Collection and analysis of kinetic data from a stopped-flow spectrophotometer using a microcomputer

A method of interfacing an inexpensive microcomputer to a stopped-flow kinetics spectrophotometer is described. It allows software-selectable sampling frequencies between 0.1 ms and 8 s and large numbers of data points to be collected. Machine language routines to use the interface are described and these allow the sampling frequency to be altered during data collection to ensure adequate numbers of points in critical regions of the kinetic profile. BASIC programs for collection and analysis of multicomponent kinetic data using this system are also described. Due to the large number of data points that can be collected and the ability to selectively sample transmittance values in regions where the signal is rapidly changing with time, relatively unsophisticated methods of data analysis can be used. These methods are suitable for use by microcomputers and mean that data analysis and acquisition can be performed on the same microcomputer in real time. To illustrate this, multicomponent analysis of kinetic transients is performed on simulated data and on the dissociation kinetics of the ethidium-DNA complex.     

A computer based culturing system for measuring the photosynthetic response of phytoplankton to a fluctuating environment

A microcomputer-controlled culturing system developed to simulate temperature and salinity fluctuations in an estuary is described. The system consists of a microcomputer, interfacing hardware, a continuous culture apparatus, and system software. The system can regulate the temperature and salinity of a continuous phytoplankton culture based on user-defined models of the physical environment and particle transport in a natural environment. The microcomputer also provides efficient data acquisition and data storage. The system was designed to facilitate expansion and modification and can easily be adapted to accomodate various studies of phytoplankton production. Details of a simulation and representative data are presented.     

Hand-held computer program for field-capture and analysis of herbage yield and composition data using a modified dry-weight-rank and yield estimate method

A BASIC program is described which is used to collect, checkand analyse rank estimates of plant yield in the field. Theprogram operates in a portable, battery-powered Sharp PCI500Ahand-held computer than can be used in a field environment.Data are collected using a modified dry-weight-rank method andcomparative yield estimates. Much of the software is designedto trap incorrect data entry. Raw data or summary data may beprinted, displayed, and stored on cassette tape or transferredto another computer through a communications interface. Theprogram can be easily modified to run on other models of theSharp PC series or other portable computers that use a similarBASIC interpreter. Received on July 2, 1987; accepted on August 6, 1987     

A Grid-based solution for management and analysis of microarrays in distributed experiments

Several systems have been presented in the last years in order to manage the complexity of large microarray experiments. Although good results have been achieved, most systems tend to lack in one or more fields. A Grid based approach may provide a shared, standardized and reliable solution for storage and analysis of biological data, in order to maximize the results of experimental efforts. A Grid framework has been therefore adopted due to the necessity of remotely accessing large amounts of distributed data as well as to scale computational performances for terabyte datasets. Two different biological studies have been planned in order to highlight the benefits that can emerge from our Grid based platform. The described environment relies on storage services and computational services provided by the gLite Grid middleware. The Grid environment is also able to exploit the added value of metadata in order to let users better classify and search experiments. A state-of-art Grid portal has been implemented in order to hide the complexity of framework from end users and to make them able to easily access available services and data. The functional architecture of the portal is described. As a first test of the system performances, a gene expression analysis has been performed on a dataset of Affymetrix GeneChip Rat Expression Array RAE230A, from the ArrayExpress database. The sequence of analysis includes three steps: (i) group opening and image set uploading, (ii) normalization, and (iii) model based gene expression (based on PM/MM difference model). Two different Linux versions (sequential and parallel) of the dChip software have been developed to implement the analysis and have been tested on a cluster. From results, it emerges that the parallelization of the analysis process and the execution of parallel jobs on distributed computational resources actually improve the performances. Moreover, the Grid environment have been tested both against the possibility of uploading and accessing distributed datasets through the Grid middleware and against its ability in managing the execution of jobs on distributed computational resources. Results from the Grid test will be discussed in a further paper.     

