Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering

Pedigree and sibship reconstruction are important methods in quantifying relationships and fitness of individuals in natural populations. Current methods employ a Markov chain‐based algorithm to explore plausible possible pedigrees iteratively. This provides accurate results, but is time‐consuming. Here, we develop a method to infer sibship and paternity relationships from half‐sibling arrays of known maternity using hierarchical clustering. Given 50 or more unlinked SNP markers and empirically derived error rates, the method performs as well as the widely used package Colony, but is faster by two orders of magnitude. Using simulations, we show that the method performs well across contrasting mating scenarios, even when samples are large. We then apply the method to open‐pollinated arrays of the snapdragon Antirrhinum majus and find evidence for a high degree of multiple mating. Although we focus on diploid SNP data, the method does not depend on marker type and as such has broad applications in nonmodel systems.     

Dynamic Lung Modeling and Tumor Tracking Using Deformable Image Registration and Geometric Smoothing

A greyscale-based fully automatic deformable image registration algorithm, based on an optical flow method together with geometric smoothing, is developed for dynamic lung modeling and tumor tracking. In our computational processing pipeline, the input data is a set of 4D CT images with 10 phases. The triangle mesh of the lung model is directly extracted from the more stable exhale phase (Phase 5). In addition, we represent the lung surface model in 3D volumetric format by applying a signed distance function and then generate tetrahedral meshes. Our registration algorithm works for both triangle and tetrahedral meshes. In CT images, the intensity value reflects the local tissue density. For each grid point, we calculate the displacement from the static image (Phase 5) to match with the moving image (other phases) by using merely intensity values of the CT images. The optical flow computation is followed by a regularization of the deformation field using geometric smoothing. Lung volume change and the maximum lung tissue movement are used to evaluate the accuracy of the application. Our testing results suggest that the application of deformable registration algorithm is an effective way for delineating and tracking tumor motion in image-guided radiotherapy.     

Micromachined polymerase chain reaction system for multiple DNA amplification of upper respiratory tract infectious diseases

This paper presents a micro polymerase chain reaction (PCR) chip for the DNA-based diagnosis of microorganism genes and the detection of their corresponding antibiotic-resistant genes. The micro PCR chip comprises cheap biocompatible soda-lime glass substrates with integrated thin-film platinum resistors as heating/sensing elements, and is fabricated using micro-electro-mechanical-system (MEMS) techniques in a reliable batch-fabrication process. The heating and temperature sensing elements are made of the same material and are located inside the reaction chamber in order to ensure a uniform temperature distribution. This study performs the detection of several genes associated with upper respiratory tract infection microorganisms, i.e. Streptococcus pneumoniae, Haemopilus influenze, Staphylococcu aureus, Streptococcus pyogenes, and Neisseria meningitides, together with their corresponding antibiotic-resistant genes. The lower thermal inertia of the proposed micro PCR chip relative to conventional bench-top PCR systems enables a more rapid detection operation with reduced sample and reagent consumption. The experimental data reveal that the high heating and cooling rates of the system (20 and 10 degrees C/s, respectively) permit successful DNA amplification within 15 min. The micro PCR chip is also capable of performing multiple DNA amplification, i.e. the simultaneous duplication of multiple genes under different conditions in separate reaction wells. Compared with the large-scale PCR system, it is greatly advantageous for fast diagnosis of multiple infectious diseases. Multiplex PCR amplification of two DNA segments in the same well is also feasible using the proposed micro device. The developed micro PCR chip provides a crucial tool for genetic analysis, molecular biology, infectious disease detection, and many other biomedical applications.     

Topography simulation for structural analysis using cell advancing method

In this paper, we propose a novel method for topography simulation in micro-electronic processes such as deposition and etching processes. The proposed scheme comprises of calculating the forward and backward movement of the surface and converting the cell structure into a tetrahedral mesh structure with topological information. Memory requirements are mitigated through a dynamic allocating scheme, which takes only the surface cells under consideration. For the removal of cells, a fixed time step is employed while volume remains in the surface cells. A spillover algorithm has also been devised in order to consider the case when more volume has to be removed from a cell during a single time step. Our proposed scheme was applied to the cases such as the construction of a TFT-LCD structure, ROM and a DRAM cell. A numerical simulator was interfaced with the topography simulator in order to investigate the successful meshing operation form the cell structure. For exemplary application, parasitic capacitances were extracted from a test wafer structure having 4 metal lines embedded in two types of non-planar dielectric layer. The simulation result exhibited about maximum 8% error, which seems to be relatively small in comparison to the planar dielectric layer.     

