bluuebunny/crossref_metadata_2025_split huggingface dataset:
ProSOM: core promoter prediction based on unsupervised clustering of DNA physical profiles
Authors: Abeel Thomas , Saeys Yvan , Rouzé Pierre , Van de Peer Yves 
Published: June 2008

AbstractMotivation: More and more genomes are being sequenced, and to keep up with the pace of sequencing projects, automated annotation techniques are required. One of the most challenging problems in genome annotation is the identification of the core promoter. Because the identification of the transcription initiation region is such a challenging problem, it is not yet a common practice to integrate transcription start site prediction in genome annotation projects. Nevertheless, better core promoter prediction can improve genome annotation and can be used to guide experimental work.Results: Comparing the average structural profile based on base stacking energy of transcribed, promoter and intergenic sequences demonstrates that the core promoter has unique features that cannot be found in other sequences. We show that unsupervised clustering by using self-organizing maps can clearly distinguish between the structural profiles of promoter sequences and other genomic sequences. An implementation of this promoter prediction program, called ProSOM, is available and has been compared with the state-of-the-art. We propose an objective, accurate and biologically sound validation scheme for core promoter predictors. ProSOM performs at least as well as the software currently available, but our technique is more balanced in terms of the number of predicted sites and the number of false predictions, resulting in a better all-round performance. Additional tests on the ENCODE regions of the human genome show that 98% of all predictions made by ProSOM can be associated with transcriptionally active regions, which demonstrates the high precision.Availability: Predictions for the human genome, the validation datasets and the program (ProSOM) are available upon request.Contact: yves.vandepeer@psb.ugent.be
Optimal pooling for genome re-sequencing with ultra-high-throughput short-read technologies
Authors: Hajirasouliha Iman , Hormozdiari Fereydoun , Sahinalp S. Cenk , Birol Inanc 
Published: June 2008

Abstract
New generation sequencing technologies offer unique opportunities and challenges for re-sequencing studies. In this article, we focus on re-sequencing experiments using the Solexa technology, based on bacterial artificial chromosome (BAC) clones, and address an experimental design problem. In these specific experiments, approximate coordinates of the BACs on a reference genome are known, and fine-scale differences between the BAC sequences and the reference are of interest. The high-throughput characteristics of the sequencing technology makes it possible to multiplex BAC sequencing experiments by pooling BACs for a cost-effective operation. However, the way BACs are pooled in such re-sequencing experiments has an effect on the downstream analysis of the generated data, mostly due to subsequences common to multiple BACs. The experimental design strategy we develop in this article offers combinatorial solutions based on approximation algorithms for the well-known max n-cut problem and the related max n-section problem on hypergraphs. Our algorithms, when applied to a number of sample cases give more than a 2-fold performance improvement over random partitioning.
Contact: cenk@cs.sfu.ca
MicroRNA prediction with a novel ranking algorithm based on random walks
Authors: Xu Yunpen , Zhou Xuefeng , Zhang Weixiong 
Published: June 2008

Abstract
MicroRNA (miRNAs) play essential roles in post-transcriptional gene regulation in animals and plants. Several existing computational approaches have been developed to complement experimental methods in discovery of miRNAs that express restrictively in specific environmental conditions or cell types. These computational methods require a sufficient number of characterized miRNAs as training samples, and rely on genome annotation to reduce the number of predicted putative miRNAs. However, most sequenced genomes have not been well annotated and many of them have a very few experimentally characterized miRNAs. As a result, the existing methods are not effective or even feasible for identifying miRNAs in these genomes.
Aiming at identifying miRNAs from genomes with a few known miRNA and/or little annotation, we propose and develop a novel miRNA prediction method, miRank, based on our new random walks- based ranking algorithm. We first tested our method on Homo sapiens genome; using a very few known human miRNAs as samples, our method achieved a prediction accuracy greater than 95%. We then applied our method to predict 200 miRNAs in Anopheles gambiae, which is the most important vector of malaria in Africa. Our further study showed that 78 out of the 200 putative miRNA precursors encode mature miRNAs that are conserved in at least one other animal species. These conserved putative miRNAs are good candidates for further experimental study to understand malaria infection.
Availability: MiRank is programmed in Matlab on Windows platform. The source code is available upon request.
Contact: zhang@cse.wustl.edu
A robust framework for detecting structural variations in a genome
Authors: Lee Seunghak , Cheran Elango , Brudno Michael 
Published: June 2008

