bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phenology of Psychotria tenuinervis (Rubiaceae) in Atlantic forest fragments: fragment and habitat scales
Authors: Ramos Flavio Nunes , Santos Flavio A. Maës 
Published: January 2006

The objective of this study was to investigate (1) whether the reproductive phenology of Psychotria tenuinervis Muell. Arg. is influenced by climatic conditions (precipitation and temperature); (2) whether there are differences in the reproductive phenology of P. tenuinervis between fragments (fragment scale); and (3) whether there are differences in the reproductive phenology of P. tenuinervis among anthropogenic edges, natural edges, and in the forest interior within a fragment (habitat scale). The patterns of flowering and fruiting found in 2002 and 2003 were similar between forest fragments, and proximate factors were not very important in determining the reproductive phenology of P. tenuinervis. There was phenological similarity among the three habitats on a habitat scale, probably because of the extensive heterogeneity within each habitat, with the percentage of flowering and fruiting individuals and the intensity and duration of these phenophases varying among the sample plots. This high variability within habitats indicated that factors other than the distance from the edges (i.e., gaps, matrix composition, and edge age) probably had a greater influence on the reproductive phenology of P. tenuinervis. These results also indicate that heterogeneity within fragmented habitats needs to be considered in conservation and management programs for fragmented landscapes.
A high level interface to SCOP and ASTRAL implemented in Python
Authors: Casbon James A , Crooks Gavin E , Saqi Mansoor AS 
Published: January 2006

Abstract

Background
Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources.

Results
We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL.

Conclusion
The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.
Automatic discovery of cross-family sequence features associated with protein function
Authors: Brameier Markus , Haan Josien , Krings Andrea , MacCallum Robert M 
Published: January 2006

Abstract

Background
Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed.

Results
We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location.

Conclusion
We have developed a novel and useful approach for knowledge discovery in annotated sequence data. The technique is able to identify functionally important sequence features and does not require expert knowledge. By viewing protein function from a sequence perspective, the approach is also suitable for discovering unexpected links between biological processes, such as the recently discovered role of ubiquitination in transcription.
OpWise: Operons aid the identification of differentially expressed genes in bacterial microarray experiments
Authors: Price Morgan N , Arkin Adam P , Alm Eric J 
Published: January 2006

AbstractBackgroundDifferentially expressed genes are typically identified by analyzing the variation between replicate measurements. These procedures implicitly assume that there are no systematic errors in the data even though several sources of systematic error are known.ResultsOpWise estimates the amount of systematic error in bacterial microarray data by assuming that genes in the same operon have matching expression patterns. OpWise then performs a Bayesian analysis of a linear model to estimate significance. In simulations, OpWise corrects for systematic error and is robust to deviations from its assumptions. In several bacterial data sets, significant amounts of systematic error are present, and replicate-based approaches overstate the confidence of the changers dramatically, while OpWise does not. Finally, OpWise can identify additional changers by assigning genes higher confidence if they are consistent with other genes in the same operon.ConclusionAlthough microarray data can contain large amounts of systematic error, operons provide an external standard and allow for reasonable estimates of significance. OpWise is available athttp://microbesonline.org/OpWise.
Prediction of protein structural class with Rough Sets
Authors: Cao Youfang , Liu Shi , Zhang Lida , Qin Jie , Wang Jiang , Tang Kexuan 
Published: January 2006

Abstract

Background
A new method for the prediction of protein structural classes is constructed based on Rough Sets algorithm, which is a rule-based data mining method. Amino acid compositions and 8 physicochemical properties data are used as conditional attributes for the construction of decision system. After reducing the decision system, decision rules are generated, which can be used to classify new objects.

Results
In this study, self-consistency and jackknife tests on the datasets constructed by G.P. Zhou (Journal of Protein Chemistry, 1998, 17: 729–738) are used to verify the performance of this method, and are compared with some of prior works. The results showed that the rough sets approach is very promising and may play a complementary role to the existing powerful approaches, such as the component-coupled, neural network, SVM, and LogitBoost approaches.

Conclusion
The results with high success rates indicate that the rough sets approach as proposed in this paper might hold a high potential to become a useful tool in bioinformatics.
Metabolic pathways variability and sequence/networks comparisons
Authors: Tun Kyaw , Dhar Pawan K , Palumbo Maria Concetta , Giuliani Alessandro 
Published: January 2006

Abstract

Background
In this work a simple method for the computation of relative similarities between homologous metabolic network modules is presented. The method is similar to classical sequence alignment and allows for the generation of phenotypic trees amenable to be compared with correspondent sequence based trees. The procedure can be applied to both single metabolic modules and whole metabolic network data without the need of any specific assumption.

