bluuebunny/crossref_metadata_2025_split huggingface dataset:
Culturally competence care of moroccan migrants
Authors: Moussaoui D. 
Published: May 2011

About 15% of all Moroccans live abroad (4 and a half million), mostly in Europe and North America. For historic reasons, migration of Moroccans went essentially to France, Belgium, Holland, and more recently to Spain. Many of these migrants are well integrated, but many others do suffer from social bad integration. Those with mental disorders are probably those who are most at risk of non-integration.Mental health workers are not always aware of the cultural background of the Moroccan migrant, including family structure and interactions, religious and traditional beliefs. In France and Holland, and recently in Spain, a few teams are highly interested in transcultural psychiatry and provide care to the migrants and teaching to other mental health professionals. Their number and resources are however far from being sufficient to cover all the field in the entire country. One of the solutions is to develop a teaching program for post-graduates in psychiatry on "Cultural sensitivity" in all departments of psychiatry. A collaboration between mental health workers from the North and the South of the Mediterranean Sea is highly desirable in this respect. This is why the Euro-Med Network on Migration and Mental Health was created in 2007.
Study of the optical response of Si-rich a-SiNx : H thin film near Si L2,3-edge using soft x-ray reflectivity
Authors: Singh Sarab Preet , Modi Mohammed H , Srivastava P 
Published: May 2011

Angle-dependent soft x-ray reflectivity measurements in the photon energy range 82.67–248 eV near the Si L
2,3 absorption edge have been performed on Si-rich a-SiN
x
: H (SRSN) thin film deposited by the Hg-sensitized photo-chemical vapour deposition technique. It is found that experimentally obtained δ (dispersion) values of the SRSN film lie in between that of pure silicon (Si) and silicon nitride (Si3N4). X-ray photoelectron spectroscopy measurements suggest that excess silicon is responsible for reducing optical constants values and hence by controlling the silicon amount one can tune the optical constants to desired values. We further compare the soft x-ray optical spectrum of the SRSN film with those of other silicon compounds such as silicon carbide (SiC) and silicon monoxide (SiO) near the Si L
2,3 edge region to shows its possibility as a prospective material for the next generation 13.5 nm (91.85 eV) node extreme ultraviolet (EUV) lithography technology.
A multiple network learning approach to capture system-wide condition-specific responses
Authors: Roy Sushmita , Werner-Washburne Margaret , Lane Terran 
Published: May 2011

AbstractMotivation: Condition-specific networks capture system-wide behavior under varying conditions such as environmental stresses, cell types or tissues. These networks frequently comprise parts that are unique to each condition, and parts that are shared among related conditions. Existing approaches for learning condition-specific networks typically identify either only differences or only similarities across conditions. Most of these approaches first learn networks per condition independently, and then identify similarities and differences in a post-learning step. Such approaches do not exploit the shared information across conditions during network learning.Results: We describe an approach for learning condition-specific networks that identifies the shared and unique subgraphs during network learning simultaneously, rather than as a post-processing step. Our approach learns networks across condition sets, shares data from different conditions and produces high-quality networks that capture biologically meaningful information. On simulated data, our approach outperformed an existing approach that learns networks independently for each condition, especially for small training datasets. On microarray data of hundreds of deletion mutants in two, yeast stationary-phase cell populations, the inferred network structure identified several common and population-specific effects of these deletion mutants and several high-confidence cases of double-deletion pairs, which can be experimentally tested. Our results are consistent with and extend the existing knowledge base of differentiated cell populations in yeast stationary phase.Availability and Implementation: C++ code can be accessed from http://www.broadinstitute.org/~sroy/condspec/Contact: sroy@broadinstitute.orgSupplementary information: Supplementary data are available at Bioinformatics online.
The strength of chemical linkage as a criterion for pruning metabolic graphs
Authors: Zhou Wanding , Nakhleh Luay 
Published: May 2011

Abstract
Motivation: A metabolic graph represents the connectivity patterns of a metabolic system, and provides a powerful framework within which the organization of metabolic reactions can be analyzed and elucidated. A common practice is to prune (i.e. remove nodes and edges) the metabolic graph prior to any analysis in order to eliminate confounding signals from the representation. Currently, this pruning process is carried out in an ad hoc fashion, resulting in discrepancies and ambiguities across studies.
Results: We propose a biochemically informative criterion, the strength of chemical linkage (SCL), for a systematic pruning of metabolic graphs. By analyzing the metabolic graph of Escherichia coli, we show that thresholding SCL is powerful in selecting the conventional pathways' connectivity out of the raw network connectivity when the network is restricted to the reactions collected from these pathways. Further, we argue that the root of ambiguity in pruning metabolic graphs is in the continuity of the amount of chemical content that can be conserved in reaction transformation patterns. Finally, we demonstrate how biochemical pathways can be inferred efficiently if the search procedure is guided by SCL.
Contact: wz4@rice.edu; nakhleh@rice.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Application of the Bayesian MMSE estimator for classification error to gene expression microarray data
Authors: Dalton Lori A. , Dougherty Edward R. 
Published: May 2011

