A minicomputer system for analyzing and reporting pilot plant fermentor data

In 1979, a minicomputer system was developed for Hoffmann-La Roche by ABEC, Inc. for the purpose of achieving on-line analysis and reporting of data from 16 70-L pilot-plant fermentors (New Brunswick Scientific Co.). The system consists of a PDP 11/60 computer with 96K core capacity, two RL01 disk drives, two RX01 floppy-disk drives, LA-36 DECwriter terminal, Tektronix CRT, and Versatec printer plotter. DEC, PDP, RSX, RL01, RX01, LA-36, and DECwriter are trademarks of Digital Equipment Corporation. The computer software comprises three distinct groups of programs. RSX-11M is a disk-based operating system that allows quick response to realtime events, such as process monitoring and data acquisition, while carrying out less time-dependent activities, such as program development and graphical output. The AIM (Biles, Inc.) system is used to acquire and convert the voltage signals produced by pilot-plant instrumentation into engineering units. Analysis and graphical output are executed by ABEC and Versatec supplied programs. The most beneficial task performed by the computer is the production of graphical output of a variety of measured and analyzed data. This has led to an increase in personnel productivity and design of more meaningful experiments. An ancillary function of the system is to pick up data logged by a PDP 11/03 computer from a remote fermentation production plant by means of a MODEM interfaced communication link. Production data are analyzed and presented in a form identical with pilot-plant data. The experience with the system is discussed in this article.     

KnowledgeEditor: a new tool for interactive modeling and analyzing biological pathways based on microarray data

KnowledgeEditor is a graphical workbench for biological experts to model biomolecular network graphs. The modeled network data are represented by SRML, and can be published via the internet with the help of plug-in module 'GSCope'. KnowledgeEditor helps us to model and analyze biological pathways based on microarray data. It is possible to analyze the drawn networks by simulating up-down regulatory cascade in molecular interactions. AVAILABILITY: KnowledgeEditor is available at http://gscope.gsc.riken.go.jp/.     

A new method for analyzing protein sequence relationships based on Sammon maps.

Recent advances in gene sequencing and rational drug design have re-emphasized the need for new methods for protein analysis, classification, and structure and function prediction. In this article, we introduce a new method for analyzing protein sequences based on Sammon''s non-linear mapping algorithm. When applied to a family of homologous sequences, the method is able to capture the essential features of the similarity matrix, and provides a faithful representation of chemical or evolutionary distance in a simple and intuitive way. The merits of the new algorithm are demonstrated using examples from the protein kinase family.     

Deep data analyzing algorithm based on scale space theory

Scale space theory has been introduced into the field of big data, but its research is still not deep enough and perfect because of the lack of universal theory and method. With deepening of big data processing applications, the research becomes more and more urgent. In view of the above question, this paper studies pervasive multiscale data analysis theory and method, and proposes ARAMS (Association Rules Algorithm based on Multi Scale). On one hand, we give the definition and partition of data scale as well as the relationship of multiscale data set between the upper scale and lower scale based on concept hierarchy theory. On the other hand, we clarify the definition of multiscale data analysis, study essence and classification method. Previous studies show that the proposed method has high coverage rate, high accuracy rate, lower error rate of support estimation degree and greater improvement the efficiency than the traditional algorithm.     

DWARF – a data warehouse system for analyzing protein families

Background  

The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allows to gain a novel understanding of complex biological systems. The data warehouse DWARF applies integrative bioinformatics approaches to the analysis of large protein families.     

A simple method for analyzing exome sequencing data shows distinct levels of nonsynonymous variation for human immune and nervous system genes

To measure the strength of natural selection that acts upon single nucleotide variants (SNVs) in a set of human genes, we calculate the ratio between nonsynonymous SNVs (nsSNVs) per nonsynonymous site and synonymous SNVs (sSNVs) per synonymous site. We transform this ratio with a respective factor f that corrects for the bias of synonymous sites towards transitions in the genetic code and different mutation rates for transitions and transversions. This method approximates the relative density of nsSNVs (rdnsv) in comparison with the neutral expectation as inferred from the density of sSNVs. Using SNVs from a diploid genome and 200 exomes, we apply our method to immune system genes (ISGs), nervous system genes (NSGs), randomly sampled genes (RSGs), and gene ontology annotated genes. The estimate of rdnsv in an individual exome is around 20% for NSGs and 30-40% for ISGs and RSGs. This smaller rdnsv of NSGs indicates overall stronger purifying selection. To quantify the relative shift of nsSNVs towards rare variants, we next fit a linear regression model to the estimates of rdnsv over different SNV allele frequency bins. The obtained regression models show a negative slope for NSGs, ISGs and RSGs, supporting an influence of purifying selection on the frequency spectrum of segregating nsSNVs. The y-intercept of the model predicts rdnsv for an allele frequency close to 0. This parameter can be interpreted as the proportion of nonsynonymous sites where mutations are tolerated to segregate with an allele frequency notably greater than 0 in the population, given the performed normalization of the observed nsSNV to sSNV ratio. A smaller y-intercept is displayed by NSGs, indicating more nonsynonymous sites under strong negative selection. This predicts more monogenically inherited or de-novo mutation diseases that affect the nervous system.     

