Random copolymer adsorption: Morita approximation compared to exact numerical simulations.

We study the adsorption of ideal random lattice copolymers with correlations in the sequences on homogeneous substrates with two different methods: An analytical solution of the problem based on the constrained annealed approximation introduced by Morita in 1964 and the generating function technique, and direct numerical simulations of lattice chains averaged over many realizations of random sequences. Both methods allow to calculate the free energy and different conformational characteristics of the adsorbed chain. The comparison of the results for random copolymers with different degree of correlations and different types of nonadsorbing monomers (neutral or repelling from the surface) shows not only qualitative but a very good quantitative agreement, especially in the cases of Bernoullian and quasialternating random sequences.

Coarse-grained lattice model for investigating the role of cooperativity in molecular recognition.

Equilibrium aspects of the molecular recognition of rigid biomolecules are investigated using coarse-grained lattice models. The analysis is carried out in two stages. First, an ensemble of probe molecules is designed with respect to the target biomolecule.

Multiscale analysis of MR-mammography data.

In this work we propose a method for automatically discriminating between different types of tissue in MR mammography datasets. This is accomplished by employing a wavelet-based multiscale analysis. After the data has been wavelet-transformed unsupervised machine learning methods are employed to identify typical patterns in the wavelet domain.

Quantitative evaluation of free-form deformation registration for dynamic contrast-enhanced MR mammography.

In this paper, we present an evaluation study of a set of registration strategies for the alignment of sequences of 3D dynamic contrast-enhanced magnetic resonance breast images. The accuracy of the optimal registration strategies was determined on unseen data. The evaluation is based on the simulation of physically plausible breast deformations using finite element methods and on contrast-enhanced image pairs without visually detectable motion artifacts.

Developing and analyzing idealized models for molecular recognition.

We study equilibrium aspects of molecular recognition of two biomolecules using idealized model systems and methods from statistical physics. Starting from the basic experimental findings we demonstrate exemplarily how an idealized coarse-grained model for the investigation of molecular recognition of two biomolecules can be developed. In addition we provide details regarding two model systems for the recognition of a flexible and a rigid biomolecule respectively, the latter taking into account conformational changes.

Coarse-grained lattice model for molecular recognition.

We present a simple model which allows us to investigate the equilibrium aspects of molecular recognition between rigid biomolecules on a generic level. Using a two-stage approach, which consists of a design and a testing step, the role of cooperativity and of varying bond strength in molecular recognition is investigated. Cooperativity is found to enhance selectivity.

Evaluation of radiological features for breast tumour classification in clinical screening with machine learning methods.

Objective: In this work, methods utilizing supervised and unsupervised machine learning are applied to analyze radiologically derived morphological and calculated kinetic tumour features. The features are extracted from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) time-course data.

Material: The DCE-MRI data of the female breast are obtained within the UK Multicenter Breast Screening Study.

Molecular recognition in a lattice model: an enumeration study.

We investigate the mechanisms underlying selective molecular recognition of single heteropolymers at chemically structured planar surfaces. To this end, we study systems with two-letter (HP) lattice heteropolymers by exact enumeration techniques. Selectivity for a particular surface is defined by an adsorption energy criterion.

Polymer adsorption onto random planar surfaces: interplay of polymer and surface correlations.

We study the adsorption of homogeneous or heterogeneous polymers onto heterogeneous planar surfaces with exponentially decaying site-site correlations, using a variational reference system approach. As a main result, we derive simple equations for the adsorption-desorption transition line. We show that it is preferable to have a small amount of strongly adsorbing sites or monomers rather than a greater amount of weakly adsorbing ones.

Influence of sequence correlations on the adsorption of random heteropolymers onto homogeneous planar surfaces.

Using a reference system approach, we develop an analytical theory for the adsorption of random heteropolymers with exponentially decaying and/or oscillating sequence correlations on planar homogeneous surfaces. We obtain a simple equation for the adsorption--desorption transition line. This result as well as the validity of the reference system approach is tested by a comparison with numerical lattice calculations.

Validation of nonrigid image registration using finite-element methods: application to breast MR images.

This paper presents a novel method for validation of nonrigid medical image registration. This method is based on the simulation of physically plausible, biomechanical tissue deformations using finite-element methods. Applying a range of displacements to finite-element models of different patient anatomies generates model solutions which simulate gold standard deformations.

Real-space renormalization-group approach to field evolution equations.

An operator formalism for the reduction of degrees of freedom in the evolution of discrete partial differential equations (PDE) via real-space renormalization group is introduced, in which cell overlapping is the key concept. Applications to (1+1)-dimensional PDEs are presented for linear and quadratic equations that are first order in time.