A generalized weighted quantile sum approach for analyzing correlated data in the presence of interactions

A weighted quantile sum (WQS) regression has been used to assess the associations between environmental exposures and health outcomes. However, the currently available WQS approach, which is based on additive effects, does not allow exploring for potential interactions of exposures with other covariates in relation to a health outcome. In addition, the current WQS cannot account for clustering, thus it may not be valid for analysis of clustered data. We propose a generalized WQS approach that can assess interactions by estimating stratum‐specific weights of exposures in a mixture, while accounting for potential clustering effect of matched pairs of cases and controls as well as censored exposure data due to being below the limits of detection. The performance of the proposed method in identifying interactions is evaluated through simulations based on various scenarios of correlation structures among the exposures and with an outcome. We also assess how well the proposed method performs in the presence of the varying levels of censoring in exposures. Our findings from the simulation study show that the proposed method outperforms the traditional WQS, as indicated by higher power of detecting interactions. We also find no strong evidence that the proposed method falsely identifies interactions when there are no true interactive effects. We demonstrate application of the proposed method to real data from the Epidemiological Research on Autism Spectrum Disorder (ASD) in Jamaica (ERAJ) by examining interactions between exposure to manganese and glutathione S‐transferase family gene, GSTP1 in relation to ASD.     

Monte Carlo studies on equilibrium globular protein folding. III. The four helix bundle

The nature of the equilibrium conformational transition from the denatured state to a four-member alpha-helical bundle was studied employing a dynamic Monte Carlo algorithm in which the model protein chain was confined to a tetrahedral lattice. The model chain was allowed to hunt over all phase space, the target native state was not assumed a priori, and no site-specific interactions were introduced. The exterior vs the interior part of the protein is distinguished by the pattern of hydrophilic and hydrophobic interactions encoded into the primary sequence. The importance of a statistical preference for forming bends, as a function of bend location in the primary sequence, and helical wheel type cooperative interactions were examined, and the necessary conditions for collapse of the chain to the unique native structure were investigated. It was found that an amphipathic pattern of hydrophobic/hydrophilic interactions along with a statistical preference of the central residues for bend formation are sufficient to obtain the four-helix bundle. The transition to the native state has an all-or-none character.     

Hierarchy of the interaction energy distribution in the spatial structure of globular proteins and the problem of domain definition.

An algorithm for determining of protein domain structure is proposed. Domain structures resulted from the algorithm application have been obtained and compared with available data. The method is based on entirely physical model of van der Waals interactions that reflects as illustrated in this work the distribution of electron density. Various levels of hierarchy in the protein spatial structure are discerned by analysis of the energy interaction between structural units of different scales. Thus the level of energy hierarchy plays role of sole parameter, and the method obviates the use of complicated geometrical criteria with numerous fitting parameters. The algorithm readily and accurately locates domains formed by continuous segments of the protein chain as well as those comprising non-sequential segments, sets no limit to the number of segments in a domain. We have analyzed 309 protein structures. Among 277 structures for which our results could be compared with the domain definitions made in other works, 243 showed complete or partial coincidence, and only in 34 cases the domain structures proved substantially different. The domains delineated with our approach may coincide with reference definition at different levels of the globule hierarchy. Along with defining the domain structure, our approach allows one to consider the protein spatial structure in terms of the spatial distribution of the interaction energy in order to establish the correspondence between the hierarchy of energy distribution and the hierarchy of structural elements.     

In vitro and in silico characterization of open-cell structures of trabecular bone

This work aimed to perform a detailed in vitro and in silico characterization of open-cell structures, which resemble trabecular bone, to elucidate osteoporosis failure mechanisms. Experimental and image-based computational methods were used to estimate Young′s modulus and porosities of different open-cell structures (Sawbones; Malmö, Sweden). Three different open-cell structures with different porosities were characterized. Additionally, some open-cell structures were scanned using a microcomputed tomography system (μCT) to non-destructively predict specimen Young′s modulus of the structures by developing voxel-based and tetrahedral finite element (FE) models. A 3D reconstruction and FE analyses were used. The experimental and computational results with different element types (linear and quadratic tetrahedrons and voxel-based meshes) were compared with Sawbones data (Sawbones; Malmö, Sweden) revealing important differences in Young′s modulus and porosities. The specimens with high and low volume fractions were best represented by linear and quadratic tetrahedrons, respectively. These results could be used to develop new osteoporosis-prevention strategies.     

