bluuebunny/crossref_metadata_2025_split huggingface dataset:
CLOE: Identification of putative functional relationships among genes by comparison of expression profiles between two species
Authors: Pellegrino Maurizio , Provero Paolo , Silengo Lorenzo , Di Cunto Ferdinando 
Published: January 2005

Abstract
Background
Public repositories of microarray data contain an incredible amount of information that is potentially relevant to explore functional relationships among genes by meta-analysis of expression profiles. However, the widespread use of this resource by the scientific community is at the moment limited by the limited availability of effective tools of analysis. We here describe CLOE, a simple cDNA microarray data mining strategy based on meta-analysis of datasets from pairs of species. The method consists in ranking EST probes in the datasets of the two species according to the similarity of their expression profiles with that of two EST probes from orthologous genes, and extracting orthologous EST pairs from a given top interval of the ranked lists. The Gene Ontology annotation of the obtained candidate partners is then analyzed for keywords overrepresentation.

Results
We demonstrate the capabilities of the approach by testing its predictive power on three proteomically-defined mammalian protein complexes, in comparison with single and multiple species meta-analysis approaches. Our results show that CLOE can find candidate partners for a greater number of genes, if compared to multiple species co-expression analysis, but retains a comparable specificity even when applied to species as close as mouse and human. On the other hand, it is much more specific than single organisms co-expression analysis, strongly reducing the number of potential candidate partners for a given gene of interest.

Conclusions
CLOE represents a simple and effective data mining approach that can be easily used for meta-analysis of cDNA microarray experiments characterized by very heterogeneous coverage. Importantly, it produces for genes of interest an average number of high confidence putative partners that is in the range of standard experimental validation techniques.
A new mixture model approach to analyzing allelic-loss data using Bayes factors
Authors: Desai Manisha , Emond Mary J 
Published: January 2005

Abstract
Background
Allelic-loss studies record data on the loss of genetic material in tumor tissue relative to normal tissue at various loci along the genome. As the deletion of a tumor suppressor gene can lead to tumor development, one objective of these studies is to determine which, if any, chromosome arms harbor tumor suppressor genes.

Results
We propose a large class of mixture models for describing the data, and we suggest using Bayes factors to select a reasonable model from the class in order to classify the chromosome arms. Bayes factors are especially useful in the case of testing that the number of components in a mixture model is n0 versus n1. In these cases, frequentist test statistics based on the likelihood ratio statistic have unknown distributions and are therefore not applicable. Our simulation study shows that Bayes factors favor the right model most of the time when tumor suppressor genes are present. When no tumor suppressor genes are present and background allelic-loss varies, the Bayes factors are often inconclusive, although this results in a markedly reduced false-positive rate compared to that of standard frequentist approaches. Application of our methods to three data sets of esophageal adenocarcinomas yields interesting differences from those results previously published.

Conclusions
Our results indicate that Bayes factors are useful for analyzing allelic-loss data.
Optimized LOWESS normalization parameter selection for DNA microarray data
Authors: Berger John A , Hautaniemi Sampsa , Järvinen Anna-Kaarina , Edgren Henrik , Mitra Sanjit K , Astola Jaakko 
Published: January 2005

Abstract
Background
Microarray data normalization is an important step for obtaining data that are reliable and usable for subsequent analysis. One of the most commonly utilized normalization techniques is the locally weighted scatterplot smoothing (LOWESS) algorithm. However, a much overlooked concern with the LOWESS normalization strategy deals with choosing the appropriate parameters. Parameters are usually chosen arbitrarily, which may reduce the efficiency of the normalization and result in non-optimally normalized data. Thus, there is a need to explore LOWESS parameter selection in greater detail.

Results and discussion
In this work, we discuss how to choose parameters for the LOWESS method. Moreover, we present an optimization approach for obtaining the fraction of data points utilized in the local regression and analyze results for local print-tip normalization. The optimization procedure determines the bandwidth parameter for the local regression by minimizing a cost function that represents the mean-squared difference between the LOWESS estimates and the normalization reference level. We demonstrate the utility of the systematic parameter selection using two publicly available data sets. The first data set consists of three self versus self hybridizations, which allow for a quantitative study of the optimization method. The second data set contains a collection of DNA microarray data from a breast cancer study utilizing four breast cancer cell lines. Our results show that different parameter choices for the bandwidth window yield dramatically different calibration results in both studies.

