fusion-Bridge cycles in cancer arise when a broken segment of DNA is duplicated and an end from each copy joined together. This structure then 'unfolds' into a new piece of palindromic DNA. This is one mechanism responsible for the localised amplicons observed in cancer genome data. The process has parallels with paper folding sequences that arise when a piece of paper is folded several times and then unfolded. Here we adapt such methods to study the breakage-fusion-bridge structures in detail. We firstly consider discrete representations of this space with 2-d trees to demonstrate that there are 2^(n(n-1)/2) qualitatively distinct evolutions involving n breakage-fusion-bridge cycles. Secondly we consider the stochastic nature of the fold positions, to determine evolution likelihoods, and also describe how amplicons become localised. Finally we highlight these methods by inferring the evolution of breakage-fusion-bridge cycles with data from primary tissue cancer samples
Hidden breakpoints in genome alignments
During the course of evolution, an organism's genome can undergo changes that
affect the large-scale structure of the genome. These changes include gene
gain, loss, duplication, chromosome fusion, fission, and rearrangement. When
gene gain and loss occurs in addition to other types of rearrangement,
breakpoints of rearrangement can exist that are only detectable by comparison
of three or more genomes. An arbitrarily large number of these "hidden"
breakpoints can exist among genomes that exhibit no rearrangements in pairwise
comparisons.
We present an extension of the multichromosomal breakpoint median problem to
genomes that have undergone gene gain and loss. We then demonstrate that the
median distance among three genomes can be used to calculate a lower bound on
the number of hidden breakpoints present. We provide an implementation of this
calculation including the median distance, along with some practical
improvements on the time complexity of the underlying algorithm.
We apply our approach to measure the abundance of hidden breakpoints in
simulated data sets under a wide range of evolutionary scenarios. We
demonstrate that in simulations the hidden breakpoint counts depend strongly on
relative rates of inversion and gene gain/loss. Finally we apply current
multiple genome aligners to the simulated genomes, and show that all aligners
introduce a high degree of error in hidden breakpoint counts, and that this
error grows with evolutionary distance in the simulation. Our results suggest
that hidden breakpoint error may be pervasive in genome alignments.Comment: 13 pages, 4 figure
MoKCa database - mutations of kinases in cancer
Members of the protein kinase family are amongst the most commonly mutated genes in human cancer, and both mutated and activated protein kinases have proved to be tractable targets for the development of new anticancer therapies The MoKCa database (Mutations of Kinases in Cancer, http://strubiol.icr.ac.uk/extra/mokca) has been developed to structurally and functionally annotate, and where possible predict, the phenotypic consequences of mutations in protein kinases implicated in cancer. Somatic mutation data from tumours and tumour cell lines have been mapped onto the crystal structures of the affected protein domains. Positions of the mutated amino-acids are highlighted on a sequence-based domain pictogram, as well as a 3D-image of the protein structure, and in a molecular graphics package, integrated for interactive viewing. The data associated with each mutation is presented in the Web interface, along with expert annotation of the detailed molecular functional implications of the mutation. Proteins are linked to functional annotation resources and are annotated with structural and functional features such as domains and phosphorylation sites. MoKCa aims to provide assessments available from multiple sources and algorithms for each potential cancer-associated mutation, and present these together in a consistent and coherent fashion to facilitate authoritative annotation by cancer biologists and structural biologists, directly involved in the generation and analysis of new mutational data
Spectral statistics for quantized skew translations on the torus
We study the spectral statistics for quantized skew translations on the
torus, which are ergodic but not mixing for irrational parameters. It is shown
explicitly that in this case the level--spacing distribution and other common
spectral statistics, like the number variance, do not exist in the
semiclassical limit.Comment: 7 pages. One figure, include
Effects of Noise on Ecological Invasion Processes: Bacteriophage-mediated Competition in Bacteria
Pathogen-mediated competition, through which an invasive species carrying and
transmitting a pathogen can be a superior competitor to a more vulnerable
resident species, is one of the principle driving forces influencing
biodiversity in nature. Using an experimental system of bacteriophage-mediated
competition in bacterial populations and a deterministic model, we have shown
in [Joo et al 2005] that the competitive advantage conferred by the phage
depends only on the relative phage pathology and is independent of the initial
phage concentration and other phage and host parameters such as the
infection-causing contact rate, the spontaneous and infection-induced lysis
rates, and the phage burst size. Here we investigate the effects of stochastic
fluctuations on bacterial invasion facilitated by bacteriophage, and examine
the validity of the deterministic approach. We use both numerical and
analytical methods of stochastic processes to identify the source of noise and
assess its magnitude. We show that the conclusions obtained from the
deterministic model are robust against stochastic fluctuations, yet deviations
become prominently large when the phage are more pathological to the invading
bacterial strain.Comment: 39 pages, 7 figure
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Verification and Validation of MERCURY: A Modern, Monte Carlo Particle Transport Code
Ab-Initio Calculation of Molecular Aggregation Effects: a Coumarin-343 Case Study
We present time-dependent density functional theory (TDDFT) calculations for
single and dimerized Coumarin-343 molecules in order to investigate the quantum
mechanical effects of chromophore aggregation in extended systems designed to
function as a new generation of sensors and light-harvesting devices. Using the
single-chromophore results, we describe the construction of effective
Hamiltonians to predict the excitonic properties of aggregate systems. We
compare the electronic coupling properties predicted by such effective
Hamiltonians to those obtained from TDDFT calculations of dimers, and to the
coupling predicted by the transition density cube (TDC) method. We determine
the accuracy of the dipole-dipole approximation and TDC with respect to the
separation distance and orientation of the dimers. In particular, we
investigate the effects of including Coulomb coupling terms ignored in the
typical tight-binding effective Hamiltonian. We also examine effects of orbital
relaxation which cannot be captured by either of these models
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