An electrochemical method for measuring metabolic activity and counting cells

An express electrochemical method for determining the metabolic activity of live cells based on the possibility of an electron exchange between an electrode and elements of the biological electron transfer chain in the presence of a mediator is proposed. This method is useful for studying any live cells (animal, plant, and microbial), including anaerobic, dormant, and spore cells. The sample preparation and measurement itself does not take more than 30 min. The detection limit in a volume of 15 ml amounts to 10-5 cells/ml. The applicability of the assessment method of the metabolic activity level during the transition of the bacteria Mycobacterium smegmatis into an uncultivable dormant state was demonstrated. This method is of special value for medicine and environmental control, detecting latent forms of pathogens. An optimal combination of the methods for the express analysis of latent pathogens is proposed.     

DNA–DNA kissing complexes as a new tool for the assembly of DNA nanostructures

Kissing-loop annealing of nucleic acids occurs in nature in several viruses and in prokaryotic replication, among other circumstances. Nucleobases of two nucleic acid strands (loops) interact with each other, although the two strands cannot wrap around each other completely because of the adjacent double-stranded regions (stems). In this study, we exploited DNA kissing-loop interaction for nanotechnological application. We functionalized the vertices of DNA tetrahedrons with DNA stem-loop sequences. The complementary loop sequence design allowed the hybridization of different tetrahedrons via kissing-loop interaction, which might be further exploited for nanotechnology applications like cargo transport and logical elements. Importantly, we were able to manipulate the stability of those kissing-loop complexes based on the choice and concentration of cations, the temperature and the number of complementary loops per tetrahedron either at the same or at different vertices. Moreover, variations in loop sequences allowed the characterization of necessary sequences within the loop as well as additional stability control of the kissing complexes. Therefore, the properties of the presented nanostructures make them an important tool for DNA nanotechnology.     

Sparse Zero-Sum Games as Stable Functional Feature Selection

In large-scale systems biology applications, features are structured in hidden functional categories whose predictive power is identical. Feature selection, therefore, can lead not only to a problem with a reduced dimensionality, but also reveal some knowledge on functional classes of variables. In this contribution, we propose a framework based on a sparse zero-sum game which performs a stable functional feature selection. In particular, the approach is based on feature subsets ranking by a thresholding stochastic bandit. We provide a theoretical analysis of the introduced algorithm. We illustrate by experiments on both synthetic and real complex data that the proposed method is competitive from the predictive and stability viewpoints.     

Using indirect protein-protein interactions for protein complex prediction

Protein complexes are fundamental for understanding principles of cellular organizations. As the sizes of protein-protein interaction (PPI) networks are increasing, accurate and fast protein complex prediction from these PPI networks can serve as a guide for biological experiments to discover novel protein complexes. However, it is not easy to predict protein complexes from PPI networks, especially in situations where the PPI network is noisy and still incomplete. Here, we study the use of indirect interactions between level-2 neighbors (level-2 interactions) for protein complex prediction. We know from previous work that proteins which do not interact but share interaction partners (level-2 neighbors) often share biological functions. We have proposed a method in which all direct and indirect interactions are first weighted using topological weight (FS-Weight), which estimates the strength of functional association. Interactions with low weight are removed from the network, while level-2 interactions with high weight are introduced into the interaction network. Existing clustering algorithms can then be applied to this modified network. We have also proposed a novel algorithm that searches for cliques in the modified network, and merge cliques to form clusters using a "partial clique merging" method. Experiments show that (1) the use of indirect interactions and topological weight to augment protein-protein interactions can be used to improve the precision of clusters predicted by various existing clustering algorithms; and (2) our complex-finding algorithm performs very well on interaction networks modified in this way. Since no other information except the original PPI network is used, our approach would be very useful for protein complex prediction, especially for prediction of novel protein complexes.     