Abstract
Motivation: With the development of high-throughput genomic and proteomic technologies, coupled with the inherent difficulties in obtaining large samples, biomedicine faces difficult small-sample classification issues, in particular, error estimation. Most popular error estimation methods are motivated by intuition rather than mathematical inference. A recently proposed error estimator based on Bayesian minimum mean square error estimation places error estimation in an optimal filtering framework. In this work, we examine the application of this error estimator to gene expression microarray data, including the suitability of the Gaussian model with normal–inverse-Wishart priors and how to find prior probabilities.
Results: We provide an implementation for non-linear classification, where closed form solutions are not available. We propose a methodology for calibrating normal-inverse-Wishart priors based on discarded microarray data and examine the performance on synthetic high-dimensional data and a real dataset from a breast cancer study. The calibrated Bayesian error estimator has superior root mean square performance, especially with moderate to high expected true errors and small feature sizes.
Availability: We have implemented in C code the Bayesian error estimator for Gaussian distributions and normal–inverse-Wishart priors for both linear classifiers, with exact closed-form representations, and arbitrary classifiers, where we use a Monte Carlo approximation. Our code for the Bayesian error estimator and a toolbox of related utilities are available at http://gsp.tamu.edu/Publications/supplementary/dalton11a. Several supporting simulations are also included.
Contact: ldalton@tamu.edu
Supplementary Information: Supplementary data are available at Bioinformatics online.
TVNViewer: An interactive visualization tool for exploring networks that change over time or space
Authors: Curtis Ross E. , Yuen Amos , Song Le , Goyal Anuj , Xing Eric P. 
Published: May 2011

Abstract
Summary: The relationship between genes and proteins is a dynamic relationship that changes across time and differs in different cells. The study of these differences can reveal various insights into biological processes and disease progression, especially with the aid of proper tools for network visualization. Toward this purpose, we have developed TVNViewer, a novel visualization tool, which is specifically designed to aid in the exploration and analysis of dynamic networks.
Availability: TVNViewer is freely available with documentation and tutorials on the web at http://sailing.cs.cmu.edu/tvnviewer.
Contact: epxing@cs.cmu.edu
Identification of prokaryotic small proteins using a comparative genomic approach
Authors: Samayoa Josue , Yildiz Fitnat H. , Karplus Kevin 
Published: May 2011

Abstract
Motivation: Accurate prediction of genes encoding small proteins (on the order of 50 amino acids or less) remains an elusive open problem in bioinformatics. Some of the best methods for gene prediction use either sequence composition analysis or sequence similarity to a known protein coding sequence. These methods often fail for small proteins, however, either due to a lack of experimentally verified small protein coding genes or due to the limited statistical significance of statistics on small sequences.
Our approach is based upon the hypothesis that true small proteins will be under selective pressure for encoding the particular amino acid sequence, for ease of translation by the ribosome and for structural stability. This stability can be achieved either independently or as part of a larger protein complex. Given this assumption, it follows that small proteins should display conserved local protein structure properties much like larger proteins. Our method incorporates neural-net predictions for three local structure alphabets within a comparative genomic approach using a genomic alignment of 22 closely related bacteria genomes to generate predictions for whether or not a given open reading frame (ORF) encodes for a small protein.
Results: We have applied this method to the complete genome for Escherichia coli strain K12 and looked at how well our method performed on a set of 60 experimentally verified small proteins from this organism. Out of a total of 11 407 possible ORFs, we found that 6 of the top 10 and 27 of the top 100 predictions belonged to the set of 60 experimentally verified small proteins. We found 35 of all the true small proteins within the top 200 predictions. We compared our method to Glimmer, using a default Glimmer protocol and a modified small ORF Glimmer protocol with a lower minimum size cutoff. The default Glimmer protocol identified 16 of the true small proteins (all in the top 200 predictions), but failed to predict on 34 due to size cutoffs. The small ORF Glimmer protocol made predictions for all the experimentally verified small proteins but only contained 9 of the 60 true small proteins within the top 200 predictions.
Contact: jsamayoa@jhu.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
MPEA—metabolite pathway enrichment analysis
Authors: Kankainen Matti , Gopalacharyulu Peddinti , Holm Liisa , Orešič Matej 
Published: May 2011