Results
We demonstrate both the ability of the proposed method to build reliable biological classification of a set of microrganisms and the strong correlation between the metabolic network wiringand involved enzymes sequence space.

Conclusion
The method represents a valuable tool for the investigation of genotype/phenotype correlationsallowing for a direct comparison of different species as for their metabolic machinery. In addition the detection of enzymes whose sequence space is maximally correlated with the metabolicnetwork space gives an indication of the most crucial (on an evolutionary viewpoint) steps of the metabolic process.
Djinn Lite: a tool for customised gene transcript modelling, annotation-data enrichment and exploration
Authors: Teber Erdahl T , Crawford Edward , Bolton Kent B , Van Dyk Derek , Schofield Peter R , Kapoor Vimal , Church W Bret 
Published: January 2006

Abstract

Background
There is an ever increasing rate of data made available on genetic variation, transcriptomes and proteomes. Similarly, a growing variety of bioinformatic programs are becoming available from many diverse sources, designed to identify a myriad of sequence patterns considered to have potential biological importance within inter-genic regions, genes, transcripts, and proteins. However, biologists require easy to use, uncomplicated tools to integrate this information, visualise and print gene annotations. Integrating this information usually requires considerable informatics skills, and comprehensive knowledge of the data format to make full use of this information. Tools are needed to explore gene model variants by allowing users the ability to create alternative transcript models using novel combinations of exons not necessarily represented in current database deposits of mRNA/cDNA sequences.

Results
Djinn Lite is designed to be an intuitive program for storing and visually exploring of custom annotations relating to a eukaryotic gene sequence and its modelled gene products. In particular, it is helpful in developing hypothesis regarding alternate splicing of transcripts by allowing the construction of model transcripts and inspection of their resulting translations. It facilitates the ability to view a gene and its gene products in one synchronised graphical view, allowing one to drill down into sequence related data. Colour highlighting of selected sequences and added annotations further supports exploration, visualisation of sequence regions and motifs known or predicted to be biologically significant.

Conclusion
Gene annotating remains an ongoing and challengingtask that will continue as gene structures, gene transcription repertoires, disease loci, protein products and their interactions become moreprecisely defined. Djinn Lite offers an accessible interface to help accumulate, enrich, and individualise sequence annotations relating to a gene, its transcripts and translations. The mechanism of transcript definition and creation, and subsequent navigation and exploration of features, are very intuitive and demand only a short learning curve. Ultimately, Djinn Lite can form the basis for providing valuable clues to plan new experiments, providing storage of sequences and annotations for dedication to customised projects. The application is appropriate for Windows 98-ME-2000-XP-2003 operating systems.
OligoSpawn: a software tool for the design of overgo probes from large unigene datasets
Authors: Zheng Jie , Svensson Jan T , Madishetty Kavitha , Close Timothy J , Jiang Tao , Lonardi Stefano 
Published: January 2006

Abstract

Background
Expressed sequence tag (EST) datasets represent perhaps the largest collection of genetic information. ESTs can be exploited in a variety of biological experiments and analysis. Here we are interested in the design of overlapping oligonucleotide (overgo) probes from large unigene (EST-contigs) datasets.

Results
OLIGOSPAWN is a suite of software tools that offers two complementary services, namely (1) the selection of "unique" oligos each of which appears in one unigene but does not occur (exactly or approximately) in any other and (2) the selection of "popular" oligos each of which occurs (exactly or approximately) in as many unigenes as possible. In this paper, we describe the functionalities of OLIGOSPAWN and the computational methods it employs, and we report on experimental results for the overgo probes designed with it.

Conclusion
The algorithms we designed are highly efficient and capable of processing unigene datasets of sizes on the order of several tens of Mb in a few hours on a regular PC. The software has been used to design overgo probes employed to screen a barley BAC library (Hordeum vulgare). OLIGOSPAWN is freely available at http://oligospawn.ucr.edu/.
Examination of actin and microtubule dependent APC localisations in living mammalian cells
Authors: Langford Kelly J , Askham Jon M , Lee Tracy , Adams Matthew , Morrison Ewan E 
Published: January 2006

Abstract

Background
The trafficking of the adenomatous polyposis coli (APC) tumour suppressor protein in mammalian cells is a perennially controversial topic. Immunostaining evidence for an actin-associated APC localisation at intercellular junctions has been previously presented, though live imaging of mammalian junctional APC has not been documented.

