bluuebunny/crossref_metadata_2025_split huggingface dataset:
Proteinase-activated receptor 4 stimulation-induced epithelial-mesenchymal transition in alveolar epithelial cells
Authors: Ando Seijitsu , Otani Hitomi , Yagi Yasuhiro , Kawai Kenzo , Araki Hiromasa , Fukuhara Shirou , Inagaki Chiyoko 
Published: May 2007

Abstract

Background
Proteinase-activated receptors (PARs; PAR1–4) that can be activated by serine proteinases such as thrombin and neutrophil catepsin G are known to contribute to the pathogenesis of various pulmonary diseases including fibrosis. Among these PARs, especially PAR4, a newly identified subtype, is highly expressed in the lung. Here, we examined whether PAR4 stimulation plays a role in the formation of fibrotic response in the lung, through alveolar epithelial-mesenchymal transition (EMT) which contributes to the increase in myofibroblast population.

Methods
EMT was assessed by measuring the changes in each specific cell markers, E-cadherin for epithelial cell, α-smooth muscle actin (α-SMA) for myofibroblast, using primary cultured mouse alveolar epithelial cells and human lung carcinoma-derived alveolar epithelial cell line (A549 cells).

Results
Stimulation of PAR with thrombin (1 U/ml) or a synthetic PAR4 agonist peptide (AYPGKF-NH2, 100 μM) for 72 h induced morphological changes from cobblestone-like structure to elongated shape in primary cultured alveolar epithelial cells and A549 cells. In immunocytochemical analyses of these cells, such PAR4 stimulation decreased E-cadherin-like immunoreactivity and increased α-SMA-like immunoreactivity, as observed with a typical EMT-inducer, tumor growth factor-β (TGF-β). Western blot analyses of PAR4-stimulated A549 cells also showed similar changes in expression of these EMT-related marker proteins. Such PAR4-mediated changes were attenuated by inhibitors of epidermal growth factor receptor (EGFR) kinase and Src. PAR4-mediated morphological changes in primary cultured alveolar epithelial cells were reduced in the presence of these inhibitors. PAR4 stimulation increased tyrosine phosphorylated EGFR or tyrosine phosphorylated Src level in A549 cells, and the former response being inhibited by Src inhibitor.

Conclusion
PAR4 stimulation of alveolar epithelial cells induced epithelial-mesenchymal transition (EMT) as monitored by cell shapes, and epithelial or myofibroblast marker at least partly through EGFR transactivation via receptor-linked Src activation.
HMM-ModE – Improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences
Authors: Srivastava Prashant K , Desai Dhwani K , Nandi Soumyadeep , Lynn Andrew M 
Published: May 2007

Abstract

Background
Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have been used in identifying remote homologues with considerable success. These conservation patterns arise from fold specific signals, shared across multiple families, and function specific signals unique to the families. The availability of sequences pre-classified according to their function permits the use of negative training sequences to improve the specificity of the HMM, both by optimizing the threshold cutoff and by modifying emission probabilities to minimize the influence of fold-specific signals. A protocol to generate family specific HMMs is described that first constructs a profile HMM from an alignment of the family's sequences and then uses this model to identify sequences belonging to other classes that score above the default threshold (false positives). Ten-fold cross validation is used to optimise the discrimination threshold score for the model. The advent of fast multiple alignment methods enables the use of the profile alignments to align the true and false positive sequences, and the resulting alignments are used to modify the emission probabilities in the original model.

Results
The protocol, called HMM-ModE, was validated on a set of sequences belonging to six sub-families of the AGC family of kinases. These sequences have an average sequence similarity of 63% among the group though each sub-group has a different substrate specificity. The optimisation of discrimination threshold, by using negative sequences scored against the model improves specificity in test cases from an average of 21% to 98%. Further discrimination by the HMM after modifying model probabilities using negative training sequences is provided in a few cases, the average specificity rising to 99%. Similar improvements were obtained with a sample of G-Protein coupled receptors sub-classified with respect to their substrate specificity, though the average sequence identity across the sub-families is just 20.6%. The protocol is applied in a high-throughput classification exercise on protein kinases.

