DNA algorithm for an unbounded fan-in Boolean circuit

In this paper, we present a new DNA-based evaluation algorithm for a Boolean circuit that employs standard bio-molecular techniques. The algorithm operates on an unbounded fan-in Boolean circuit consisting of AND and OR gates. The whole simulation of our algorithm is proposed in a single test tube in O(1) time complexity and is much easier to implement in the laboratory than previously described models. Furthermore, the algorithm allows for evaluating any number of Boolean circuits in parallel in a single test tube.     

Ion-channel gating mechanisms: model identification and parameter estimation from single channel recordings

Patch-clamp data may be analysed in terms of Markov process models of channel gating mechanisms. We present a maximum likelihood algorithm for estimation of gating parameters from records where only a single channel is present. Computer simulated data for three different models of agonist receptor gated channels are used to demonstrate the performance of the procedure. Full details of the implementation of the algorithm are given for an example gating mechanism. The effects of omission of brief openings and closings from the single-channel data on parameter estimation are explored. A strategy for discriminating between alternative possible gating models, based upon use of the Schwarz criterion, is described. Omission of brief events is shown not to lead to incorrect model identification, except in extreme circumstances. Finally, the algorithm is extended to include channel gating models exhibiting multiple conductance levels.     

Construction of restriction maps

A computer program is described, which constructs maps of restrictionendonuclease cleavage sites in linear or circular DNA molecules,given the fragment lengths in single and double digestions withtwo enzymes. The algorithm is based upon a partition methodand a very simple rule to chain fragments. The program is writtenin Prolog II. Received on July 28, 1987; accepted on December 31, 1987     

Angle determination for side views in single particle electron microscopy

In order to build a first model in single particle electron microscopy the relative angular orientation of each image of a protein complex must be determined. These orientations can be described by three Eulerian angles. Images of complexes that present the same view can be aligned in two-dimensions and averaged in order to increase their signal-to-noise ratio. Based on these averaged images, several standard approaches exist for determining Euler angles for randomly oriented projection images. The common lines and angular reconstitution methods work well for particles with symmetry while the random conical tilting and related orthogonal tilt reconstruction methods work in most cases but require the acquisition of tilt pairs of images. For the situation where views of particles can be identified that are rotations about a single axis parallel to the grid, an alternative algorithm to determine the orientations of class averages without the need to acquire tilt pairs can be applied. This type of view of a complex is usually called a side view. This paper describes the detailed workings and characterization of an algorithm, named rotational analysis, which uses real-space fiducial markers derived from the averages themselves to determine the Euler angles for side views. We demonstrate how this algorithm works in practice by applying it to a data set of images of affinity-purified bovine mitochondrial ATP synthase.     

Accessing single nucleotide polymorphisms in genomic DNA by direct multiplex polymerase chain reaction amplification on oligonucleotide microarrays

This study introduces a DNA microarray-based genotyping system for accessing single nucleotide polymorphisms (SNPs) directly from a genomic DNA sample. The described one-step approach combines multiplex amplification and allele-specific solid-phase PCR into an on-chip reaction platform. The multiplex amplification of genomic DNA and the genotyping reaction are both performed directly on the microarray in a single reaction. Oligonucleotides that interrogate single nucleotide positions within multiple genomic regions of interest are covalently tethered to a glass chip, allowing quick analysis of reaction products by fluorescence scanning. Due to a fourfold SNP detection approach employing simultaneous probing of sense and antisense strand information, genotypes can be automatically assigned and validated using a simple computer algorithm. We used the described procedure for parallel genotyping of 10 different polymorphisms in a single reaction and successfully analyzed more than 100 human DNA samples. More than 99% of genotype data were in agreement with data obtained in control experiments with allele-specific oligonucleotide hybridization and capillary sequencing. Our results suggest that this approach might constitute a powerful tool for the analysis of genetic variation.     