Abstract
Motivation: Recently, structural genomic variants have come to the forefront as a significant source of variation in the human population, but the identification of these variants in a large genome remains a challenge. The complete sequencing of a human individual is prohibitive at current costs, while current polymorphism detection technologies, such as SNP arrays, are not able to identify many of the large scale events. One of the most promising methods to detect such variants is the computational mapping of clone-end sequences to a reference genome.
Results: Here, we present a probabilistic framework for the identification of structural variants using clone-end sequencing. Unlike previous methods, our approach does not rely on an a priori determined mapping of all reads to the reference. Instead, we build a framework for finding the most probable assignment of sequenced clones to potential structural variants based on the other clones. We compare our predictions with the structural variants identified in three previous studies. While there is a statistically significant correlation between the predictions, we also find a significant number of previously uncharacterized structural variants. Furthermore, we identify a number of putative cross-chromosomal events, primarily located proximally to the centromeres of the chromosomes.
Availability: Our dataset, results and source code are available at http://compbio.cs.toronto.edu/structvar/
Contact: seunghak@cs.toronto.edu,echeran@cs.toronto.edu,brudno@cs.toronto.edu
Annotation-based inference of transporter function
Authors: Lee Thomas J. , Paulsen Ian , Karp Peter 
Published: June 2008

Abstract
Motivation: We present a method for inferring and constructing transport reactions for transporter proteins based primarily on the analysis of the names of individual proteins in the genome annotation of an organism. Transport reactions are declarative descriptions of transporter activities, and thus can be manipulated computationally, unlike free-text protein names. Once transporter activities are encoded as transport reactions, a number of computational analyses are possible including database queries by transporter activity; inclusion of transporters into an automatically generated metabolic-map diagram that can be painted with omics data to aid in their interpretation; detection of anomalies in the metabolic and transport networks, such as substrates that are transported into the cell but are not inputs to any metabolic reaction or pathway; and comparative analyses of the transport capabilities of different organisms.
Results: On randomly selected organisms, the method achieves precision and recall rates of 0.93 and 0.90, respectively in identifying transporter proteins by name within the complete genome. The method obtains 67.5% accuracy in predicting complete transport reactions; if allowance is made for predictions that are overly general yet not incorrect, reaction prediction accuracy is 82.5%.
Availability: The method is implemented as part of PathoLogic, the inference component of the Pathway Tools software. Pathway Tools is freely available to researchers at non-commercial institutions, including source code; a fee applies to commercial institutions.
Contact: tomlee@ai.sri.com
Supplementary information: Supplementary data are available at Bioinformatics online.
Identifying gene-disease associations using centrality on a literature mined gene-interaction network
Authors: Özgür Arzucan , Vu Thuy , Erkan Güneş , Radev Dragomir R. 
Published: June 2008

Abstract
Motivation: Understanding the role of genetics in diseases is one of the most important aims of the biological sciences. The completion of the Human Genome Project has led to a rapid increase in the number of publications in this area. However, the coverage of curated databases that provide information manually extracted from the literature is limited. Another challenge is that determining disease-related genes requires laborious experiments. Therefore, predicting good candidate genes before experimental analysis will save time and effort. We introduce an automatic approach based on text mining and network analysis to predict gene-disease associations. We collected an initial set of known disease-related genes and built an interaction network by automatic literature mining based on dependency parsing and support vector machines. Our hypothesis is that the central genes in this disease-specific network are likely to be related to the disease. We used the degree, eigenvector, betweenness and closeness centrality metrics to rank the genes in the network.
Results: The proposed approach can be used to extract known and to infer unknown gene-disease associations. We evaluated the approach for prostate cancer. Eigenvector and degree centrality achieved high accuracy. A total of 95% of the top 20 genes ranked by these methods are confirmed to be related to prostate cancer. On the other hand, betweenness and closeness centrality predicted more genes whose relation to the disease is currently unknown and are candidates for experimental study.
Availability: A web-based system for browsing the disease-specific gene-interaction networks is available at: http://gin.ncibi.org
Contact: radev@umich.edu
Classification of arrayCGH data using fused SVM
Authors: Rapaport Franck , Barillot Emmanuel , Vert Jean-Philippe 
Published: June 2008