A new oxidase method for analyzing L-lactate

A new oxidase-coupled colorimetric method for analysis of L-lactate in biological fluids has been developed without use of peroxidase. The method is based on lactate oxidase-catalysed transformation of lactate to pyruvate which is determined photometrically in the next dye-producing reaction of 3-methyl-2-benzothiazolinone hydrazone (MBTH) in the presence of ferric ions. Sensitivity of the method is estimated as 0.1 micromole of analyte in 4-ml of reaction mixture. Linearity is observed in the range 0.1-1.0 micromole of L-lactate in sample (r = 0.99943; p < 0.0001). The developed method has been adapted for assay of L-lactic acid in kefirs and yogurts.     

A pseudolikelihood method for analyzing interval censored data

We introduce a method based on a pseudolikelihood ratio forestimating the distribution function of the survival time ina mixed-case interval censoring model. In a mixed-case model,an individual is observed a random number of times, and at eachtime it is recorded whether an event has happened or not. Oneseeks to estimate the distribution of time to event. We usea Poisson process as the basis of a likelihood function to constructa pseudolikelihood ratio statistic for testing the value ofthe distribution function at a fixed point, and show that thisconverges under the null hypothesis to a known limit distribution,that can be expressed as a functional of different convex minorantsof a two-sided Brownian motion process with parabolic drift.Construction of confidence sets then proceeds by standard inversion.The computation of the confidence sets is simple, requiringthe use of the pool-adjacent-violators algorithm or a standardisotonic regression algorithm. We also illustrate the superiorityof the proposed method over competitors based on resamplingtechniques or on the limit distribution of the maximum pseudolikelihoodestimator, through simulation studies, and illustrate the differentmethods on a dataset involving time to HIV seroconversion ina group of haemophiliacs.     

A new mixture model approach to analyzing allelic-loss data using Bayes factors

Background  

Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor suppressor gene can lead to tumor development, one objective of these studies is to determine which, if any, chromosome arms harbor tumor suppressor genes.     

A new digital field data collection system for dendrochronology

A wide variety of information or ‘metadata’ is required when undertaking dendrochronological sampling. Traditionally, researchers record observations and measurements on field notebooks and/or paper recording forms, and use digital cameras and hand-held GPS devices to capture images and record locations. In the lab, field notes are often manually entered into spreadsheets or personal databases, which are then sometimes linked to images and GPS waypoints. This process is both time consuming and prone to human and instrument error. Specialised hardware technology exists to marry these data sources, but costs can be prohibitive for small scale operations (>$2000 USD). Such systems often include proprietary software that is tailored to very specific needs and might require a high level of expertise to use. We report on the successful testing and deployment of a dendrochronological field data collection system utilising affordable off-the-shelf devices ($100–300 USD). The method builds upon established open source software that has been widely used in developing countries for public health projects as well as to assist in disaster recovery operations. It includes customisable forms for digital data entry in the field, and a marrying of accurate GPS location with geotagged photographs (with possible extensions to other measuring devices via Bluetooth) into structured data fields that are easy to learn and operate. Digital data collection is less prone to human error and efficiently captures a range of important metadata. In our experience, the hardware proved field worthy in terms of size, ruggedness, and dependability (e.g., battery life). The system integrates directly with the Tellervo software to both create forms and populate the database, providing end users with the ability to tailor the solution to their particular field data collection needs.     

A new kinematic model of pro- and supination of the human forearm

We introduce a new kinematic model describing the motion of the human forearm bones, ulna and radius, during forearm rotation. During this motion between the two forearm extrem-positions, referred to as supination (palm up) and pronation (palm down), effects occur, that cannot be explained by the the established kinematic model of R. Fick from 1904. Especially, the motion of the ulna is not properly reproduced by Fick's model. During forearm rotation an evasive motion of the ulna is observed by various authors, using magnetic resonance imaging MRI) technology. Our new kinematic model also simulates this evasive motion. Furthermore, the model is enlarged to include angulations of the forearm bones. Using these results the influence of forearm fractures on the range of forearm motion can be predicted. This knowledge can be used by surgeons to choose the optimal therapy in re-establishing free forearm mobility.     