A statistical simulation model for field testing of non‐target organisms in environmental risk assessment of genetically modified plants

Genetic modification of plants may result in unintended effects causing potentially adverse effects on the environment. A comparative safety assessment is therefore required by authorities, such as the European Food Safety Authority, in which the genetically modified plant is compared with its conventional counterpart. Part of the environmental risk assessment is a comparative field experiment in which the effect on non‐target organisms is compared. Statistical analysis of such trials come in two flavors: difference testing and equivalence testing. It is important to know the statistical properties of these, for example, the power to detect environmental change of a given magnitude, before the start of an experiment. Such prospective power analysis can best be studied by means of a statistical simulation model. This paper describes a general framework for simulating data typically encountered in environmental risk assessment of genetically modified plants. The simulation model, available as Supplementary Material, can be used to generate count data having different statistical distributions possibly with excess‐zeros. In addition the model employs completely randomized or randomized block experiments, can be used to simulate single or multiple trials across environments, enables genotype by environment interaction by adding random variety effects, and finally includes repeated measures in time following a constant, linear or quadratic pattern in time possibly with some form of autocorrelation. The model also allows to add a set of reference varieties to the GM plants and its comparator to assess the natural variation which can then be used to set limits of concern for equivalence testing. The different count distributions are described in some detail and some examples of how to use the simulation model to study various aspects, including a prospective power analysis, are provided.     

Programming for the DNA analysis of FCM data on an IBM microcomputer

The analysis of data generated on a flow cytometer (FCM) is often performed on a computer obtained especially for dedicated use with the flow cytometer. This computer component can be expensive and also presents the FCM user with the added burden of mastering specialized programming language or of accepting the secret analytical processes of protected proprietary program routines. We believe that the evolution of more accurate and efficient FCM analyses that have the power to consider complex signal distributions can be assisted by the availability of analysis programs written in languages common to many users. DNA analysis routines written for a relatively inexpensive microcomputer (IBM PC/XT) in Basic and Pascal are described here. The routines can automatically process multiple FCM data files and can provide high-resolution graphic hardcopy. A foreground/background utilization is also described that allows the computer to be available for other uses in the laboratory.     

Analyzing heat capacity profiles of peptide-containing membranes: cluster formation of gramicidin A

The analysis of peptide and protein partitioning in lipid membranes is of high relevance for the understanding of biomembrane function. We used statistical thermodynamics analysis to demonstrate the effect of peptide mixing behavior on heat capacity profiles of lipid membranes with the aim to predict peptide aggregation from c(P)-profiles. This analysis was applied to interpret calorimetric data on the interaction of the antibiotic peptide gramicidin A with lipid membranes. The shape of the heat capacity profiles was found to be consistent with peptide clustering in both gel and fluid phase. Applying atomic force microscopy, we found gramicidin A aggregates and established a close link between thermodynamics data and microscopic imaging. On the basis of these findings we described the effect of proteins on local fluctuations. It is shown that the elastic properties of the membrane are influenced in the peptide environment.     

Data retrieval and analysis for radioimmunoassays

A data retrieval and analysis system is described here which allows one to simplify and automate the collection of data for radioimmunoassays. The resulting data can be collected in a data summary format to provide the operator with clear, concise results. The software utilizes a Logit function to do regression analysis for results expressed in concentration of antibody, be it IgG, IgM or other, per milliliter of serum. This system allows the operator to do analysis on thousands of serum samples.     

The important choice of reference environment in microevolutionary climate response predictions

It is well documented that individuals of wild populations can adjust to climate change by means of phenotypic plasticity, but few reports on adaptation by means of genetically based microevolution caused by selection. Disentanglement of these separate effects requires that the reference environment (the environmental zero point) is defined, and this should not be done arbitrarily. The problem is that an error in the reference environment may lead to large errors in predicted microevolution. Together with parameter values and initial mean trait values, the reference environment can be estimated from environmental, phenotypic and fitness data. A prediction error method for this purpose is described, with the feasibility shown by simulations. As shown in a toy example, an estimated reference environment may have large errors, especially for small populations. This may still be a better choice than use of an initial environmental value in a recorded time series, or the mean value, which is often used. Another alternative may be to use the mean value of a past and stationary stochastic environment, which the population is judged to have been fully adapted to, in the sense that the expected geometric mean fitness was at a global maximum. Exceptions are cases with constant phenotypic plasticity, where the microevolutionary changes per generation follow directly from phenotypic and environmental data, independent of the chosen reference environment.     