Bayesian Modeling of the Level and Duration of Fertility in the Menstrual Cycle

Time to pregnancy studies that identify ovulation days and collect daily intercourse data can be used to estimate the day-specific probabilities of conception given intercourse on a single day relative to ovulation. In this article, a Bayesian semiparametric model is described for flexibly characterizing covariate effects and heterogeneity among couples in daily fecundability. The proposed model is characterized by the timing of the most fertile day of the cycle relative to ovulation, by the probability of conception due to intercourse on the most fertile day, and by the ratios of the daily conception probabilities for other days of the cycle relative to this peak probability. The ratios are assumed to be increasing in time to the peak and decreasing thereafter. Generalized linear mixed models are used to incorporate covariate and couple-specific effects on the peak probability and on the day-specific ratios. A Markov chain Monte Carlo algorithm is described for posterior estimation, and the methods are illustrated through application to caffeine data from a North Carolina pregnancy study.     

Structure motif discovery and mining the PDB

MOTIVATION: Many of the most interesting functional and evolutionary relationships among proteins are so ancient that they cannot be reliably detected through sequence analysis and are apparent only through a comparison of the tertiary structures. The conserved features can often be described as structural motifs consisting of a few single residues or Secondary Structure (SS) elements. Confidence in such motifs is greatly boosted when they are found in more than a pair of proteins. RESULTS: We describe an algorithm for the automatic discovery of recurring patterns in protein structures. The patterns consist of individual residues having a defined order along the protein's backbone that come close together in the structure and whose spatial conformations are similar. The residues in a pattern need not be close in the protein's sequence. The work described in this paper builds on an earlier reported algorithm for motif discovery. This paper describes a significant improvement of the algorithm which makes it very efficient. The improved efficiency allows us to use it for doing unsupervised learning of patterns occurring in small subsets in a large set of structures, a non-redundant subset of the Protein Data Bank (PDB) database of all known protein structures.     

Hidden Markov modeling for single channel kinetics with filtering and correlated noise

Hidden Markov modeling (HMM) can be applied to extract single channel kinetics at signal-to-noise ratios that are too low for conventional analysis. There are two general HMM approaches: traditional Baum's reestimation and direct optimization. The optimization approach has the advantage that it optimizes the rate constants directly. This allows setting constraints on the rate constants, fitting multiple data sets across different experimental conditions, and handling nonstationary channels where the starting probability of the channel depends on the unknown kinetics. We present here an extension of this approach that addresses the additional issues of low-pass filtering and correlated noise. The filtering is modeled using a finite impulse response (FIR) filter applied to the underlying signal, and the noise correlation is accounted for using an autoregressive (AR) process. In addition to correlated background noise, the algorithm allows for excess open channel noise that can be white or correlated. To maximize the efficiency of the algorithm, we derive the analytical derivatives of the likelihood function with respect to all unknown model parameters. The search of the likelihood space is performed using a variable metric method. Extension of the algorithm to data containing multiple channels is described. Examples are presented that demonstrate the applicability and effectiveness of the algorithm. Practical issues such as the selection of appropriate noise AR orders are also discussed through examples.     

Modelling the growth curve of Maine-Anjou beef cattle using heteroskedastic random coefficients models

A heteroskedastic random coefficients model was described for analyzing weight performances between the 100th and the 650th days of age of Maine-Anjou beef cattle. This model contained both fixed effects, random linear regression and heterogeneous variance components. The objective of this study was to analyze the difference of growth curves between animals born as twin and single bull calves. The method was based on log-linear models for residual and individual variances expressed as functions of explanatory variables. An expectation-maximization (EM) algorithm was proposed for calculating restricted maximum likelihood (REML) estimates of the residual and individual components of variances and covariances. Likelihood ratio tests were used to assess hypotheses about parameters of this model. Growth of Maine-Anjou cattle was described by a third order regression on age for a mean growth curve, two correlated random effects for the individual variability and independent errors. Three sources of heterogeneity of residual variances were detected. The difference of weight performance between bulls born as single and twin bull calves was estimated to be equal to about 15 kg for the growth period considered.     

Eye-hand-coordination: A model for computing reaction times in a visually guided reach task

A model is described which provides a simple algorithm to compute the reaction times of saccadic eye movements and reach movements aimed at a single visual target. It is assumed, that the two movements are prepared inparallel and initiated independently unless the preparation of the saccade for some reason takes longer than the preparation of the reach movement. In the latter case the final command to execute the reach movement is synchronized with that to execute the eye movement and therefore the corresponding reaction times are highly correlated in a one-to-one relationship. Random variables are used to predict sets of data that are directly comparable with the experimental results. The algorithm includes the effects of daily practice (learning). The structure of the model and its computational results will be compared with the physiological data from monkey and man.     