Conclusions
Results derived from the self versus self experiment indicate that the proposed optimization approach is a plausible solution for estimating the LOWESS parameters, while results from the breast cancer experiment show that the optimization procedure is readily applicable to real-life microarray data normalization. In summary, the systematic approach to obtain critical parameters in the LOWESS technique is likely to produce data that optimally meets assumptions made in the data preprocessing step and thereby makes studies utilizing the LOWESS method unambiguous and easier to repeat.
An SVD-based comparison of nine whole eukaryotic genomes supports a coelomate rather than ecdysozoan lineage
Authors: Stuart Gary W , Berry Michael W 
Published: January 2005

Abstract
Background
Eukaryotic whole genome sequences are accumulating at an impressive rate. Effective methods for comparing multiple whole eukaryotic genomes on a large scale are needed. Most attempted solutions involve the production of large scale alignments, and many of these require a high stringency pre-screen for putative orthologs in order to reduce the effective size of the dataset and provide a reasonably high but unknown fraction of correctly aligned homologous sites for comparison. As an alternative, highly efficient methods that do not require the pre-alignment of operationally defined orthologs are also being explored.

Results
A non-alignment method based on the Singular Value Decomposition (SVD) was used to compare the predicted protein complement of nine whole eukaryotic genomes ranging from yeast to man. This analysis resulted in the simultaneous identification and definition of a large number of well conserved motifs and gene families, and produced a species tree supporting one of two conflicting hypotheses of metazoan relationships.

Conclusions
Our SVD-based analysis of the entire protein complement of nine whole eukaryotic genomes suggests that highly conserved motifs and gene families can be identified and effectively compared in a single coherent definition space for the easy extraction of gene and species trees. While this occurs without the explicit definition of orthologs or homologous sites, the analysis can provide a basis for these definitions.
Predicting binding sites of hydrolase-inhibitor complexes by combining several methods
Authors: Sen Taner Z , Kloczkowski Andrzej , Jernigan Robert L , Yan Changhui , Honavar Vasant , Ho Kai-Ming , Wang Cai-Zhuang , Ihm Yungok , Cao Haibo , Gu Xun , Dobbs Drena 
Published: January 2005

Abstract
Background
Protein-protein interactions play a critical role in protein function. Completion of many genomes is being followed rapidly by major efforts to identify interacting protein pairs experimentally in order to decipher the networks of interacting, coordinated-in-action proteins. Identification of protein-protein interaction sites and detection of specific amino acids that contribute to the specificity and the strength of protein interactions is an important problem with broad applications ranging from rational drug design to the analysis of metabolic and signal transduction networks.

Results
In order to increase the power of predictive methods for protein-protein interaction sites, we have developed a consensus methodology for combining four different methods. These approaches include: data mining using Support Vector Machines, threading through protein structures, prediction of conserved residues on the protein surface by analysis of phylogenetic trees, and the Conservatism of Conservatism method of Mirny and Shakhnovich. Results obtained on a dataset of hydrolase-inhibitor complexes demonstrate that the combination of all four methods yield improved predictions over the individual methods.

Conclusions
We developed a consensus method for predicting protein-protein interface residues by combining sequence and structure-based methods. The success of our consensus approach suggests that similar methodologies can be developed to improve prediction accuracies for other bioinformatic problems.
A database for G proteins and their interaction with GPCRs
Authors: Elefsinioti Antigoni L , Bagos Pantelis G , Spyropoulos Ioannis C , Hamodrakas Stavros J 
Published: January 2005

Abstract
Background
G protein-coupled receptors (GPCRs) transduce signals from extracellular space into the cell, through their interaction with G proteins, which act as switches forming hetero-trimers composed of different subunits (α,β,γ). The α subunit of the G protein is responsible for the recognition of a given GPCR. Whereas specialised resources for GPCRs, and other groups of receptors, are already available, currently, there is no publicly available database focusing on G Proteins and containing information about their coupling specificity with their respective receptors.

Description
gpDB is a publicly accessible G proteins/GPCRs relational database. Including species homologs, the database contains detailed information for 418 G protein monomers (272 Gα, 87 Gβ and 59 Gγ) and 2782 GPCRs sequences belonging to families with known coupling to G proteins. The GPCRs and the G proteins are classified according to a hierarchy of different classes, families and sub-families, based on extensive literature searchs. The main innovation besides the classification of both G proteins and GPCRs is the relational model of the database, describing the known coupling specificity of the GPCRs to their respective α subunit of G proteins, a unique feature not available in any other database. There is full sequence information with cross-references to publicly available databases, references to the literature concerning the coupling specificity and the dimerization of GPCRs and the user may submit advanced queries for text search. Furthermore, we provide a pattern search tool, an interface for running BLAST against the database and interconnectivity with PRED-TMR, PRED-GPCR and TMRPres2D.