AbstractMotivation: Array-based comparative genomic hybridization (arrayCGH) has recently become a popular tool to identify DNA copy number variations along the genome. These profiles are starting to be used as markers to improve prognosis or diagnosis of cancer, which implies that methods for automated supervised classification of arrayCGH data are needed. Like gene expression profiles, arrayCGH profiles are characterized by a large number of variables usually measured on a limited number of samples. However, arrayCGH profiles have a particular structure of correlations between variables, due to the spatial organization of bacterial artificial chromosomes along the genome. This suggests that classical classification methods, often based on the selection of a small number of discriminative features, may not be the most accurate methods and may not produce easily interpretable prediction rules.Results: We propose a new method for supervised classification of arrayCGH data. The method is a variant of support vector machine that incorporates the biological specificities of DNA copy number variations along the genome as prior knowledge. The resulting classifier is a sparse linear classifier based on a limited number of regions automatically selected on the chromosomes, leading to easy interpretation and identification of discriminative regions of the genome. We test this method on three classification problems for bladder and uveal cancer, involving both diagnosis and prognosis. We demonstrate that the introduction of the new prior on the classifier leads not only to more accurate predictions, but also to the identification of known and new regions of interest in the genome.Availability: All data and algorithms are publicly available.Contact: franck.rapaport@curie.fr
Modeling peptide fragmentation with dynamic Bayesian networks for peptide identification
Authors: Klammer Aaron A. , Reynolds Sheila M. , Bilmes Jeff A. , MacCoss Michael J. , Noble William Stafford 
Published: June 2008

AbstractMotivation: Tandem mass spectrometry (MS/MS) is an indispensable technology for identification of proteins from complex mixtures. Proteins are digested to peptides that are then identified by their fragmentation patterns in the mass spectrometer. Thus, at its core, MS/MS protein identification relies on the relative predictability of peptide fragmentation. Unfortunately, peptide fragmentation is complex and not fully understood, and what is understood is not always exploited by peptide identification algorithms.Results: We use a hybrid dynamic Bayesian network (DBN)/support vector machine (SVM) approach to address these two problems. We train a set of DBNs on high-confidence peptide-spectrum matches. These DBNs, known collectively as Riptide, comprise a probabilistic model of peptide fragmentation chemistry. Examination of the distributions learned by Riptide allows identification of new trends, such as prevalent a-ion fragmentation at peptide cleavage sites C-term to hydrophobic residues. In addition, Riptide can be used to produce likelihood scores that indicate whether a given peptide-spectrum match is correct. A vector of such scores is evaluated by an SVM, which produces a final score to be used in peptide identification. Using Riptide in this way yields improved discrimination when compared to other state-of-the-art MS/MS identification algorithms, increasing the number of positive identifications by as much as 12% at a 1% false discovery rate.Availability: Python and C source code are available upon request from the authors. The curated training sets are available at http://noble.gs.washington.edu/proj/intense/. The Graphical Model Tool Kit (GMTK) is freely available at http://ssli.ee.washington.edu/bilmes/gmtk.Contact: noble@gs.washington.edu
Timely Resistance in the Documentary Work of Dominique Cabrera
Authors: Dobson Julia 
Published: June 2008