Six-fold speed-up of Smith-Waterman sequence database searches using parallel processing on common microprocessors

MOTIVATION: Sequence database searching is among the most important and challenging tasks in bioinformatics. The ultimate choice of sequence-search algorithm is that of Smith-Waterman. However, because of the computationally demanding nature of this method, heuristic programs or special-purpose hardware alternatives have been developed. Increased speed has been obtained at the cost of reduced sensitivity or very expensive hardware. RESULTS: A fast implementation of the Smith-Waterman sequence-alignment algorithm using Single-Instruction, Multiple-Data (SIMD) technology is presented. This implementation is based on the MultiMedia eXtensions (MMX) and Streaming SIMD Extensions (SSE) technology that is embedded in Intel's latest microprocessors. Similar technology exists also in other modern microprocessors. Six-fold speed-up relative to the fastest previously known Smith-Waterman implementation on the same hardware was achieved by an optimized 8-way parallel processing approach. A speed of more than 150 million cell updates per second was obtained on a single Intel Pentium III 500 MHz microprocessor. This is probably the fastest implementation of this algorithm on a single general-purpose microprocessor described to date.     

A mixed dispatching rule approach in FMS scheduling

Short-term scheduling in flexible manufacturing systems (FMSs) is a difficult problem because of the complexities and dynamic behavior of FMSs. To solve this problem, a dispatching rule approach is widely used. In this approach, however, a single dispatching rule is usually assigned for all machines in a system during a given scheduling interval. In this paper, a mixed dispatching rule which can assign a different dispatching rule for each machine is proposed. A search algorithm which selects an appropriate mixed dispatching rule using predictions based on discrete event simulation is developed for this approach. The search algorithm for the mixed dispatching rule is described in detail. The effectiveness (in meeting performance criteria) of the mixed dispatching rule and the efficiency of the search algorithm relative to exhaustive search (complete enumeration) is demonstrated on an FMS model. The mixed dispatching rule approach performs up to 15.9% better than the conventional approach, and is 4% better on average. The statistical significance of the results is dicussed.     

PARALLEL PHYLOGENIES: RECONSTRUCTING THE HISTORY OF HOST-PARASITE ASSEMBLAGES

Abstract— A method for reconstructing the history of a host-parasite assemblage is described. This method has the advantage of making explicit the relationship between the host and parasite trees, and it allows a visually intuitive representation of that history. It also enables host switches to be incorporated as an explanation of the observed pattern of host-parasite associations, without the spurious overestimates of the number of host switches that can be obtained using Brooks parsimony analysis (BPA). Reconstructions that maximize the number of cospeciation events have the greatest explanatory power and are hence preferred over reconstructions with fewer cospeciation events. A heuristic algorithm to find a single maximal reconstruction, and an exact algorithm to find all such reconstructions are presented. Two empirical applications of the method are given.     

A unified approach to joint modeling of multiple quantitative and qualitative traits in gene mapping

Using graph theory, we present a theoretical basis for mapping oligogenes in the joint presence of multiple phenotypic measurements of both quantitative and qualitative types. Various statistical models proposed earlier for several traits of solely single type are special cases of the unified approach given here. Our emphasis is on the generality of the framework, without specifying explicit assumptions about a sampling design. When information about environmental factors potentially affecting the traits is available, it can be incorporated into the genetic model. We adopt the Bayesian inferential machinery due to its firm theoretical basis and its capability of handling uncertain quantities; such as unobserved model parameters, missing marker data, and even different putative genetic models, probabilistically within a single framework. It is shown here that biological hypotheses about single gene affecting simultaneously multiple traits (pleiotropy) can be intuitively imposed as parameter constraints, leading to pleiotropic models for which posterior probabilities can be calculated. Outline of the possible implementation of the Bayesian method is described using the general reversible-jump Markov chain Monte Carlo algorithm. Some future challenges and extensions are also discussed.     