Molecular dynamics simulation of the first stages of the cavitation process in amorphous polymers

The first stages of the cavitation process in amorphous polymers submitted to an hydrostatic deformation in the glassy state are studied with coarse grain molecular dynamics simulations for various intermolecular interactions strengths and flexible and semi-flexible chains. For strong intermolecular interactions, the cavitation process is highly localized and the holes have a marked spherical symmetry. The cavitation regions are more diffuse for weaker intermolecular interactions or when the chain stiffness is increased. The mean Voronoï polyhedra volume and the disorder inside the polymer increase until the stress peak observed below the glass transition. High mobility regions are present before the stress peak that may act as nucleation sites for the cavitation process. The localization of these high mobility zones is enhanced for strong intermolecular interactions or a low chain rigidity. Moreover, the velocity fluctuations are more marked in the vicinity of the holes. For strong intermolecular interactions, the holes are not randomly distributed throughout the system and the nucleation of cavities upon deformation occurs preferentially near the chain ends of the polymer.     

Local sequence information-based support vector machine to classify voltage-gated potassium channels

In our previous work,we developed a computational tool,PreK-ClassK-ClassKv,to predictand classify potassium (K~ ) channels.For K channel prediction (PreK) and classification at family level(ClassK),this method performs well.However,it does not perform so well in classifying voltage-gatedpotassium (Kv) channels (ClassKv).In this paper,a new method based on the local sequence information ofKv channels is introduced to classify Kv channels.Six transmembrane domains of a Kv channel protein areused to define a protein,and the dipeptide composition technique is used to transform an amino acid sequenceto a numerical sequence.A Kv channel protein is represented by a vector with 2000 elements,and a supportvector machine algorithm is applied to classify Kv channels.This method shows good performance withaverages of total accuracy (Acc),sensitivity (SE),specificity (SP),reliability (R) and Matthews correlationcoefficient (MCC) of 98.0%,89.9%,100%,0.95 and 0.94 respectively.The results indicate that the localsequence information-based method is better than the global sequence information-based method to classifyKv channels.     

RECORD: a novel method for ordering loci on a genetic linkage map

A new method, REcombination Counting and ORDering (RECORD) is presented for the ordering of loci on genetic linkage maps. The method minimizes the total number of recombination events. The search algorithm is a heuristic procedure, combining elements of branch-and-bound with local reshuffling. Since the criterion we propose does not require intensive calculations, the algorithm rapidly produces an optimal ordering as well as a series of near-optimal ones. The latter provides insight into the local certainty of ordering along the map. A simulation study was performed to compare the performance of RECORD and JoinMap. RECORD is much faster and less sensitive to missing observations and scoring errors, since the optimisation criterion is less dependent on the position of the erroneous markers. In particular, RECORD performs better in regions of the map with high marker density. The implications of high marker densities on linkage map construction are discussed.     

Magnetic microbubble-mediated ultrasound-MRI registration based on robust optical flow model

Background

As a dual-modality contrast agent, magnetic microbubbles (MMBs) can not only improve contrast of ultrasound (US) image, but can also serve as a contrast agent of magnetic resonance image (MRI). With the help of MMBs, a new registration method between US image and MRI is presented.

Methods

In this method, MMBs were used in both ultrasound and magnetic resonance imaging process to enhance the most important information of interest. In order to reduce the influence of the speckle noise to registration, semi-automatic segmentations of US image and MRI were carried out by using active contour model. After that, a robust optical flow model between US image segmentation (floating image) and MRI segmentation (reference image) was built, and the vector flow field was estimated by using the Coarse-to-fine Gaussian pyramid and graduated non-convexity (GNC) schemes.

Results

Qualitative and quantitative analyses of multiple group comparison experiments showed that registration results using all methods tested in this paper without MMBs were unsatisfactory. On the contrary, the proposed method combined with MMBs led to the best registration results.

Conclusion

The proposed algorithm combined with MMBs contends with larger deformation and performs well not only for local deformation but also for global deformation. The comparison experiments also demonstrated that ultrasound-MRI registration using the above-mentioned method might be a promising method for obtaining more accurate image information.

     

Estimation of the mechanical parameters of the human respiratory system

A numerical algorithm has been developed for the estimation of the mechanical parameters of the human respiratory system. In order to estimate the pulmonary resistance and the dynamic pulmonary elastance, the transpulmonary pressure and the airflow at the mouth or nose are expanded in Chebyshev series. The nonlinear mathematical lung model and a set of measurements for airflow and pressure are then handled by the numerical technique. The lung model includes a component to account for turbulent flow in the larynx and trachea. This contribution presents an alternative method for lung parameter estimation and differs from most existing methods in that it does not need measurements for the tidal volume. It therefore eliminates the use of a body plethysmograph. The method may also find potential application to various other parameter identification problems.