Limitations of conventional regression analysis a proposed modification

Summary The conventional genotype-environment interaction analysis cannot detect the theoretically ideal genotype which has been defined as the one with relatively low sensitivity in the poor environments and high sensitivity in the favourable environments. The computation of separate regression coefficients on the two regions of the response curve has been suggested to detect such genotypes. This procedure is simple and more convenient than the complicated curvilinear regression analysis.     

Computation of genetic contributions from pedigrees

Summary A simple procedure is outlined by which genetic contributions of individuals to later generations can be estimated. The method, which involves simple matrix operations, is well suited to automatic computation.     

Computational aspects of motion perception in natural and artificial vision systems.

In this paper a computational scheme for motion perception in artificial and natural vision systems is described. The scheme is motivated by a mathematical analysis in which first-order spatial properties of optical flow, such as singular points and elementary components of optical flow, are shown to be salient features for the computation and analysis of visual motion. The fact that different methods for the computation of optical flow produce similar results is explained in terms of the simple spatial structure of the image motion of rigid bodies. Singular points and elementary flow components are used to compute motion parameters, such as time-to-collision and angular velocity, and also to segment the visual field into areas which correspond to different motions. Then a number of biological implications are discussed. Electrophysiological findings suggest that the brain perceives visual motion by detecting and analysing optical flow components. However, the cortical neurons, which seem to detect elementary flow components, are not able to extract these components from more complex flows. A simple model for the organization of the receptive field of these cells, which is consistent with anatomical and electrophysiological data, is described at the end of the paper.     

An efficient method for scoring base pair interactions

A simple method is described for speeding up the computation of base pairing interractions. It is especially effective on microcomputers.     

Towards a theoretical foundation for morphological computation with compliant bodies

The control of compliant robots is, due to their often nonlinear and complex dynamics, inherently difficult. The vision of morphological computation proposes to view these aspects not only as problems, but rather also as parts of the solution. Non-rigid body parts are not seen anymore as imperfect realizations of rigid body parts, but rather as potential computational resources. The applicability of this vision has already been demonstrated for a variety of complex robot control problems. Nevertheless, a theoretical basis for understanding the capabilities and limitations of morphological computation has been missing so far. We present a model for morphological computation with compliant bodies, where a precise mathematical characterization of the potential computational contribution of a complex physical body is feasible. The theory suggests that complexity and nonlinearity, typically unwanted properties of robots, are desired features in order to provide computational power. We demonstrate that simple generic models of physical bodies, based on mass-spring systems, can be used to implement complex nonlinear operators. By adding a simple readout (which is static and linear) to the morphology such devices are able to emulate complex mappings of input to output streams in continuous time. Hence, by outsourcing parts of the computation to the physical body, the difficult problem of learning to control a complex body, could be reduced to a simple and perspicuous learning task, which can not get stuck in local minima of an error function.     

Stepwise Paring down Variation for Identifying Influential Multi-factor Interactions Related to a Continuous Response Variable

Although several model-based methods are promising for the identification of influential single factors and multi-factor interactions, few are widely used in real applications for most of the model-selection procedures are complex and/or infeasible in computation for high-dimensional data. In particular, the ability of the methods to reveal more true factors and fewer false ones often relies heavily on the selection of appropriate values of tuning parameters, which is still a difficult task to practical analysts. This article provides a simple algorithm modified from stepwise forward regression for the identification of influential factors. Instead of keeping the identified factors in the next models for adjustment in stepwise regression, we propose to subtract the effects of identified factors in each run and always fit a single-term model to the effect-subtracted responses. The computation is lighter as the proposed method only involves calculations of a simple test statistic; and therefore it could be applied to screen ultrahigh-dimensional data for important single factors and multi-factor interactions. Most importantly, we have proposed a novel stopping rule of using a constant threshold for the simple test statistic, which is different from the conventional stepwise regression with AIC or BIC criterion. The performance of the new algorithm has been confirmed competitive by extensive simulation studies compared to several methods available in R packages, including the popular group lasso, surely independence screening, Bayesian quantitative trait locus mapping methods and others. Findings from two real data examples, including a genome-wide association study, demonstrate additional useful information of high-order interactions that can be gained from implementing the proposed algorithm.     