Conclusion
The protocol has the potential to maximise the contributions of discriminating residues to classify proteins based on their molecular function, using pre-classified positive and negative sequence training data. The high specificity of the method, and increasing availability of pre-classified sequence data holds the potential for its application in sequence annotation.
A meta-data based method for DNA microarray imputation
Authors: Jörnsten Rebecka , Ouyang Ming , Wang Hui-Yu 
Published: May 2007

AbstractBackgroundDNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting.ResultsWe download all cDNA microarray data ofSaccharomyces cerevisiae, Arabidopsis thaliana, andCaenorhabditis elegansfrom the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones.ConclusionSince downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.
Evaluation of gene-expression clustering via mutual information distance measure
Authors: Priness Ido , Maimon Oded , Ben-Gal Irad 
Published: May 2007

Abstract

Background
The definition of a distance measure plays a key role in the evaluation of different clustering solutions of gene expression profiles. In this empirical study we compare different clustering solutions when using the Mutual Information (MI) measure versus the use of the well known Euclidean distance and Pearson correlation coefficient.

Results
Relying on several public gene expression datasets, we evaluate the homogeneity and separation scores of different clustering solutions. It was found that the use of the MI measure yields a more significant differentiation among erroneous clustering solutions. The proposed measure was also used to analyze the performance of several known clustering algorithms. A comparative study of these algorithms reveals that their "best solutions" are ranked almost oppositely when using different distance measures, despite the found correspondence between these measures when analysing the averaged scores of groups of solutions.

Conclusion
In view of the results, further attention should be paid to the selection of a proper distance measure for analyzing the clustering of gene expression data.
Locational distribution of gene functional classes in Arabidopsis thaliana
Authors: Riley Michael C , Clare Amanda , King Ross D 
Published: May 2007

Abstract

Background
We are interested in understanding the locational distribution of genes and their functions in genomes, as this distribution has both functional and evolutionary significance. Gene locational distribution is known to be affected by various evolutionary processes, with tandem duplication thought to be the main process producing clustering of homologous sequences. Recent research has found clustering of protein structural families in the human genome, even when genes identified as tandem duplicates have been removed from the data. However, this previous research was hindered as they were unable to analyse small sample sizes. This is a challenge for bioinformatics as more specific functional classes have fewer examples and conventional statistical analyses of these small data sets often produces unsatisfactory results.

Results
We have developed a novel bioinformatics method based on Monte Carlo methods and Greenwood's spacing statistic for the computational analysis of the distribution of individual functional classes of genes (from GO). We used this to make the first comprehensive statistical analysis of the relationship between gene functional class and location on a genome. Analysis of the distribution of all genes except tandem duplicates on the five chromosomes of A. thaliana reveals that the distribution on chromosomes I, II, IV and V is clustered at P = 0.001. Many functional classes are clustered, with the degree of clustering within an individual class generally consistent across all five chromosomes. A novel and surprising result was that the locational distribution of some functional classes were significantly more evenly spaced than would be expected by chance.

Conclusion
Analysis of the A. thaliana genome reveals evidence of unexplained order in the locational distribution of genes. The same general analysis method can be applied to any genome, and indeed any sequential data involving classes.
From genes to functional classes in the study of biological systems
Authors: Al-Shahrour Fátima , Arbiza Leonardo , Dopazo Hernán , Huerta-Cepas Jaime , Mínguez Pablo , Montaner David , Dopazo Joaquín 
Published: May 2007

AbstractBackgroundWith the popularisation of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed.ResultsHere we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics.ConclusionMethods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at:http://www.babelomics.org.
VSGdb: a database for trypanosome variant surface glycoproteins, a large and diverse family of coiled coil proteins
Authors: Marcello Lucio , Menon Suraj , Ward Pauline , Wilkes Jonathan M , Jones Nicola G , Carrington Mark , Barry J David 
Published: May 2007