Conclusions
The database will be very useful, for both experimentalists and bioinformaticians, for the study of G protein/GPCR interactions and for future development of predictive algorithms. It is available for academics, via a web browser at the URL: http://bioinformatics.biol.uoa.gr/gpDB
A novel method for prokaryotic promoter prediction based on DNA stability
Authors: Kanhere Aditi , Bansal Manju 
Published: January 2005

Abstract
Background
In the post-genomic era, correct gene prediction has become one of the biggest challenges in genome annotation. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. This work presents a novel prokaryotic promoter prediction method based on DNA stability.

Results
The promoter region is less stable and hence more prone to melting as compared to other genomic regions. Our analysis shows that a method of promoter prediction based on the differences in the stability of DNA sequences in the promoter and non-promoter region works much better compared to existing prokaryotic promoter prediction programs, which are based on sequence motif searches. At present the method works optimally for genomes such as that of Escherichia coli, which have near 50 % G+C composition and also performs satisfactorily in case of other prokaryotic promoters.

Conclusions
Our analysis clearly shows that the change in stability of DNA seems to provide a much better clue than usual sequence motifs, such as Pribnow box and -35 sequence, for differentiating promoter region from non-promoter regions. To a certain extent, it is more general and is likely to be applicable across organisms. Hence incorporation of such features in addition to the signature motifs can greatly improve the presently available promoter prediction programs.
Activation of α1A-adrenergic receptor promotes differentiation of rat-1 fibroblasts to a smooth muscle-like phenotype
Authors: Saeed Abdelwahab E , Parmentier Jean-Hugues , Malik Kafait U 
Published: January 2005

Abstract
Background
Fibroblasts, as connective tissue cells, are able to transform into another cell type including smooth muscle cells. α1A-adrenergic receptor (α1A-AR) stimulation in rat-1 fibroblasts is coupled to cAMP production. However, the significance of an increase in cAMP produced by α1A-AR stimulation on proliferation, hypertrophy and differentiation in these cells is not known.

Results
Activation of the α1A-AR in rat-1 fibroblasts by phenylephrine (PE) inhibited DNA synthesis by 67% and blocked the re-entry of 81% of the cells into S phase of the cell cycle. This cell cycle blockage was associated with hypertrophy characterized by an increase in protein synthesis (64%) and cell size. Elevation of cAMP levels decreased both DNA and protein synthesis. Inhibition of adenylyl cyclase or protein kinase A reversed the antiproliferative effect of cAMP analogs but not PE; the hypertrophic effect of PE was also not altered. The functional response of rat-1 cells to PE was accompanied by increased expression of cyclin-dependent kinase (Cdk) inhibitors p27kip1 and p21cip1/waf1, which function as negative regulators of the cell cycle. Stimulation of α1A-AR also upregulated the cell cycle regulatory proteins pRb, cyclin D1, Cdk 2, Cdk 4, and proliferating cell nuclear antigen. The antiproliferative effect of PE was blocked by p27kip1 antisense but not sense oligonucleotide. PE also promoted expression of smooth muscle cell differentiation markers (smooth muscle alpha actin, caldesmon, and myosin heavy chain) as well as the muscle development marker MyoD.

Conclusions
Stimulation of α1A-AR promotes cell cycle arrest, hypertrophy and differentiation of rat-1 fibroblasts into smooth muscle-like cells and expression of negative cell cycle regulators by a mechanism independent of the cAMP/PKA signaling pathway.
MAB21L2, a vertebrate member of the Male-abnormal 21 family, modulates BMP signaling and interacts with SMAD1
Authors: Baldessari Danila , Badaloni Aurora , Longhi Renato , Zappavigna Vincenzo , Consalez G Giacomo 
Published: January 2005

Abstract
Background
Through in vivo loss-of-function studies, vertebrate members of the Male abnormal 21 (mab-21) gene family have been implicated in gastrulation, neural tube formation and eye morphogenesis. Despite mounting evidence of their considerable importance in development, the biochemical properties and nature of MAB-21 proteins have remained strikingly elusive. In addition, genetic studies conducted in C. elegans have established that in double mutants mab-21 is epistatic to genes encoding various members of a Transforming Growth Factor beta (TGF-beta) signaling pathway involved in the formation of male-specific sensory organs.

Results
Through a gain-of-function approach, we analyze the interaction of Mab21l2 with a TGF-beta signaling pathway in early vertebrate development. We show that the vertebrate mab-21 homolog Mab21l2 antagonizes the effects of Bone Morphogenetic Protein 4 (BMP4) overexpression in vivo, rescuing the dorsal axis and restoring wild-type distribution of Chordin and Xvent2 transcripts in Xenopus gastrulae. We show that MAB21L2 immunoprecipitates in vivo with the BMP4 effector SMAD1, whilst in vitro it binds SMAD1 and the SMAD1-SMAD4 complex. Finally, when targeted to an heterologous promoter, MAB21L2 acts as a transcriptional repressor.