遗传算法——进化论思想与遗传学原理在工程优化中的应用

优胜劣汰是自然界物种进化的法则,近年来,生物科学中的进化论思想与遗传学原理被成功地应用于工程中优化问题的计算,于是产生了一种不同于传统算法的优化算法———遗传算法（ＧＡ）。本文介绍遗传算法所采用的进化论思想和遗传学原理,遗传算法的基本操作、算法步骤、不同于传统算法的特点以及遗传算法的发展历史与应用情况等,并对遗传算法对生物科学的可能应用作了简单的展望。     

Invariants and Other Structural Properties of Biochemical Models as a Constraint Satisfaction Problem

Background

We present a way to compute the minimal semi-positive invariants of a Petri net representing a biological reaction system, as resolution of a Constraint Satisfaction Problem. The use of Petri nets to manipulate Systems Biology models and make available a variety of tools is quite old, and recently analyses based on invariant computation for biological models have become more and more frequent, for instance in the context of module decomposition.

Results

In our case, this analysis brings both qualitative and quantitative information on the models, in the form of conservation laws, consistency checking, etc. thanks to finite domain constraint programming. It is noticeable that some of the most recent optimizations of standard invariant computation techniques in Petri nets correspond to well-known techniques in constraint solving, like symmetry-breaking. Moreover, we show that the simple and natural encoding proposed is not only efficient but also flexible enough to encompass sub/sur-invariants, siphons/traps, etc., i.e., other Petri net structural properties that lead to supplementary insight on the dynamics of the biochemical system under study.

Conclusions

A simple implementation based on GNU-Prolog's finite domain solver, and including symmetry detection and breaking, was incorporated into the BIOCHAM modelling environment and in the independent tool Nicotine. Some illustrative examples and benchmarks are provided.     

A Sensorimotor Model for Computing Intended Reach Trajectories

The presumed role of the primate sensorimotor system is to transform reach targets from retinotopic to joint coordinates for producing motor output. However, the interpretation of neurophysiological data within this framework is ambiguous, and has led to the view that the underlying neural computation may lack a well-defined structure. Here, I consider a model of sensorimotor computation in which temporal as well as spatial transformations generate representations of desired limb trajectories, in visual coordinates. This computation is suggested by behavioral experiments, and its modular implementation makes predictions that are consistent with those observed in monkey posterior parietal cortex (PPC). In particular, the model provides a simple explanation for why PPC encodes reach targets in reference frames intermediate between the eye and hand, and further explains why these reference frames shift during movement. Representations in PPC are thus consistent with the orderly processing of information, provided we adopt the view that sensorimotor computation manipulates desired movement trajectories, and not desired movement endpoints.     

Optical coherence tomography angiography for mapping cerebral microvasculature based on normalized differentiation analysis

Optical coherence tomography angiography (OCTA) is a label‐free, noninvasive biomedical imaging modality for mapping microvascular networks and quantifying blood flow velocities in vivo. Simple computation and fast processing are critical for the OCTA in some applications. Herein, we report on a normalized differentiation method for mapping cerebral microvasculature with the advantages of simple analysis and high image quality, benefitting from computation of differentiation and characteristics of normalization. Normalized differentiation values are validated to have a nearly linear relationship with flow velocities in a range using a flow phantom. The measurements in a rat cerebral cortex show that the OCTA based on the normalized differentiation analysis can generate microvascular images with high quality and monitor spatiotemporal dynamics of blood flow with simple computation and fast processing before and after localized ischemia induced by arterial occlusion.     

DNA rings with multiple energy minima

Within the context of DNA rings, we analyze the relationship between intrinsic shape and the existence of multiple stable equilibria, either nicked or cyclized with the same link. A simple test, based on a perturbation expansion of symmetry breaking within a continuum elastic rod model, provides good predictions of the occurrence of such multiple equilibria. The reliability of these predictions is verified by direct computation of nicked and cyclized equilibria for several thousand DNA minicircles with lengths of 200 and 900 bp. Furthermore, our computations of equilibria for nicked rings predict properties of the equilibrium distribution of link, as calculated by much more computationally intensive Monte Carlo simulations.     

