bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linking quality management to manufacturing strategy: an empirical investigation of customer focus practices
Authors: Sousa Rui 
Published: January 2003

AbstractQuality management (QM) has often been advocated as being universally applicable to organizations. This is in contrast with the manufacturing strategy contingency approach of operations management (OM) which advocates internal and external consistency between manufacturing strategy choices. This article investigates, using the case‐study method, whether customer focus practices—a distinctive subset of the whole set of QM practices—are contingent on a plant’s manufacturing strategy context. The study strongly suggests that customer focus practices are contingent on a plant’s manufacturing strategy and identifies mechanisms by which this takes place. The findings inform the implementation of QM programs.
Revisiting customer participation in service encounters: does culture matter?
Authors: Youngdahl William E. , Kellogg Deborah L. , Nie Winter , Bowen David E. 
Published: January 2003

AbstractService customers expend significant effort through a variety of behaviors, before, during, and after encounters, to increase the likelihood of satisfactory service experience or to salvage failing service encounters. Service customers’ satisfaction‐seeking behaviors are both proactive and reactive in terms of both intent and execution. These behaviors include preparation, relationship building, information exchange, and intervention. This extension of the original research was presented by Youngdahl and Kellogg [Journal of Operations Management 15 (1997) 19]. It provides an examination of how robust the satisfaction‐seeking behaviors are across cultures. The overall question is whether people in different cultures would use similar participative behaviors. We also examined whether or not culture is related to service customers’ effort and satisfaction. The counter‐intuitive findings indicate that service customers’ satisfaction‐seeking behaviors are not related to their cultural orientations. Additionally, culture is not related to effort or satisfaction level. The implication is that prescriptions derived from earlier research on these forms of service participation can be applied both across cultures and to any culturally diverse customer base.
Improving operations planning with learning curves: overcoming the pitfalls of ‘messy’ shop floor data
Authors: Smunt Timothy L , Watts Charles A 
Published: January 2003

AbstractWhile most of the previous research on learning and experience curves examines cost improvements at the product level, we investigate the use of learning curve analysis at the detailed component part production level. Using extensive shop floor data from a medium‐sized commercial firm, we discovered that the ‘messy’ data (i.e. high level of data variance) at the detailed levels often lead to reduced decision maker confidence in the estimates of the learning rates. However, we also found that by applying simple aggregation methods, we could better determine the accuracy of the predicted learning curve rates. Increased confidence in the learning curve estimates is made possible by comparison of regression estimates made at the detailed data level to those made at various aggregated data levels. Based upon our analysis of the empirical data, we are able to provide insights into the practical use of learning curve analysis and associated data aggregation with ‘messy’ shop floor data.
Computational and experimental analysis reveals a novel Src family kinase in the C. elegans genome
Authors: Pandey Akhilesh , Peri Suraj , Thacker Colin , Whipple Chery A. , Collins John J. , Mann Matthias 
Published: January 2003

Abstract
Motivation: The complete genomes of a number of organisms have already been sequenced. However, the vast majority of annotated genes are derived by gene prediction methods. It is important to not only validate the predicted coding regions but also to identify genes that may have been missed by these programs.
Methods: We searched the entire C.elegans genomic sequence database maintained by the Sanger Center using human c-Src sequence in a TBLASN search. We have confirmed one of the predicted regions by isolation of a cDNA and carried out a phylogenetic analysis of Src kinase family members in the worm, fly and several vertebrate species.
Results: Our analysis identified a novel tyrosine kinase in the C.elegans genome that contains functional features typical of the Src family kinases that we have designated as Src-1. The open reading frame contains a conserved N-terminal myristoylation site and a tyrosine residue within the C-terminus that is crucial for regulating the activity of Src kinases. Our phylogenetic analysis of Src family members from C.elegans, Drosophila and other higher organisms revealed a relationship among Src kinases from C. elegans and Drosophila.
Contact: pandey@cebi.sdu.dk
* To whom correspondence should be addressed.
Chemometric Modelling based on 2D-Fluorescence Spectra without
a Calibration Measurement
Authors: Solle D. , Geissler D. , Stärk E. , Scheper T. , Hitzmann B. 
Published: January 2003

