bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prediction of disulfide connectivity in proteins
Authors: Fariselli Piero , Casadio Rita 
Published: September 2002

Abstract
Motivation: A major problem in protein structure predictionis the correct location of disulfide bridges in cysteine-rich proteins. In protein-folding prediction, the location of disulfide bridges can strongly reduce the search in the conformational space. Therefore the correct prediction of the disulfide connectivity starting from the protein residue sequencemay also help in predicting its 3D structure.
Results: In this paper we equate the problem of predicting the disulfide connectivity in proteins to a problem of finding the graph matching with the maximum weight. The graph vertices are the residues of cysteine-forming disulfide bridges, and the weight edges are contact potentials. In order to solve this problem we develop and test different residue contact potentials. The best performing one, based on the Edmonds–Gabow algorithm and Monte-Carlo simulated annealing reaches an accuracy significantly higher than that obtained with a general mean force contact potential. Significantly, in the case of proteins with four disulfide bonds in the structure, the accuracy is 17 times higher than that of a random predictor. The method presented here can be used to locate putative disulfide bridges in protein-folding.
Availability: The program is available upon request from the authors.
Contact: Casadio@alma.unibo.it; Piero@biocomp.unibo.it
Birth of scale-free molecular networks and the number of

distinct DNA and protein domains per genome
Authors: Rzhetsky Andrey , Gomez Shawn M. 
Published: September 2002

Abstract
Motivation: Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties—including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes.
Results: We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology.
Availability: MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors.
Contact: ar345@columbia.edu
* To whom correspondence should be addressed.
A non-parametric approach to translating gene region
heterogeneity associated with phenotype into location heterogeneity
Authors: Kowalski Jeanne 
Published: September 2002

Abstract
Motivation: The analysis of genetic data poses statistical problems in the form of high dimensionality with small sample sizes. The construction of a composite gene region (sequence pair) heterogeneity measure is one technique for reducing the dimensionality of the problem. This approach however is not without cost, since the contribution of locations to observed gene region differences between groups becomes entangled in this summary measure. This is problematic since it is of scientific interest to identify locations that together depict phenotype.
Results: A method is proposed for relating observed gene region heterogeneity back to the location level. In the spirit of a factor analysis-type setting, the approach focuses on identifying a latent variable structure among locations to explain within and between group genetic differences associated with phenotype. The method is flexible for identifying either the additive contribution from individual locations or the additive contribution from a group of locations, to observed gene region heterogeneity, depending upon the weighting scheme used in constructing a gene region heterogeneity measure. The approach is illustrated with clinical trial data, where the problem of altered HIV drug susceptibility is examined through characterizing location contributions to HIV protease gene region differences associated with a phenotypic treatment response.
Availability: The Splus (MathSoft, Inc. S-Plus 2000, Seattle, WA, 1999) developed menu-driven functions for obtaining results, GENE_ S (J.Kowalski, Harvard School of Public Health, Boston, MA 2001), is available from the author upon request.
Evolutionary HMMs: a Bayesian approach to multiple alignment
Authors: Holmes Ian , Bruno William J. 
Published: September 2002

Abstract
Motivation: We review proposed syntheses of probabilistic sequence alignment, profiling and phylogeny. We develop a multiple alignment algorithm for Bayesian inference in the links model proposed by Thorne et al. (1991, J. Mol. Evol. , 33, 114–124). The algorithm, described in detail in Section 3, samples from and/or maximizes the posterior distribution over multiple alignments for any number of DNA or protein sequences, conditioned on a phylogenetic tree. The individual sampling and maximization steps of the algorithm require no more computational resources than pairwise alignment.
Methods: We present a software implementation (Handel) of our algorithm and report test results on (i) simulated data sets and (ii) the structurally informed protein alignments of BAliBASE (Thompson et al. , 1999, Nucleic Acids Res. , 27, 2682–2690).
Results: We find that the mean sum-of-pairs score (a measure of residue-pair correspondence) for the BAliBASE alignments is only 13% lower for Handelthan for CLUSTALW(Thompson et al. , 1994, Nucleic Acids Res. , 22, 4673–4680), despite the relative simplicity of the links model (CLUSTALW uses affine gap scores and increased penalties for indels in hydrophobic regions). With reference to these benchmarks, we discuss potential improvements to the links model and implications for Bayesian multiple alignment and phylogenetic profiling.
Availability: The source code to Handelis freely distributed on the Internet at http://www.biowiki.org/Handel under the terms of the GNU Public License (GPL, 2000, http://www.fsf.org./copyleft/gpl.html).
Contact: ihh@fruitfly.org
A simple algorithm to infer gene duplication and speciation
events on a gene tree
Authors: Zmasek Christian M. , Eddy Sean R. 
Published: September 2002