BTM-P1 polycationic peptide biological activity and 3D-dimensional structure

The novel BTM-P1 peptide interferes with energetic processes in mitochondria; its antimicrobial activity against Gram-positive and Gram-negative bacteria is described here. BTM-P1 three-dimensional structure was determined by 1H NMR to explain its biological mechanisms and membrane activity. Structural data indicated that BTM-P1 can form an alpha-helix; circular dichroism analysis confirmed the peptide's propensity to behave as a typical transmembrane helix in a lipidic environment. According to the structural characteristics of the polycationic BTM-P1 peptide so revealed, its biological activity can be explained by a mechanism involving the formation of ion-permeable channels in biomembranes.     

Multifactorial inheritance with cultural transmission and assortative mating. II. a general model of combined polygenic and cultural inheritance.

A general linear model of combined polygenic-cultural inheritance is described. The model allows for phenotypic assortative mating, common environment, maternal and paternal effects, and genic-cultural correlation. General formulae for phenotypic correlation between family members in extended pedigrees are given for both primary and secondary assortative mating. A FORTRAN program BETA, available upon request, is used to provide maximum likelihood estimates of the parameters from reported correlations. American data about IQ and Burks' culture index are analyzed. Both cultural and genetic components of phenotypic variance are observed to make significant and substantial contributions to familial resemblance in IQ. The correlation between the environments of DZ twins is found to equal that of singleton sibs, not that of MZ twins. Burks' culture index is found to be an imperfect measure of midparent IQ rather than an index of home environment as previously assumed. Conditions under which the parameters of the model may be uniquely and precisely estimated are discussed. Interpretation of variance components in the presence of assortative mating and genic-cultural covariance is reviewed. A conservative, but robust, approach to the use of environmental indices is described.     

Estimating kinetic constants from single channel data.

The process underlying the opening and closing of ionic channels in biological or artificial lipid membranes can be modeled kinetically as a time-homogeneous Markov chain. The elements of the chain are kinetic states that can be either open or closed. A maximum likelihood procedure is described for estimating the transition rates between these states from single channel data. The method has been implemented for linear kinetic schemes of fewer than six states, and is suitable for nonstationary data in which one or more independent channels are functioning simultaneously. It also provides standard errors for all estimates of rate constants and permits testing of smoothly parameterized subhypotheses of a general model. We have illustrated our approach by analysis of single channel data simulated on a computer and have described a procedure for analysis of experimental data.     

Hydration of nucleic acid fragments: comparison of theory and experiment for high-resolution crystal structures of RNA, DNA, and DNA-drug complexes.

A computationally efficient method to describe the organization of water around solvated biomolecules is presented. It is based on a statistical mechanical expression for the water-density distribution in terms of particle correlation functions. The method is applied to analyze the hydration of small nucleic acid molecules in the crystal environment, for which high-resolution x-ray crystal structures have been reported. Results for RNA [r(ApU).r(ApU)] and DNA [d(CpG).d(CpG) in Z form and with parallel strand orientation] and for DNA-drug complexes [d(CpG).d(CpG) with the drug proflavine intercalated] are described. A detailed comparison of theoretical and experimental data shows positional agreement for the experimentally observed water sites. The presented method can be used for refinement of the water structure in x-ray crystallography, hydration analysis of nuclear magnetic resonance structures, and theoretical modeling of biological macromolecules such as molecular docking studies. The speed of the computations allows hydration analyses of molecules of almost arbitrary size (tRNA, protein-nucleic acid complexes, etc.) in the crystal environment and in aqueous solution.     

A System for Continuous Monitoring of Whole Shoot CO2 Exchange as an Adjunct to Growth Analysis Experiments in Controlled Environments

A multichannel system is described in which continuous CO₂ exchangemeasurements of whole shoots can be made on plants grown incontrolled environments such as growth cabinets, glasshouses,or plastic houses. The shoot enclosure is made from a coatedpolypropylene film which not only combines excellent light transmittancewith poor permeability to CO₂ but can also be tailored easilyto individual shoot systems of various sizes ensuring a rapidresponse time for CO₂ exchange measurements. Air speeds withinthe enclosure are regulated precisely; temperature and relativehumidity are also controlled to within narrow limits, duringdaylight hours and at night. Thus, the aerial environment ofenclosed shoots parallels closely that of non-enclosed plants. The system compliments a root respiration chamber designed earlier;used in conjunction with growth analysis data, the two systemsfacilitate quantitative determinations of the carbon economyof entire plants throughout all stages of growth.     