A general framework for analyzing beta diversity,nestedness and related community-level phenomena based on abundance data

We describe a procedure for evaluating the relative importance of beta diversity, nestedness, and similarity properties of ecological data matrices containing density, cover or biomass scores of species. Our goals are achieved by extension of the simplex approach – originally proposed for presence–absence data – to abundances. Basically, the method involves decomposition of the Marczewski–Steinhaus coefficient of dissimilarity between pairs of sites into two fractions, one derived from differences between total abundance and the other from differences due to abundance replacement. These are contrasted by the similarity function counterpart, known as the Ruzicka coefficient, and are displayed graphically using ternary (or 2D simplex) plots. Interpretation is aided by calculating percentage contributions from these components to the (dis)similarity structure. Measures of replacement and nestedness are new for abundance data; these are considered complementary phenomena reflecting antithetic ecological processes that are analogous to those operating at the presence–absence level. The method is illustrated by artificial data and a range of actual ecological data sets representing different groups of organisms, different scales and different types of data. While the simplex diagrams and associated coefficients are meaningful by themselves, their comparison with presence–absence based results gives additional insight into data structure and background factors.     

Development and evaluation of the measurement system for the human shoulder joint based on the 6 DOF kinematic modelling

Although numerical models on the shoulder complex joint are currently available, many are impractical because of the procedural complexity coupled with limited and mere simple simulations. The present study defined the clavicle-scapula system as the "base of the humerus" in determining the position of proximal head of humerus, rendering conclusive innovation of a six degree of freedom (DOF) shoulder complex joint model. Furthermore, a complete measurement system where evaluation by calibrating the actual values via the use of an electromagnetic tracking device (ETD) was developed based on the innovated model. The special calibration method using optimizing calculation to work out the rotational center of humerus was employed and actually tested if the theoretical consideration was practically available. As a result of accuracy check experiments, the measurement error was defined within 2-3 mm, indicating sufficient accuracy in studies for human movement. Our findings strongly advocate that the benefit of this novel measurement system would contribute to studies related to shoulder movements in physiological anthropology.     

CLUM: A cluster program for analyzing microarray data

Microarray technology is increasingly being applied in biological and medical research to address a wide range of problems. Cluster analysis has proven to be a very useful tool for investigating the structure of microarray data. This paper presents a program for clustering microarray data, which is based on the so-called path-distance. The algorithm gives in each step a partition in two clusters and no prior assumptions on the structure of clusters are required. It assigns each object (gene or sample) to only one cluster and gives the global optimum for the function that quantifies the adequacy of a given partition of the sample into k clusters. The program was tested on experimental data sets, showing the robustness of the algorithm.     

Methods for analyzing the spatial distribution of chiasmata during meiosis based on recombination data

Using genetic recombination data to make inferences about chiasmata on the tetrad during meiosis is a classic problem dating back to Weinstein's paper in 1936 (Genetics 21, 155-199). In the last few years, Weinstein's methods have been revived and applied to new problems, but a number of important statistical issues remain unresolved. Recently, we developed improved statistical methods for studying the frequency distribution of the number of chiasmata (Yu and Feingold, 2001, Biometrics 57, 427-434). In the current article, we develop methods for the complementary issue of studying the spatial distribution of chiasmata. Somewhat different statistical approaches are needed for the spatial problem than for the frequency problem because different scientific questions are of interest. We explore the properties of the maximum likelihood estimate (MLE) for chiasma spatial distributions and propose improvements to the estimation procedures. We develop a class of statistical tests for comparing chiasma patterns in tetrads that have undergone normal meiosis and tetrads that have had a nondisjunction event. Finally, we propose an EM algorithm to find the MLE when the observed data is ambiguous, as is often the case in human datasets. We apply our improved methods to reanalyze a dataset from the literature studying the association between crossover location and meiotic nondisjunction of chromosome 21.     

Note on a method for analyzing stage-frequency data

A new method for analyzing stage-frequency data is proposed which is based on the estimation of rates of transition between one stage and the next highest stage in one unit of time, and a unit time survival rate that is assumed to be constant. Once these estimates are calculated it becomes possible to also estimate the mean durations of stages, stage-specific survival rates, and numbers entering stages. An advantage of the method is that it can be applied with any distribution of entry times to stage 1, and any distribution of numbers in stages when sampling begins. Use of the method is illustrated on data from a copepod population in a Canadian lake.