Conclusions
Our results provide the first biochemical and cellular foundation for future functional studies of mab-21 genes in normal neural development and its pathological disturbances.
Identification of cardiac malformations in mice lacking Ptdsrusing a novel high-throughput magnetic resonance imaging technique
Authors: Schneider Jürgen E , Böse Jens , Bamforth Simon D , Gruber Achim D , Broadbent Carol , Clarke Kieran , Neubauer Stefan , Lengeling Andreas , Bhattacharya Shoumo 
Published: January 2005

Abstract
Background
Congenital heart defects are the leading non-infectious cause of death in children. Genetic studies in the mouse have been crucial to uncover new genes and signaling pathways associated with heart development and congenital heart disease. The identification of murine models of congenital cardiac malformations in high-throughput mutagenesis screens and in gene-targeted models is hindered by the opacity of the mouse embryo.

Results
We developed and optimized a novel method for high-throughput multi-embryo magnetic resonance imaging (MRI). Using this approach we identified cardiac malformations in phosphatidylserine receptor (Ptdsr) deficient embryos. These included ventricular septal defects, double-outlet right ventricle, and hypoplasia of the pulmonary artery and thymus. These results indicate that Ptdsr plays a key role in cardiac development.

Conclusions
Our novel multi-embryo MRI technique enables high-throughput identification of murine models for human congenital cardiopulmonary malformations at high spatial resolution. The technique can be easily adapted for mouse mutagenesis screens and, thus provides an important new tool for identifying new mouse models for human congenital heart diseases.
The genetics of ray pattern variation in Caenorhabditis briggsae
Authors: Baird Scott Everet , Davidson Cynthia R , Bohrer Justin C 
Published: January 2005

Abstract
Background
How does intraspecific variation relate to macroevolutionary change in morphology? This question can be addressed in species in which derived characters are present but not fixed. In rhabditid nematodes, the arrangement of the nine bilateral pairs of peripheral sense organs (rays) in tails of males is often the most highly divergent character between species. The development of ray pattern involves inputs from hometic gene expression patterns, TGFβ signalling, Wnt signalling, and other genetic pathways. In Caenorhabditis briggsae, strain-specific variation in ray pattern has provided an entrée into the evolution of ray pattern. Some strains were fixed for a derived pattern. Other strains were more plastic and exhibited derived and ancestral patterns at equal frequencies.

Results
Recombinant inbred lines (RILs) constructed from crosses between the variant C. briggsae AF16 and HK104 strains exhibited a wide range of phenotypes including some that were more extreme than either parental strain. Transgressive segregation was significantly associated with allelic variation in the C. briggsae homolog of abdominal B, Cb-egl-5. At least two genes that affected different elements of ray pattern, ray position and ray fusion, were linked to a second gene, mip-1. Consistent with this, the segregation of ray position and ray fusion phenotypes were only partially correlated in the RILs.

Conclusions
The evolution of ray pattern has involved allelic variation at multiple loci. Some of these loci impact the specification of ray identities and simultaneously affect multiple ray pattern elements. Others impact individual characters and are not constrained by covariance with other ray pattern elements. Among the genetic pathways that may be involved in ray pattern evolution is specification of anteroposterior positional information by homeotic genes.
Climate change and recent genetic flux in populations of Drosophila robusta
Authors: Levitan Max , Etges William J 
Published: January 2005

Abstract
Background
Studied since the early 1940's, chromosomal polymorphisms in the deciduous woods species Drosophila robusta have been characterized by well-defined latitudinal, longitudinal, and elevational clines, but – until at least ten years ago – stable, local population frequencies. Recent biogeographical analyses indicate that D. robusta invaded North America from southeast Asia and has persisted in eastern temperate forests for at least 20–25 my without speciating. The abundant chromosome polymorphisms found across the range of D. robusta are thus likely to be relatively ancient, having accumulated over many well known climatic cycles in North America. Sufficient long-term data are now available such that we can now gauge the rate of these evolutionary changes in natural populations due to environmental change.

Results
Recent local collections have revealed significant changes in the frequencies of several chromosomal forms. New data presented here extend the range of these changes to six states, three in the northeastern United States and three west of the Mississippi River. These data reinforce recent directional changes in which the frequencies of three gene arrangements have reached percentage levels typical of distant southern populations consistent with regional climatic changes. Another gene arrangement has been steadily decreasing in frequency at a number of the sites studied. Meteorological records from 1945 to 2003 indicate temperature increases at all study sites, particularly average minimum air temperatures.

Conclusions
Observation of parallel genetic flux suggests that these long-term temporal frequency shifts in widely disparate populations of D. robusta are evolutionary responses to environmental change. Since these chromosomes are known to be sensitive to ambient temperature, regional climatic shifts associated with global warming are likely to be responsible.