Abstract
Motivation: 2D fluorescence spectra provide information from intracellular compounds. Fluorophores like trytophan, tyrosine and phenylalanin as well as NADH and flavins make the corresponding measurement systems very important for bioprocess supervision and control. The evaluation is usually based on chemometric modelling using for their calibration procedure off-line measurements of the desired process variables. Due to the data driven approach lots of off-line measurements are required. Here a methodology is presented, which enables to perform a calibration procedure of chemometric models without any further measurement.
Results: The necessary information for the calibration procedure is provided by means of the a priori knowledge about the process, i.e. a mathematical model, whose model parameters are estimated during the calibration procedure, as well as the fact that the substrate should be consumed at the end of the process run. The new methodology for chemometric calibration is applied for a batch cultivation of aerobically grown S. cerevisiae on the glucose Schatzmann medium. As will be presented the chemometric models, which are determined by this method, can be used for prediction during new process runs.
Availability:The MATHLAB routine is free available on request from the authors.
Contact: Hitzmann@IFTC.Uni-Hannover.de
* To whom correspondence should be addressed.
A study of accuracy and precision in oligonucleotide
arrays: extracting more signal at large concentrations
Authors: Naef Felix , Socci Nicholas D. , Magnasco Marcelo 
Published: January 2003

Abstract
Motivation: Despite the success and popularity of oligonucleotide arrays as a high-throughput technique for measuring mRNA expression levels, quantitative calibration studies have until now been limited. The main reason is that suitable data was not available. However, calibration data recently produced by Affymetrix now permits detailed studies of the intensity dependent sensitivity. Given a certain transcript concentration, it is of particular interest to know whether current analysis methods are capable of detecting differential expression ratios of 2 or higher.
Results: Using the calibration data, we demonstrate that while current techniques are capable of detecting changes in the low to mid concentration range, the situation is noticeably worse for high concentrations. In this regime, expression changes as large as 4 fold are severely biased, and changes of 2 are often undetectable. Such effects are mainly the consequence of the sequence specific binding properties of probes, and not the result of optical saturation in the fluorescence measurements. GeneChips are manufactured such that each transcript is probed by a set of sequences with a wide affinity range. We show that this property can be used to design a method capable of reducing the high intensity bias. The idea behind our methods is to transfer the weight of a measurement to a subset of probes with optimal linear response at a given concentration, which can be achieved using local embedding techniques.
Availability: Program source code will be sent electronically upon request.
Contact: felix@funes.rockefeller.edu
* To whom correspondence should be addressed.
Combinatorial image analysis of DNA microarray features
Authors: Glasbey C.A. , Ghazal P. 
Published: January 2003

Abstract
Motivation: DNA and protein microarrays have become an established leading-edge technology for large-scale analysis of gene and protein content and activity. Contact-printed microarrays has emerged as a relatively simple and cost effective method of choice but its reliability is especially susceptible to quality of pixel information obtained from digital scans of spotted features in the microarray image.
Results: We address the statistical computation requirements for optimizing data acquisition and processing of digital scans. We consider the use of median filters to reduce noise levels in images and top-hat filters to correct for trends in background values. We also consider, as alternative estimators of spot intensity, discs of fixed radius, proportions of histograms and k-means clustering, either with or without a square-root intensity transformation and background subtraction. We identify, using combinatoric procedures, optimal filter and estimator parameters, in achieving consistency among the replicates of a gene on each microarray. Our results, using test data from microarrays of HCMV, indicate that a highly effective approach for improving reliability and quality of microarray data is to apply a 21 by 21 top-hat filter, then estimate spot intensity as the mean of the largest 20% of pixel values in the target region, after a square-root transformation, and corrected for background, by subtracting the mean of the smallest 70% of pixel values.
Availability: Fortran90 subroutines implementing these methods are available from the authors, or at http://www.bioss.ac.uk/~chris.
Contact: chris@bioss.ac.uk
* To whom correspondence should be addressed.
An associative analysis of gene expression array data
Authors: Dozmorov Igor , Centola Michael 
Published: January 2003