Abstract
Motivation: When analyzing protein sequences using sequence similarity searches, orthologous sequences (that diverged by speciation) are more reliable predictors of a new protein’s function than paralogous sequences (that diverged by gene duplication), because duplication enables functional diversification. The utility of phylogenetic information in high-throughput genome annotation (‘phylogenomics’) is widely recognized, but existing approaches are either manual or indirect (e.g. not based on phylogenetic trees). Our goal is to automate phylogenomics using explicit phylogenetic inference. A necessary component is an algorithm to infer speciation and duplication events in a given gene tree.
Results: We give an algorithm to infer speciation and duplication events on a gene tree by comparison to a trusted species tree. This algorithm has a worst-case running time of O(\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(n^{2}\) \end{document}) which is inferior to two previous algorithms that are \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \({\sim}\) \end{document}O(\batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(n\) \end{document}) for a gene tree of \batchmode \documentclass[fleqn,10pt,legalpaper]{article} \usepackage{amssymb} \usepackage{amsfonts} \usepackage{amsmath} \pagestyle{empty} \begin{document} \(n\) \end{document}sequences. However, our algorithm is extremely simple, and its asymptotic worst case behavior is only realized on pathological data sets. We show empirically, using 1750 gene trees constructed from the Pfam protein family database, that it appears to be a practical (and often superior) algorithm for analyzing real gene trees.
Availability: http://www.genetics.wustl.edu/eddy/forester
Contact: zmasek@genetics.wustl.edu; eddy@genetics.wustl.edu
Knowledge representation of signal transduction pathways
Authors: Fukuda Ken-ichiro , Takagi Toshihisa 
Published: September 2002

Abstract
Motivations: Signal transduction is the common term used to define a diverse topic that encompasses a large body of knowledge about the biochemical mechanisms. Since most of the knowledge of signal transduction resides in scientific articles and is represented by texts in natural language or by diagrams, there is the need of a knowledge representation model for signal transduction pathways that can be as readily processed by a computer as it is easily understood by humans.
Results: A signal transduction pathway representation model is presented. It is based on a compound graph structure and is designed to handle the diversity and hierarchical structure of pathways. A prototype knowledge base was implemented on a deductive database and a number of biological queries are demonstrated on it.
Contact: fukuda-cbrc@aist.go.jp; ichiro@ims.u-tokyo.ac.jp
2 Present address: Computational Biology Research Center (CBRC), NationalInstitute of Advanced Industrial Science and Technology (AIST) 2-41-6 Aomi, Koutou-ku, Tokyo 135-0064, Japan.
GeneMachine: gene prediction and sequence annotation
Authors: Makalowska Izabela , Ryan Joseph F. , Baxevanis Andreas D. 
Published: September 2002

Abstract
Motivation: A number of free-standing programs have been developed in order to help researchers find potential coding regions and deduce gene structure for long stretches of what is essentially ‘anonymous DNA’. As these programs apply inherently different criteria to the question of what is and is not a coding region, multiple algorithms should be used in the course of positional cloning and positional candidate projects to assure that all potential coding regions within a previously-identified critical region are identified.
Results: We have developed a gene identification tool called GeneMachine which allows users to query multiple exon and gene prediction programs in an automated fashion. BLAST searches are also performed in order to see whether a previously-characterized coding region corresponds to a region in the query sequence. A suite of Perl programs and modules are used to run MZEF, GENSCAN, GRAIL 2, FGENES, RepeatMasker, Sputnik, and BLAST. The results of these runs are then parsed and written into ASN.1 format. Output files can be opened using NCBI Sequin, in essence using Sequin as both a workbench and as a graphical viewer. The main feature of GeneMachine is that the process is fully automated; the user is only required to launch GeneMachine and then open the resulting file with Sequin. Annotations can then be made to these results prior to submission to GenBank, thereby increasing the intrinsic value of these data.
Availability: GeneMachine is freely-available for download at http://genome.nhgri.nih.gov/genemachine. A public Web interface to the GeneMachine server for academic and not-for-profit users is available at http://genemachine.nhgri.nih.gov. The Web supplement to this paper may be found at http://genome.nhgri.nih.gov/genemachine/supplement/.
Contact: andy@nhgri.nih.gov
* To whom correspondence should be addressed.
Critical Assessment of Microarray Data Analysis: the 2001
challenge
Authors: Johnson Kimberly F. , Lin Simon M. 
Published: September 2002