Abstract

Dominique Cabrera's œuvre attests to a consistent preoccupation with the representation and construction of a
bonheur collectif
. Through a detailed analysis of two documentary films,
Chronique d'une banlieue ordinaire
(1992) and
Demain et encore demain (journal 1995)
(1997), this article will reveal her adoption of the documentary as a therapeutic form in opposition to dominant Griersonian modes of documentary that counter the potential empowerment of representation with the conferral of victimhood on its subjects. Cabrera's films avoid such heritages through their insistence on a formal
mise en abyme
of documentary processes to perform a
réinsertion sociale
of the stigmatized communities of Val Fourré and a moving
réinsertion temporelle
of the filmmaker herself in the first-person confessional
Demain et encore demain
. This
mise en abyme
includes a meditation on the ontology of the photographic image and its pervasive relationship with mortality; both films sensitize their audience to the relationship between image, time and narrative. Such arguments are presented within the context of the dramatic increase in production of (first-person) documentary in contemporary France and the current crisis of legitimization in the conventional documentary form.
Promenades de lecteurs dans
Le Vaillant Petit Tailleur
d'Éric Chevillard
Authors: Tobiassen Elin Beate 
Published: June 2008

Abstract

Le roman
Le Vaillant Petit Tailleur
d'Éric Chevillard (2003), écrivain dont la production figure peut-être parmi les œuvres en prose les plus notoires de la littérature française actuelle, a été perçu par la critique comme une attaque sévère contre la forme traditionnelle du conte de fées. Explorant une nouvelle piste, cet article aborde le roman sous l'angle de la réception littéraire, argumentant que la préoccupation cruciale de son narrateur-auteur est au contraire celle qui consiste à inventer un lecteur de son propre texte. Qui est ce lecteur en jeu dans l'œuvre? Quel(s) lecteur(s) ce texte se présume-t-il? Quelles figures de lecteurs imagine-t-il au fil des pages? Et quelle place cette œuvre métatextuelle, intelligemment agencée, demandant recul, ruse, et perspicacité de la part de son lecteur, laisse-t-elle à la jouissance, à l'envoûtement? L'analyse du
Vaillant Petit Tailleur
sous cette lumière inédite permet de reconsidérer l'attitude distanciée souvent attribuée au lecteur de la métafiction moderne. S'il est un écrivain tenant d'une conception ‘intellectuelle’ du roman, refusant l'immersion mimétique à l'égard du personnage au profit d'un développement excessif du potentiel réflexif du texte, Chevillard est pourtant fort loin de vouer son lecteur à l'abstinence du plaisir.
An operational monitoring system to provide indicators of CO2-related variables in the ocean
Authors: Hardman-Mountford Nicholas J. , Moore Gerald , Bakker Dorothee C. E. , Watson Andrew J. , Schuster Ute , Barciela Rosa , Hines Adrian , Moncoiffé Gwenaelle , Brown Juan , Dye Stephen , Blackford Jerry , Somerfield Paul J. , Holt Jason , Hydes David J. , Aiken James 
Published: June 2008

Abstract
Hardman-Mountford, N. J., Moore, G., Bakker, D. C. E., Watson, A. J., Schuster, U., Barciela, R., Hines, A., Moncoiffé, G., Brown, J., Dye, S., Blackford, J., Somerfield, P. J., Holt, J., Hydes, D. J., and Aiken, J. 2008. An operational monitoring system to provide indicators of CO2-related variables in the ocean. – ICES Journal of Marine Science, 65: 1498–1503. Demand by governments and scientists is increasing for indicators of CO2-related variables for the ocean. We describe a recent project, CARBON-OPS, during which a “supply chain” was developed for automated measurement of pCO2 in the surface of the ocean, data processing, and its use in providing information for research and policy development. Data are gathered by new pCO2 measurement systems on five UK research ships in the Southern Ocean, Atlantic Ocean, and northwestern European shelf seas. These send data in near-real-time, via satellite communication systems, to the British Oceanographic Data Centre, where they are automatically processed, quality controlled, and archived. The data are then delivered to the UK Met Office and others for use in testing predictions from operational ocean models. These models will generate indicator products and assist government through the Marine Climate Change Impact Partnership, a partnership of scientists, government, its agencies, and NGOs, by providing information on ocean CO2 uptake, changes in ocean pH, and potential impacts on global climate and marine ecosystems.
Synthetic Lipid (DOPG) Vesicles Accumulate in the Cell Plate Region But Do Not Fuse
Authors: Esseling-Ozdoba Agnieszka , Vos Jan W. , van Lammeren André A.M. , Emons Anne Mie C. 
Published: June 2008