Abstract
Motivation: We face the absence of optimized standards to guide normalization, comparative analysis, and interpretation of data sets. One aspect of this is that current methods of statistical analysis do not adequately utilize the information inherent in the large data sets generated in a microarray experiment and require a tradeoff between detection sensitivity and specificity.
Results: We present a multistep procedure for analysis of mRNA expression data obtained from cDNA array methods. To identify and classify differentially expressed genes, results from standard paired t-test of normalized data are compared with those from a novel method, denoted an associative analysis. This method associates experimental gene expressions presented as residuals in regression analysis against control averaged expressions to a common standard—the family of similarly computed residuals for low variability genes derived from control experiments. By associating changes in expression of a given gene to a large family of equally expressed genes of the control group, this method utilizes the large data sets inherent in microarray experiments to increase both specificity and sensitivity. The overall procedure is illustrated by tabulation of genes whose expression differs significantly between Snell dwarf mice (dw/dw) and their phenotypically normal littermates (dw/+, +/+). Of the 2352 genes examined only 450–500 were expressed above the background levels observed in nonexpressed genes and of these 120 were established as differentially expressed in dwarf mice at a significance level that excludes appearance of false positive determinations.
Contact: igor-dozmorov@omrf.ouhsc.edu
* To whom correspondence should be addressed.
Rank order metrics for quantifying the association of sequence
features with gene regulation
Authors: Clarke Neil D. , Granek Joshua A. 
Published: January 2003

Abstract
Motivation: Genome sequences and transcriptome analyses allow the correlation between gene regulation and DNA sequence features to be studied at the whole-genome level. To quantify these correlations, metrics are needed that can be applied to any sequence feature, regardless of its statistical distribution. It is also desirable for the metric values to be determined objectively, that is, without the use of subjective threshold values.
Results: We compare two metrics for quantifying the correlation of DNA sequence features with gene regulation. Each of the metrics is calculated from a rank-ordering of genes based on the value of the sequence feature of interest. The first metric is the area under the curve for a receiver operator characteristic plot (ROC AUC), a common way of summarizing the tradeoff between sensitivity and specificity for different values of a prediction criterion. We call the second metric the mean normalized conditional probability (MNCP). The MNCP can be thought of as the predictive value of the sequence feature averaged over all regulated genes. The statistical significance (P-value) of each metric can be estimated from simulations. Importantly, the P-value of the MNCP metric is less dramatically affected by the presence of false positives among the set of co-regulated genes than is the ROC AUC. This is especially useful in analyzing gene sets identified by DNA microarray analysis because such data cannot distinguish direct regulation by transcription factor binding from indirect regulation. We demonstrate that these two metrics, taken together, are useful tools for defining the binding site representation and regulatory control regions that best explain the difference between genes that are regulated by a given transcription factor and those that are not. Applications to other gene features are also described.
Availability: A Python program for calculating the ROC AUC and MNCP metric values given input rank orders is available from ftp://ftp.bs.jhmi.edu/users/nclarke/MNCP/
Contact: nclarke@jhmi.edu
* To whom correspondence should be addressed.
Gene finding with a hidden Markov model of genome structure and
evolution
Authors: Pedersen Jakob Skou , Hein Jotun 
Published: January 2003