Solvability of the electrocardiology inverse problem for a moving dipole

New formulations of the direct and inverse problems for the moving dipole are offered. It has been suggested to limit the study by a small area on the chest surface. This lowers the role of the medium inhomogeneity. When formulating the direct problem, irregular components are considered. The algorithm of simultaneous determination of the dipole and regular noise parameters has been described and analytically investigated. It is shown that temporal overdetermination of the equations offers a single solution of the inverse problem for the four leads.     

Alignment of whole genomes.

A new system for aligning whole genome sequences is described. Using an efficient data structure called a suffix tree, the system is able to rapidly align sequences containing millions of nucleotides. Its use is demonstrated on two strains of Mycoplasma tuberculosis, on two less similar species of Mycoplasma bacteria and on two syntenic sequences from human chromosome 12 and mouse chromosome 6. In each case it found an alignment of the input sequences, using between 30 s and 2 min of computation time. From the system output, information on single nucleotide changes, translocations and homologous genes can easily be extracted. Use of the algorithm should facilitate analysis of syntenic chromosomal regions, strain-to-strain comparisons, evolutionary comparisons and genomic duplications.     

Texture analysis of cervical cell nuclei by segmentation of chromatin patterns.

Texture parameters of the nuclear chromatin pattern can contribute to the automated classification of specimens on the basis of single cell analysis in cervical cytology. Current texture parameters are abstract and therefore hamper understanding. In this paper texture parameters are described that can be derived from the chromatin pattern after segmentation of the nuclear image. These texture parameters are more directly related to the visual properties of the chromatin pattern. The image segmentation procedure is based on a region grow algorithm which specifically isolates high chromatin density. The texture analysis method has been tested on a data set of images of 112 cervical nuclei on photographic negatives digitized with a step size of 0.125 micron. The preliminary results of a classification trial indicate that these visually interpretable parameters have promising discriminatory power for the distinction between negative and positive specimens.     

EGNAS: an exhaustive DNA sequence design algorithm

ABSTRACT: BACKGROUND: The molecular recognition based on the complementary base pairing of deoxyribonucleicacid (DNA) is the fundamental principle in the fields of genetics, DNA nanotechnologyand DNA computing. We present an exhaustive DNA sequence design algorithm thatallows to generate sets containing a maximum number of sequences with definedproperties. EGNAS (Exhaustive Generation of Nucleic Acid Sequences) offers thepossibility of controlling both interstrand and intrastrand properties. The guanine-cytosinecontent can be adjusted. Sequences can be forced to start and end with guanine orcytosine. This option reduces the risk of "fraying" of DNA strands. It is possible to limitcross hybridizations of a defined length, and to adjust the uniqueness of sequences.Self-complementarity and hairpin structures of certain length can be avoided. Sequencesand subsequences can optionally be forbidden. Furthermore, sequences can be designed tohave minimum interactions with predefined strands and neighboring sequences. RESULTS: The algorithm is realized in a C++ program. TAG sequences can be generated andcombined with primers for single-base extension reactions, which were described formultiplexed genotyping of single nucleotide polymorphisms. Thereby, possible foldbackthrough intrastrand interaction of TAG-primer pairs can be limited. The design ofsequences for specific attachment of molecular constructs to DNA origami is presented. CONCLUSIONS: We developed a new software tool called EGNAS for the design of unique nucleic acidsequences. The presented exhaustive algorithm allows to generate greater sets ofsequences than with previous software and equal constraints. EGNAS is freely availablefor noncommercial use at http://www.chm.tu-dresden.de/pc6/EGNAS.     

Single-channel autocorrelation functions: the effects of time interval omission.

We present a general mathematical framework for analyzing the dynamic aspects of single channel kinetics incorporating time interval omission. An algorithm for computing model autocorrelation functions, incorporating time interval omission, is described. We show, under quite general conditions, that the form of these autocorrelations is identical to that which would be obtained if time interval omission was absent. We also show, again under quite general conditions, that zero correlations are necessarily a consequence of the underlying gating mechanism and not an artefact of time interval omission. The theory is illustrated by a numerical study of an allosteric model for the gating mechanism of the locust muscle glutamate receptor-channel.