Abstract
Summary: We initiated the Critical Assessment of Microarray Data Analysis (CAMDA) conference to stimulate and evaluate the development of advanced data analysis techniques for microarrays. A standard data set has been released for this data analysis challenge. The goal of this challenge is to assess the performance of different analytical methods and at the same time to determine how such methods should be evaluated. We hope this effort will catalyze the discussion of microarray data analysis among the research community of biologists, statisticians, mathematicians, and computer scientists.
Availability: http://camda.duke.edu
Contact: camda01@canctr.mc.duke.edu;
* To whom correspondence should be addressed.
Improving gene recognition accuracy by combining
predictions from two gene-finding programs
Authors: Rogic Sanja , Ouellette B.F. Francis , Mackworth Alan K. 
Published: September 2002

Abstract
Motivation: Despite constant improvements in prediction accuracy, gene-finding programs are still unable to provide automatic gene discovery with desired correctness. The current programs can identify up to 75% of exons correctly and less than 50% of predicted gene structures correspond to actual genes. New approaches to computational gene-finding are clearly needed.
Results: In this paper we have explored the benefits of combining predictions from already existing gene prediction programs. We have introduced three novel methods for combining predictions from programs Genscan and HMMgene. The methods primarily aim to improve exon level accuracy of gene-finding by identifying more probable exon boundaries and by eliminating false positive exon predictions. This approach results in improved accuracy at both the nucleotide and exon level, especially the latter, where the average improvement on the newly assembled dataset is 7.9% compared to the best result obtained by Genscan and HMMgene. When tested on a long genomic multi-gene sequence, our method that maintains reading frame consistency improved nucleotide level specificity by 21.0% and exon level specificity by 32.5% compared to the best result obtained by either of the two programs individually.
Availability: The scripts implementing our methods are available from http://www.cs.ubc.ca/labs/beta/genefinding/
Contact: rogic@cse.ucsc.edu
* To whom correspondence should be addressed.
Computational identification of putative programmed
translational frameshift sites
Authors: Shah Atul A. , Giddings Michael C. , Parvaz Jasmin B. , Gesteland Raymond F. , Atkins John F. , Ivanov Ivaylo P. 
Published: September 2002

Abstract
Motivation: In an effort to identify potential programmed frameshift sites by statistical analysis, we explore the hypothesis that selective pressure would have rendered such sites underabundant and underrepresented in protein-coding sequences. We developed a computer program to compare the frequencies of k-length subsequences of nucleotides with the frequencies predicted by a zero order Markov chain determined by the codon bias of the same set of sequences. The program was used to calculate and evaluate the distribution of 7-base oligonucleotides in the 6000+ putative protein-coding sequences of S. cerevisiae preliminary to the laboratory testing of the most highly underrepresented oligos for frameshifting efficiency.
Results: Among the most significant results is the finding that the heptanucleotides CUU-AGG-C and CUU-AGU-U, sites of the programmed +1 translational frameshifts required for the production in yeast of actin filament-binding protein ABP140 and telomerase subunit EST3, respectively, rank among the least represented of phase I heptanucleotides in the coding sequences of S. cerevisiae. Laboratory experiments demonstrated that other underrepresented heptanucleotides identified by the program, for example GGU-CAG-A, are also prone to significant translational frameshifting, suggesting the possibility that genes containing other underrepresented heptamers may also encode transframe products.
Availability: The program is available for download from http://www.gesteland.genetics.utah.edu/freqAnalysis
Contact: ivaylo.ivanov@m.cc.utah.edu
Supplementary Information: Complete results from the analysis of S. cerevisiae are available on http://www.gesteland.genetics.utah.edu/freqAnalysis
* To whom correspondence should be addressed.
2 Present address: Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Mapping physiological states from microarray expression measurements
Authors: Stephanopoulos Gregory , Hwang Daehee , Schmitt William A. , Misra Jatin , Stephanopoulos George 
Published: September 2002

Abstract
Motivation: The increasing use of DNA microarrays to probe cell physiology requires methods for visualizing different expression phenotypes and explicitly connecting individual genes to discriminating expression features. Such methods should be robust and maintain biological interpretability.
Results: We propose a method for the mapping of the physiological state of cells and tissues from multidimensional expression data such as those obtained with DNA microarrays. The method uses Fisher discriminant analysis to create a linear projection of gene expression measurements that maximizes the separation of different sample classes. Relative to other typical classification methods, this method provides insights into the discriminating characteristics of expression measurements in terms of the contribution of individual genes to the definition of distinct physiological states. This projection method also facilitates visualization of classification results in a reduced dimensional space. Examples from four different cases demonstrate the ability of the method to produce well-separated groups in the projection space and to identify important genes for defining physiological states. The method can be augmented to also include data from the proteomic and metabolic phenotypes and can be useful in disease diagnosis, drug screening and bioprocessing applications.
Contact: gregstep@mit.edu
* To whom correspondence should be addressed.
A conditional density error model for the statistical
analysis of microarray data
Authors: Love Brad , Rank David R. , Penn Sharron G. , Jenkins David A. , Thomas Russell S. 
Published: September 2002