Abstract
The cell plate is the new cell wall, with bordering plasma membrane, that is formed between two daughter cells in plants, and it is formed by fusion of vesicles (approximately 60 nm). To start to determine physical properties of cell plate forming vesicles for their transport through the phragmoplast, and fusion with each other, we microinjected fluorescent synthetic lipid vesicles that were made of 1,2-dioleoyl-sn-glycero-3-[phospho-rac-(1-glycerol)] (DOPG) into Tradescantia virginiana stamen hair cells. During interphase, the 60-nm wide DOPG vesicles moved inside the cytoplasm comparably to organelles. During cytokinesis, they were transported through the phragmoplast and accumulated in the cell plate region together with the endogenous vesicles, even inside the central cell plate region. Because at this stage microtubules are virtually absent from that region, while actin filaments are present, actin filaments may have a role in the transport of vesicles toward the cell plate. Unlike the endogenous vesicles, the synthetic DOPG vesicles did not fuse with the developing cell plate. Instead, they redistributed into the cytoplasm of the daughter cells upon completion of cytokinesis. Because the redistribution of the vesicles occurs when actin filaments disappear from the phragmoplast, actin filaments may be involved in keeping the vesicles inside the developing cell plate region.
Genetic Evidence That Cellulose Synthase Activity Influences Microtubule Cortical Array Organization
Authors: Paredez Alexander R. , Persson Staffan , Ehrhardt David W. , Somerville Chris R. 
Published: June 2008

Abstract
To identify factors that influence cytoskeletal organization we screened for Arabidopsis (Arabidopsis thaliana) mutants that show hypersensitivity to the microtubule destabilizing drug oryzalin. We cloned the genes corresponding to two of the 131 mutant lines obtained. The genes encoded mutant alleles of PROCUSTE1 and KORRIGAN, which both encode proteins that have previously been implicated in cellulose synthesis. Analysis of microtubules in the mutants revealed that both mutants have altered orientation of root cortical microtubules. Similarly, isoxaben, an inhibitor of cellulose synthesis, also altered the orientation of cortical microtubules while exogenous cellulose degradation did not. Thus, our results substantiate that proteins involved in cell wall biosynthesis influence cytoskeletal organization and indicate that this influence on cortical microtubule stability and orientation is correlated with cellulose synthesis rather than the integrity of the cell wall.
ThePRA1Gene Family in Arabidopsis
Authors: Alvim Kamei Claire Lessa , Boruc Joanna , Vandepoele Klaas , Van den Daele Hilde , Maes Sara , Russinova Eugenia , Inzé Dirk , De Veylder Lieven 
Published: June 2008

AbstractPrenylated Rab acceptor 1 (PRA1) domain proteins are small transmembrane proteins that regulate vesicle trafficking as receptors of Rab GTPases and the vacuolar soluble N-ethylmaleimide-sensitive factor attachment receptor protein VAMP2. However, little is known about PRA1 family members in plants. Sequence analysis revealed that higher plants, compared with animals and primitive plants, possess an expanded family of PRA1 domain-containing proteins. The Arabidopsis (Arabidopsis thaliana) PRA1 (AtPRA1) proteins were found to homodimerize and heterodimerize in a manner corresponding to their phylogenetic distribution. Different AtPRA1 family members displayed distinct expression patterns, with a preference for vascular cells and expanding or developing tissues. AtPRA1 genes were significantly coexpressed with Rab GTPases and genes encoding vesicle transport proteins, suggesting an involvement in the vesicle trafficking process similar to that of their animal counterparts. Correspondingly, AtPRA1 proteins were localized in the endoplasmic reticulum, Golgi apparatus, and endosomes/prevacuolar compartments, hinting at a function in both secretory and endocytic intracellular trafficking pathways. Taken together, our data reveal a high functional diversity of AtPRA1 proteins, probably dealing with the various demands of the complex trafficking system.