Abstract
Motivation: A growing number of genomes are sequenced. The differences in evolutionary pattern between functional regions can thus be observed genome-wide in a whole set of organisms. The diverse evolutionary pattern of different functional regions can be exploited in the process of genomic annotation. The modelling of evolution by the existing comparative gene finders leaves room for improvement.
Results: A probabilistic model of both genome structure and evolution is designed. This type of model is called an Evolutionary Hidden Markov Model (EHMM), being composed of an HMM and a set of region-specific evolutionary models based on a phylogenetic tree. All parameters can be estimated by maximum likelihood, including the phylogenetic tree. It can handle any number of aligned genomes, using their phylogenetic tree to model the evolutionary correlations. The time complexity of all algorithms used for handling the model are linear in alignment length and genome number. The model is applied to the problem of gene finding. The benefit of modelling sequence evolution is demonstrated both in a range of simulations and on a set of orthologous human/mouse gene pairs.
Availability: Free availability over the Internet on www server: http://www.birc.dk/Software/evogene.
Contact: jsp@daimi.au.dk
* To whom correspondence should be addressed.
A generalized global alignment algorithm
Authors: Huang Xiaoqiu , Chao Kun-Mao 
Published: January 2003

Abstract
Motivation: Homologous sequences are sometimes similar over some regions but different over other regions. Homologous sequences have a much lower global similarity if the different regions are much longer than the similar regions.
Results: We present a generalized global alignment algorithm for comparing sequences with intermittent similarities, an ordered list of similar regions separated by different regions. A generalized global alignment model is defined to handle sequences with intermittent similarities. A dynamic programming algorithm is designed to compute an optimal general alignment in time proportional to the product of sequence lengths and in space proportional to the sum of sequence lengths. The algorithm is implemented as a computer program named GAP3 (Global Alignment Program Version 3). The generalized global alignment model is validated by experimental results produced with GAP3 on both DNA and protein sequences. The GAP3 program extends the ability of standard global alignment programs to recognize homologous sequences of lower similarity.
Availability: The GAP3 program is freely available for academic use at http://bioinformatics.iastate.edu/aat/align/align.html.
Contact: xqhuang@cs.iastate.edu; kmchao@csie.ntu.edu.tw
* To whom correspondence should be addressed.
A naive Bayes model to predict coupling between seven
transmembrane domain receptors and G-proteins
Authors: Cao Jack , Panetta Rosemarie , Yue Shiyi , Steyaert Alain , Young-Bellido Michele , Ahmad Sultan 
Published: January 2003

Abstract
Motivation: An understanding of the coupling between a G-protein coupled receptor (GPCR) and a specific class of heterotrimeric GTP-binding proteins (G-proteins) is vital for further comprehending the function of the receptor within a cell. However, predicting G-protein coupling based on the amino acid sequence of a receptor has been a daunting task. While experimental data for G-protein coupling exist, published models that rely on sequence based prediction are few. In this study, we have developed a Naive Bayes model to successfully predict G-protein coupling specificity by training over 80 GPCRs with known coupling. Each intracellular domain of GPCRs was treated as a discrete random variable, conditionally independent of one another. In order to determine the conditional probability distributions of these variables, ClustalW-generated phylogenetic trees were used as an approximation for the clustering of the intracellular domain sequences. The sampling of an intracellular domain sequence was achieved by identifying the cluster containing the homologue with the highest sequence similarity.
Results: Out of 55 GPCRs validated, the model yielded a correct classification rate of 72%. Our model also predicted multiple G-protein coupling for most of the GPCRs in the validation set. The Bayesian approach in this work offers an alternative to the experimental approach in order to answer the biological problem of GPCR/G-protein coupling selectivity.
Availability: Academic users should send their request for the perl program for calculating likelihood probabilities at jack.cao@astrazeneca.com.
Supplementary Information: The materials can be viewed at http://www.astrazeneca-montreal.com/AZRDM_info/supporting_info.pdf.
* To whom correspondence should be addressed.
Knowledge acquisition, consistency checking and
concurrency control for Gene Ontology (GO)
Authors: Yeh Iwei , Karp Peter D. , Noy Natalya F. , Altman Russ B. 
Published: January 2003