Computer-aided construction of nucleic acid restriction maps using defined vectors

A new algorithm is described that will rapidly produce restrictionmaps of cloned DNA fragments. Information concerning the vectoris stored as a data file and used in constructing probable maps.As the program is based upon a permutation analysis it has twoprimary uses. First, preliminary restriction maps can be createdfrom fragment length data as a starting point for further analysis.Second, existing maps can be confirmed as being highly probable,and other probable maps examined to ensure certain combinationshave not been overlooked. Although primarily designed for linearvectors, the program can be used to calculate circular maps. Received on June 5, 1985; accepted on September 27, 1985     

Variance components models for gene-environment interaction in quantitative trait locus linkage analysis.

Gene-environment interaction (G x E) is likely to be a common and important source of variation for complex behavioral traits. Gene-environment interaction, or genetic control of sensitivity to the environment, can be incorporated into variance components twin and sib-pair analyses by partitioning genetic effects into a mean part, which is independent of the environment, and a part that is a linear function of the environment. An approach described in a companion paper (Purcell, 2002) is applied to sib-pair variance components linkage analysis in two ways: allowing for quantitative trait locus by environment interaction and utilizing information on any residual interactions detected prior to analysis. As well as elucidating environmental pathways, consideration of G x E in quantitative and molecular studies will potentially direct and enhance gene-mapping efforts.     

Patterns in the species–environment relationship depend on both scale and choice of response variables

Multi-scale investigations of species–environment relationships are an important tool in ecological research. The scale at which independent and dependent variables are measured, and how they are coded for analysis, can strongly influence the relationships that are discovered. However, little is known about how the coding of the dependent variable set influences community-level analyses. In this study, we used canonical correspondence analysis to quantify species–environment relationships between environmental factors collected at three spatial scales and the structure of a forest bird community in the Oregon coast range. The main question in our analysis was how coding the bird data as abundance versus presence/absence affected the nature and strength of observed relationships. As we expected, the structure of the bird community was better described overall using abundance data than it was using presence/absence data. However, individual species and life-history groups appeared to exhibit different species–environment relationships in abundance versus presence/absence data. In particular, common species with a high frequency of occurrence among sample points exhibited a stronger 'abundance' signature, whereas uncommon species with a low frequency of occurrence exhibited a stronger 'presence/absence' signature. In addition, the apparent importance of plot-level factors in explaining the variation in the bird community was greater for abundance data, whereas patch and landscape factors were more important in the presence/absence data. Thus, conclusions about the relative importance of factors at different scales is largely contingent on the way in which the species-response data are coded for analysis. For communities as a whole, and for individual species within them, the strength and nature of species–environment relationships can differ dramatically between analyses using presence/absence versus abundance data.     

Classification of Trends Via the Linear State Space Model

A method is presented for classification of trend curves based on the linear state space model. In this approach information about the smoothness of the trend curves is incorporated into the classification model by a nonstationary stochastic trend model and can thereby be used to obtain a better classification. In the case of small data sets the performance of the classification is significantly improved in comparison with the usual cluster analysis. Maximum likelihood estimation can be used to calculate the parameters of this model and to determine the classification. The classification algorithm is described in detail and the results are compared to those of the usual cluster analysis by simulation studies and by an application to tree ring data.     

Mixed-model analysis of a censored normal distribution with reference to animal breeding

A mixed-model procedure for analysis of censored data assuming a multivariate normal distribution is described. A Bayesian framework is adopted which allows for estimation of fixed effects and variance components and prediction of random effects when records are left-censored. The procedure can be extended to right- and two-tailed censoring. The model employed is a generalized linear model, and the estimation equations resemble those arising in analysis of multivariate normal or categorical data with threshold models. Estimates of variance components are obtained using expressions similar to those employed in the EM algorithm for restricted maximum likelihood (REML) estimation under normality.