Application of a superword array in genome assembly

We introduce a data structure called a superword array for finding quickly matches between DNA sequences. The superword array possesses some desirable features of the lookup table and suffix array. We describe simple algorithms for constructing and using a superword array to find pairs of sequences that share a unique superword. The algorithms are implemented in a genome assembly program called PCAP.REP for computation of overlaps between reads. Experimental results produced by PCAP.REP and PCAP on a whole-genome dataset show that PCAP.REP produced a more accurate and contiguous assembly than PCAP.     

Analysis of Cross-Over Trials When Within-Subject Errors Follow an AR(1) Process

For cross-over trials with the assumption that the within-subject errors follow an AR(1) process, we propose a method, which is simple to compute, to obtain the generalized least squares estimates. The computation is easily implemented on any software that handles matrix manipulations.     

Estimation of the Transition/Transversion Ratio

A simple method for estimating the transition/transversion ratio was developed. This method can be applied to not only two sequences but also more than two sequences. The statistical properties of the method and some other methods were examined by numerical computation and computer simulation. The results obtained showed that, in terms of bias and variance, the new method gives a better estimate of the transition/transversion ratio than do the other examined methods. The new method was applied to human and chimpanzee mitochondrial control region sequences. Received: 22 September 1997 / Accepted: 1 November 1997     

Error thresholds of replication in finite populations mutation frequencies and the onset of Muller's ratchet

The occurrence of thresholds for error propagation in asexually replicating populations is investigated by means of a simple birth and death model as well as by numerical simulation. Previous results derived for infinite population sizes are extended to finite populations. Here, replication has to be more accurate than in infinitely large populations because the master sequence can be lost not only by accumulation of errors--similar to the loss of wildtype through the operation of Muller's ratchet--but also by natural fluctuations. An analytical expression is given which allows straight computation of highly accurate values of error thresholds. The error threshold can be expanded in a power series of the reciprocal square root of the population size and thus increases with 1 square root of N in sufficiently large populations.     

A Comparison of Algorithms for the Computation of the Mann-Whitney Test

An algorithm is proposed for the computation of the Mann-Whitney Test which only requires the separate ordering of the individual samples and is therefore more suitable than the usual one. It is also more suitable as to computation time than the algorithm described by KUMMER , 1981, if the two sample sizes are of the same magnitude.     

Spatiotemporal elements of macaque v1 receptive fields

Neurons in primary visual cortex (V1) are commonly classified as simple or complex based upon their sensitivity to the sign of stimulus contrast. The responses of both cell types can be described by a general model in which the outputs of a set of linear filters are nonlinearly combined. We estimated the model for a population of V1 neurons by analyzing the mean and covariance of the spatiotemporal distribution of random bar stimuli that were associated with spikes. This analysis reveals an unsuspected richness of neuronal computation within V1. Specifically, simple and complex cell responses are best described using more linear filters than the one or two found in standard models. Many filters revealed by the model contribute suppressive signals that appear to have a predominantly divisive influence on neuronal firing. Suppressive signals are especially potent in direction-selective cells, where they reduce responses to stimuli moving in the nonpreferred direction.     

Computation and physiology of sensory-motor processing in eye movements

Performance in sensory-motor behaviors guides our understanding of many of the key computational functions of the brain: the representation of sensory information, the translation of sensory signals to commands for movement, and the production of behavior. Eye movement behaviors have become a valuable testing ground for theories of neural computation because the neural circuitry has been well characterized and the mechanical control of the eye is comparatively simple. Here I review recent studies of eye movement behaviors that provide insight into sensory-motor computation at the single neuron and systems levels. They show that errors in sensory estimation dominate eye movement variability and that the motor system functions to reduce the behavioral impact of its own intrinsic noise sources.