Abstract
Motivation: In many microarray experiments, relatively few intra- and inter-array replicate measurements are made due to significant cost limitations and sample availability. Compounding this problem is a lack of robust statistical methods for analyzing gene expression data with limited experimental replicates. As a result, the interpretation of the results of these experiments are difficult with little understanding of the probability of type I and type II errors.
Results: The variability in a series of replicate microarray measurements was modelled using a combination of parametric and non-parametric methods. A 3-dimensional surface was created for the conditional distribution of the variability given the mean signal intensity in both the Cy3 and Cy5 channels. The results were used as the basis for developing statistical methods for analyzing gene expression data with limited experimental replicates.
Availability: The statistical analysis scripts are available upon request.
Contact: drblove@yahoo.comrthomas@kalypsys.com
* To whom correspondence should be addressed at Informax Inc., 7600 Wisconsin Avenue, Suite 1100, Bethesda, MD 20814, USA
2 Pressent address: Kalypsys, Inc., 11099 N. Torrey Pines Road, Suite 200, La Jolla, CA 92037, USA
3 Pressent address: Amersham Biosciences, 928 East Arques Avenue, Sunnyvale, CA 94085, USA
Neural network predicts sequence of TP53 gene based on DNA chip
Authors: Spicker Jeppe S. , Wikman Friedrik , Lu Ming-Lan , Cordon-Cardo Carlos , Workman Christopher , Ørntoft Torben F. , Brunak Søren , Knudsen Steen 
Published: September 2002

Abstract
Summary: We have trained an artificial neural network to predict the sequence of the human TP53 tumor suppressor gene based on a p53 GeneChip. The trained neural network uses as input the fluorescence intensities of DNA hybridized to oligonucleotides on the surface of the chip and makes between zero and four errors in the predicted 1300 bp sequence when tested on wild-type TP53 sequence.
Availability: The trained neural network is available for academic use by contacting steen@cbs.dtu.dk
Contact: steen@cbs.dtu.dk
* To whom correspondence should be addressed.
XEMBL: distributing EMBL data in XML format
Authors: Wang Lichun , Riethoven Jean-Jack , Robinson Alan 
Published: September 2002

Abstract
Summary: Data in the EMBL Nucleotide Sequence Database is traditionally available in a flat file format that has a number of known shortcomings. With XML rapidly emerging as a standard data exchange format that can address some problems of flat file formats by defining data structure and syntax, there is now a demand to distribute EMBL data in an XML format. XEMBL is a service tool that employs CORBA servers to access EMBL data, and distributes the data in XML format via a number of mechanisms.
Availability: Use of the XEMBL service is free of charge at http://www.ebi.ac.uk/xembl/, and can be accessed via web forms, CGI, and a SOAP-enabled service.
Contact: lcwang@ebi.ac.ukpow@ebi.ac.ukalan@ebi.ac.uk
Supplementary information: Information on the EMBL Nucleotide Sequence Database is available at http://www.ebi.ac.uk/embl/. The EMBL Object Model is available at http://corba.ebi.ac.uk/models/. Information on the EMBL CORBA servers is at http://corba.ebi.ac.uk/
Recent History of Melanism in American Peppered Moths
Authors: Grant B. S. , Wiseman L. L. 
Published: September 2002

AbstractIndustrial melanism in peppered moths has been studied most intensively in Britain. The first melanic phenotype (effectively solid black) was recorded near Manchester in 1848. By 1895 about 98% of the specimens near Manchester were melanic, and this once rare phenotype had spread across regions of the country blackened by industrial soot. In rural, unpolluted regions, well away from industrial centers, the pale phenotype (peppered with white and black scales) remained the predominant form. During the latter half of the 20th century, following legislation designed to improve air quality, melanics began to decline in frequency and are now rare where once they had been common. Similar evolutionary changes have occurred elsewhere, but records from outside Britain are fragmentary. We have extended previous surveys of American peppered moth populations and present a composite picture of the recent decline in melanism in northern industrial states—Michigan and Pennsylvania—where melanic phenotypes decreased from more than 90% in 1959 to 6% by 2001. We contrast these changes to the near absence of melanism in a southern state—Virginia—during that same period. As in Britain, the decline in melanism in American peppered moths followed clean air legislation.