Abstract
Summary: We present metabolite pathway enrichment analysis (MPEA) for the visualization and biological interpretation of metabolite data at the system level. Our tool follows the concept of gene set enrichment analysis (GSEA) and tests whether metabolites involved in some predefined pathway occur towards the top (or bottom) of a ranked query compound list. In particular, MPEA is designed to handle many-to-many relationships that may occur between the query compounds and metabolite annotations. For a demonstration, we analysed metabolite profiles of 14 twin pairs with differing body weights. MPEA found significant pathways from data that had no significant individual query compounds, its results were congruent with those discovered from transcriptomics data and it detected more pathways than the competing metabolic pathway method did.
Availability: The web server and source code of MPEA are available at http://ekhidna.biocenter.helsinki.fi/poxo/mpea/.
Contact: matti.kankainen@helsinki.fi
Supplementary information: Supplementary data are available at Bioinformatics online.
A cautionary note for retrocopy identification: DNA-based duplication of intron-containing genes significantly contributes to the origination of single exon genes
Authors: Zhang Yong E. , Vibranovski Maria D. , Krinsky Benjamin H. , Long Manyuan 
Published: May 2011

Abstract
Motivation: Retrocopies are important genes in the genomes of almost all higher eukaryotes. However, the annotation of such genes is a non-trivial task. Intronless genes have often been considered to be retroposed copies of intron-containing paralogs. Such categorization relies on the implicit premise that alignable regions of the duplicates should be long enough to cover exon–exon junctions of the intron-containing genes, and thus intron loss events can be inferred. Here, we examined the alternative possibility that intronless genes could be generated by partial DNA-based duplication of intron-containing genes in the fruitfly genome.
Results: By building pairwise protein-, transcript- and genome-level DNA alignments between intronless genes and their corresponding intron-containing paralogs, we found that alignments do not cover exon–exon junctions in 40% of cases and thus no intron loss could be inferred. For these cases, the candidate parental proteins tend to be partially duplicated, and intergenic sequences or neighboring genes are included in the intronless paralog. Moreover, we observed that it is significantly less likely for these paralogs to show inter-chromosomal duplication and testis-dominant transcription, compared to the remaining 60% of cases with evidence of clear intron loss (retrogenes). These lines of analysis reveal that DNA-based duplication contributes significantly to the 40% of cases of single exon gene duplication. Finally, we performed an analogous survey in the human genome and the result is similar, wherein 34% of the cases do not cover exon–exon junctions. Thus, genome annotation for retrogene identification should discard candidates without clear evidence of intron loss.
Contact: mlong@uchicago.edu; zhangy@uchicago.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Creating views on integrated multidomain data
Authors: Rohn Hendrik , Klukas Christian , Schreiber Falk 
Published: May 2011

Abstract
Motivation: Modern data acquisition methods in biology allow the procurement of different types of data in increasing quantity, facilitating a comprehensive view of biological systems. As data are usually gathered and interpreted by separate domain scientists, it is hard to grasp multidomain properties and structures. Consequently, there is a need for the integration of biological data from different sources and of different types in one application, providing various visualization approaches.
Results: In this article, methods for the integration and visualization of multimodal biological data are presented. This is achieved based on two graphs representing the meta-relations between biological data and the measurement combinations, respectively. Both graphs are linked and serve as different views of the integrated data with navigation and exploration possibilities. Data can be combined and visualized multifariously, resulting in views of the integrated biological data.
Availability: http://vanted.ipk-gatersleben.de/hive/.
Contact: rohn@ipk-gatersleben.de
Integrative gene network construction for predicting a set of complementary prostate cancer genes
Authors: Ahn Jaegyoon , Yoon Youngmi , Park Chihyun , Shin Eunji , Park Sanghyun 
Published: May 2011

Abstract
Motivation: Diagnosis and prognosis of cancer and understanding oncogenesis within the context of biological pathways is one of the most important research areas in bioinformatics. Recently, there have been several attempts to integrate interactome and transcriptome data to identify subnetworks that provide limited interpretations of known and candidate cancer genes, as well as increase classification accuracy. However, these studies provide little information about the detailed roles of identified cancer genes.
Results: To provide more information to the network, we constructed the network by incorporating genetic interactions and manually curated gene regulations to the protein interaction network. To make our newly constructed network cancer specific, we identified edges where two genes show different expression patterns between cancer and normal phenotypes. We showed that the integration of various datasets increased classification accuracy, which suggests that our network is more complete than a network based solely on protein interactions. We also showed that our network contains significantly more known cancer-related genes than other feature selection algorithms. Through observations of some examples of cancer-specific subnetworks, we were able to predict more detailed and interpretable roles of oncogenes and other cancer candidate genes in the prostate cancer cells.
Availability: http://embio.yonsei.ac.kr/~Ahn/tc.php.
Contact: sanghyun@cs.yonsei.ac.kr
Supplementary information: Supplementary data are available at Bioinformatics online.
Sim4db and Leaff: utilities for fast batch spliced alignment and sequence indexing
Authors: Walenz Brian , Florea Liliana 
Published: May 2011