AbstractBackgroundTrypanosomes are coated with a variant surface glycoprotein (VSG) that is so densely packed that it physically protects underlying proteins from effectors of the host immune system. Periodically cells expressing a distinct VSG arise in a population and thereby evade immunity. The main structural feature of VSGs are two long α-helices that form a coiled coil, and sets of relatively unstructured loops that are distal to the plasma membrane and contain most or all of the protective epitopes. The primary structure of different VSGs is highly variable, typically displaying only ~20% identity with each other. The genome has nearly 2000VSGgenes, which are located in subtelomeres. Only one VSG gene is expressed at a time, and switching betweenVSGs primarily involves gene conversion events. The archive of silentVSGs undergoes diversifying evolution rapidly, also involving gene conversion. The VSG family is a paradigm for α helical coiled coil structures, epitope variation and GPI-anchor signals. At the DNA level, the genes are a paradigm for diversifying evolutionary processes and for the role of subtelomeres and recombination mechanisms in generation of diversity in multigene families. To enable ready availability ofVSGsequences for addressing these general questions, and trypanosome-specific questions, we have created VSGdb, a database of all known sequences.DescriptionVSGdb contains fully annotatedVSGsequences from the genome sequencing project, with which it shares all identifiers and annotation, and other available sequences. The database can be queried in various ways. Sequence retrieval, in FASTA format, can deliver protein or nucleotide sequence filtered by chromosomes or contigs, gene type (functional, pseudogene, etc.), domain and domain sequence family. Retrieved sequences can be stored as a temporary database for BLAST querying, reports from which include hyperlinks to the genome project database (GeneDB) CDS Info and to individual VSGdb pages for each VSG, containing annotation and sequence data. Queries (text search) with specific annotation terms yield a list of relevant VSGs, displayed as identifiers leading again to individual VSG web pages.ConclusionVSGdbhttp://www.vsgdb.org/is a freely available, web-based platform enabling easy retrieval, via various filters, of sets of VSGs that will enable detailed analysis of a number of general and trypanosome-specific questions, regarding protein structure potential, epitope variability, sequence evolution and recombination events.
Normalization method for metabolomics data using optimal selection of multiple internal standards
Authors: Sysi-Aho Marko , Katajamaa Mikko , Yetukuri Laxman , Orešič Matej 
Published: May 2007

AbstractBackgroundSuccess of metabolomics as the phenotyping platform largely depends on its ability to detect various sources of biological variability. Removal of platform-specific sources of variability such as systematic error is therefore one of the foremost priorities in data preprocessing. However, chemical diversity of molecular species included in typical metabolic profiling experiments leads to different responses to variations in experimental conditions, making normalization a very demanding task.ResultsWith the aim to remove unwanted systematic variation, we present an approach that utilizes variability information from multiple internal standard compounds to find optimal normalization factor for each individual molecular species detected by metabolomics approach (NOMIS). We demonstrate the method on mouse liver lipidomic profiles using Ultra Performance Liquid Chromatography coupled to high resolution mass spectrometry, and compare its performance to two commonly utilized normalization methods: normalization byl2norm and by retention time region specific standard compound profiles. The NOMIS method proved superior in its ability to reduce the effect of systematic error across the full spectrum of metabolite peaks. We also demonstrate that the method can be used to select best combinations of standard compounds for normalization.ConclusionDepending on experiment design and biological matrix, the NOMIS method is applicable either as a one-step normalization method or as a two-step method where the normalization parameters, influenced by variabilities of internal standard compounds and their correlation to metabolites, are first calculated from a study conducted in repeatability conditions. The method can also be used in analytical development of metabolomics methods by helping to select best combinations of standard compounds for a particular biological matrix and analytical platform.
Linear array of conserved sequence motifs to discriminate protein subfamilies: study on pyridine nucleotide-disulfide reductases
Authors: Avila César L , Rapisarda Viviana A , Farías Ricardo N , De Las Rivas Javier , Chehín Rosana 
Published: May 2007