Abstract
Motivation: A critical element of the computational infrastructure required for functional genomics is a shared language for communicating biological data and knowledge. The Gene Ontology (GO; http://www.geneontology.org) provides a taxonomy of concepts and their attributes for annotating gene products. As GO increases in size, its ongoing construction and maintenance becomes more challenging. In this paper, we assess the applicability of a Knowledge Base Management System (KBMS), Protégé-2000, to the maintenance and development of GO.
Results: We transferred GO to Protégé-2000 in order to evaluate its suitability for GO. The graphical user interface supported browsing and editing of GO. Tools for consistency checking identified minor inconsistencies in GO and opportunities to reduce redundancy in its representation. The Protégé Axiom Language proved useful for checking ontological consistency. The PROMPT tool allowed us to track changes to GO. Using Protégé-2000, we tested our ability to make changes and extensions to GO to refine the semantics of attributes and classify more concepts.
Availability: Gene Ontology in Protégé-2000 and the associated code are located at http://smi.stanford.edu/projects/helix/gokbms/. Protégé-2000 is available from http://protege.stanford.edu.
Contact: russ.altman@stanford.edu
* To whom correspondence should be addressed.
Positional candidate gene selection from livestock EST databases
using Gene Ontology
Authors: Harhay Gregory P. , Keele John W. 
Published: January 2003

Abstract
Motivation: The number of expressed sequence tags (ESTs) in GenBank has now surpassed 200 000 for cattle and 100 000 for swine. The Institute of Genome Research (TIGR) has organized these sequences into approximately 60 000 non-redundant consensus sequences (identified by TIGR Gene Indices) for cattle and 40 000 for swine. Anonymous ESTs are of limited value unless they are connected to function. Functional information is difficult to manage electronically because of heterogeneity of meaning and form among databases. The Gene Ontology (GO) Consortium has produced ontologies for gene function with consistent meaning and form across species. Linking livestock EST to gene function through similarity with sequences from other annotation-rich mammals could accelerate: (1) the discovery of positional candidate genes underlying a livestock quantitative trait locus (QTL) and (2) comparative mapping between livestock and other mammals (e.g. humans, mouse and rat). We initiated this investigation to determine if incorporation of the GO into the annotation process could accelerate livestock positional candidate gene discovery.
Results: We have associated livestock ESTs with GO nodes through sequence similarity to the NCBI Reference Sequences (RefSeq). Positional candidate genes are identified within minutes that otherwise required days. The schema described here accommodates queries that return GO nodes from terms familiar to biologists, such as gene name, alternate/alias symbol, and OMIM phenotype.
Availability: Scripts and schema are available on request from the authors.
Contact: harhay@email.marc.usda.gov
* To whom correspondence should be addressed.
Fractional populations in multiple gene inheritance
Authors: Chung Myung-Hoon , Kim Chul Koo , Nahm Kyun 
Published: January 2003

Abstract
Motivation: With complete knowledge of the human genome sequence, one of the most interesting tasks remaining is to understand the functions of individual genes and how they communicate. Using the information about genes (locus, allele, mutation rate, fitness, etc.), we attempt to explain population demographic data. This population evolution study could complement and enhance biologists’ understanding about genes.
Results: We present a general approach to study population genetics in complex situations. In the present approach, multiple allele inheritance, multiple loci inheritance, natural selection and mutations are allowed simultaneously in order to consider a more realistic situation. A simulation program is presented so that readers can readily carry out studies with their own parameters. It is shown that the multiplicity of the loci greatly affects the demographic results of fractional population ratios. Furthermore, the study indicates that some high infant mortality rates due to congenital anomalies can be attributed to multiple loci inheritance.
Availability: The simulation program can be downloaded from http://won.hongik.ac.kr/~mhchung/index_files/yapop.htm. In order to run this program, one needs Visual Studio .NET platform, which can be downloaded from http://msdn.microsoft.com/netframework/downloads/default.asp.
Contact: mhchung@hongik.ac.kr
* To whom correspondence should be addressed.