Abstract
Summary: The large number of genomes that will be sequenced will need to be annotated with genes and other functional features. Aligning gene sequences from a related species to the target genome is an economical and highly reliable method to identify genes; unfortunately, existing tools have been lacking in sensitivity and speed. A program we reported, sim4cc, was shown to be highly accurate but is limited to comparing one cDNA with one genomic sequence. We present here an optimization of the tool, implemented in the packages sim4db and leaff. The new tool performs batch alignments of cDNA and genomic sequences in a fraction of the time required by its predecessor, and thus is very well suited for genome-wide analyses.
Availability: Sim4db and leaff are written in C, C++ and Perl for Linux and other Unix platforms. Source code is distributed free of charge from http://sourceforge.net/projects/kmer/.
Contact: florea@umiacs.umd.edu
Supplementary information: Supplementary data are available at Bioinformatics Online.
An MCMC algorithm for detecting short adjacent repeats shared by multiple sequences
Authors: Li Qiwei , Fan Xiaodan , Liang Tong , Li Shuo−Yen R. 
Published: May 2011

Abstract
Motivation: Repeats detection problems are traditionally formulated as string matching or signal processing problems. They cannot readily handle gaps between repeat units and are incapable of detecting repeat patterns shared by multiple sequences. This study detects short adjacent repeats with interunit insertions from multiple sequences. For biological sequences, such studies can shed light on molecular structure, biological function and evolution.
Results: The task of detecting short adjacent repeats is formulated as a statistical inference problem by using a probabilistic generative model. An Markov chain Monte Carlo algorithm is proposed to infer the parameters in a de novo fashion. Its applications on synthetic and real biological data show that the new method not only has a competitive edge over existing methods, but also can provide a way to study the structure and the evolution of repeat-containing genes.
Availability: The related C++ source code and datasets are available at http://ihome.cuhk.edu.hk/%7Eb118998/share/BASARD.zip.
Contact: xfan@sta.cuhk.edu.hk
Supplementary information: Supplementary data are available at Bioinformatics online.
The role of indirect connections in gene networks in predicting function
Authors: Gillis Jesse , Pavlidis Paul 
Published: May 2011

AbstractMotivation: Gene networks have been used widely in gene function prediction algorithms, many based on complex extensions of the ‘guilt by association’ principle. We sought to provide a unified explanation for the performance of gene function prediction algorithms in exploiting network structure and thereby simplify future analysis.Results: We use co-expression networks to show that most exploited network structure simply reconstructs the original correlation matrices from which the co-expression network was obtained. We show the same principle works in predicting gene function in protein interaction networks and that these methods perform comparably to much more sophisticated gene function prediction algorithms.Availability and implementation: Data and algorithm implementation are fully described and available at http://www.chibi.ubc.ca/extended. Programs are provided in Matlab m-code.Contact: paul@chibi.ubc.caSupplementary information: Supplementary data are available at Bioinformatics online.
Genome-wide DNA sequence polymorphisms facilitate nucleosome positioning in yeast
Authors: Dai Zhiming , Dai Xianhua , Xiang Qian 
Published: May 2011

Abstract
Motivation: The intrinsic DNA sequence is an important determinant of nucleosome positioning. Some DNA sequence patterns can facilitate nucleosome formation, while others can inhibit nucleosome formation. Nucleosome positioning influences the overall rate of sequence evolution. However, its impacts on specific patterns of sequence evolution are still poorly understood.
Results: Here, we examined whether nucleosomal DNA and nucleosome-depleted DNA show distinct polymorphism patterns to maintain adequate nucleosome architecture on a genome scale in yeast. We found that sequence polymorphisms in nucleosomal DNA tend to facilitate nucleosome formation, whereas polymorphisms in nucleosome-depleted DNA tend to inhibit nucleosome formation, which is especially evident at nucleosome-disfavored sequences in nucleosome-free regions at both ends of genes. Sequence polymorphisms facilitating nucleosome positioning correspond to stable nucleosome positioning. These results reveal that sequence polymorphisms are under selective constraints to maintain nucleosome positioning.
Contact: zhimdai@gmail.com; issdxh@mail.sysu.edu.cn
Supplementary information: Supplementary data are available at Bioinformatics online.