AbstractBackgroundThe pyridine nucleotide disulfide reductase (PNDR) is a large and heterogeneous protein family divided into two classes (I and II), which reflect the divergent evolution of its characteristic disulfide redox active site. However, not all the PNDR members fit into these categories and this suggests the need of further studies to achieve a more comprehensive classification of this complex family.ResultsA workflow to improve the clusterization of protein families based on the array of linear conserved motifs is designed. The method is applied to the PNDR large family finding two main groups, which correspond to PNDR classes I and II. However, two other separate protein clusters, previously classified as class I in most databases, are outgrouped: the peroxide reductases (NAOX, NAPE) and the type II NADH dehydrogenases (NDH-2). In this way, two novel PNDR classes III and IV for NAOX/NAPE and NDH-2 respectively are proposed. By knowledge-driven biochemical and functional data analyses done on the new class IV, a linear array of motifs putatively related to Cu(II)-reductase activity is detected in a specific subset of NDH-2.ConclusionThe results presented are a novel contribution to the classification of the complex and large PNDR protein family, supporting its reclusterization into four classes. The linear array of motifs detected within the class IV PNDR subfamily could be useful as a signature for a particular subgroup of NDH-2.
Including probe-level uncertainty in model-based gene expression clustering
Authors: Liu Xuejun , Lin Kevin K , Andersen Bogi , Rattray Magnus 
Published: May 2007

AbstractBackgroundClustering is an important analysis performed on microarray gene expression data since it groups genes which have similar expression patterns and enables the exploration of unknown gene functions. Microarray experiments are associated with many sources of experimental and biological variation and the resulting gene expression data are therefore very noisy. Many heuristic and model-based clustering approaches have been developed to cluster this noisy data. However, few of them include consideration of probe-level measurement error which provides rich information about technical variability.ResultsWe augment a standard model-based clustering method to incorporate probe-level measurement error. Using probe-level measurements from a recently developed Affymetrix probe-level model, multi-mgMOS, we include the probe-level measurement error directly into the standard Gaussian mixture model. Our augmented model is shown to provide improved clustering performance on simulated datasets and a real mouse time-course dataset.ConclusionThe performance of model-based clustering of gene expression data is improved by including probe-level measurement error and more biologically meaningful clustering results are obtained.
Regulation of norrin receptor frizzled-4 by Wnt2 in colon-derived cells
Authors: Planutis Kestutis , Planutiene Marina , Moyer Mary Pat , Nguyen Anthony V , Pérez Cherlyn A , Holcombe Randall F 
Published: May 2007

Abstract

Background
Norrin is a potent Wnt pathway ligand. Aberrant activation of this signaling pathway can result in colon tumors but the role of norrin-based signaling in the genesis of colon cancer, and its relationship to activation of the pathway by traditional Wnt ligands, is not defined.

Results
Fresh normal human colon tissue and all the cell lines studied expressed mRNA for Fz4, LRP5 and norrin, except Colo205 which lacked Fz4 expression. Canonical Wnt pathway throughput was increased slightly in NCM460 following treatment with Wnt3a CM but was inhibited by Wnt2 and Wnt1. The colon cancer cell line, RKO, responded to Wnt3a CM, Wnt2 and Wnt1 by increasing canonical Wnt pathway throughput. Wnt5a did not affect Wnt pathway throughput in either cell line. Wnt2, but not Wnt3a, abrogated Fz4 expression in NCM460, but not in RKO or another colon cancer cell line, HCT116. This effect on Fz4 was confirmed at both the RNA and protein levels via RT-PCR and a norrin binding assay. The expression of all others 9 Fz receptors did not change after treatment of NCM460 cells with Wnt2.

Conclusion
The data suggests that colonic mucosa and colon tumors may possess two autoregulatory positive Wnt feedback loops, one through canonical signals induced by Wnt:Fz interactions and one through signals resulting from norrin:Fz4 interactions. The latter interactions may be modulated via regulation of Fz4 expression by Wnt2. Retention of Fz4 by cancers, in contrast to the loss of Fz4 by normal mucosal cells, could provide a selective advantage to the tumor cells. Fz4 expression may play a critical role in responses to Wnt signaling in the tumor microenvironment.