Results
Using live imaging of transfected COS-7 cells we observed intercellular junction-associated pools of GFP-APC in addition to previously documented microtubule-associated GFP-APC and a variety of minor localisations. Although both microtubule and junction-associated populations could co-exist within individual cells, they differed in their subcellular location, dynamic behaviour and sensitivity to cytoskeletal poisons. GFP-APC deletion mutant analysis indicated that a protein truncated immediately after the APC armadillo repeat domain retained the ability to localise to adhesive membranes in transfected cells. Supporting this, we also observed junctional APC immunostaining in cultures of human colorectal cancer cell line that express truncated forms of APC.

Conclusion
Our data indicate that APC can be found in two spatially separate populations at the cell periphery and these populations can co-exist in the same cell. The first localisation is highly dynamic and associated with microtubules near free edges and in cell vertices, while the second is comparatively static and is closely associated with actin at sites of cell-cell contact. Our imaging confirms that human GFP-APC possesses many of the localisations and behaviours previously seen by live imaging of Xenopus GFP-APC. However, we report the novel finding that GFP-APC puncta can remain associated with the ends of shrinking microtubules. Deletion analysis indicated that the N-terminal region of the APC protein mediated its junctional localisation, consistent with our observation that truncated APC proteins in colon cancer cell lines are still capable of localising to the cell cortex. This may have implications for the development of colorectal cancer.
Eleven ancestral gene families lost in mammals and vertebrates while otherwise universally conserved in animals
Authors: Danchin Etienne GJ , Gouret Philippe , Pontarotti Pierre 
Published: January 2006

Abstract

Background
Gene losses played a role which may have been as important as gene and genome duplications and rearrangements, in modelling today species' genomes from a common ancestral set of genes. The set and diversity of protein-coding genes in a species has direct output at the functional level. While gene losses have been reported in all the major lineages of the metazoan tree of life, none have proposed a focus on specific losses in the vertebrates and mammals lineages. In contrast, genes lost in protostomes (i.e. arthropods and nematodes) but still present in vertebrates have been reported and extensively detailed. This probable over-anthropocentric way of comparing genomes does not consider as an important phenomena, gene losses in species that are usually described as "higher". However reporting universally conserved genes throughout evolution that have recently been lost in vertebrates and mammals could reveal interesting features about the evolution of our genome, particularly if these losses can be related to losses of capability.

Results
We report 11 gene families conserved throughout eukaryotes from yeasts (such as Saccharomyces cerevisiae) to bilaterian animals (such as Drosophila melanogaster or Caenorhabditis elegans). This evolutionarily wide conservation suggests they were present in the last common ancestors of fungi and metazoan animals. None of these 11 gene families are found in human nor mouse genomes, and their absence generally extends to all vertebrates. A total of 8 out of these 11 gene families have orthologs in plants, suggesting they were present in the Last Eukaryotic Common Ancestor (LECA). We investigated known functional information for these 11 gene families. This allowed us to correlate some of the lost gene families to loss of capabilities.

Conclusion
Mammalian and vertebrate genomes lost evolutionary conserved ancestral genes that are probably otherwise not dispensable in eukaryotes. Hence, the human genome, which is generally viewed as being the result of increased complexity and gene-content, has also evolved through simplification and gene losses. This acknowledgement confirms, as already suggested, that the genome of our far ancestor was probably more complex than ever considered.
Haseman-Elston weighted by marker informativity
Authors: Franke Daniel , Kleensang André , Elston Robert C , Ziegler Andreas 
Published: January 2006

Abstract
In the Haseman-Elston approach the squared phenotypic difference is regressed on the proportion of alleles shared identical by descent (IBD) to map a quantitative trait to a genetic marker. In applications the IBD distribution is estimated and usually cannot be determined uniquely owing to incomplete marker information. At Genetic Analysis Workshop (GAW) 13, Jacobs et al. [BMC Genet 2003, 4(Suppl 1):S82] proposed to improve the power of the Haseman-Elston algorithm by weighting for information available from marker genotypes. The authors did not show, however, the validity of the employed asymptotic distribution. In this paper, we use the simulated data provided for GAW 14 and show that weighting Haseman-Elston by marker information results in increased type I error rates. Specifically, we demonstrate that the number of significant findings throughout the chromosome is significantly increased with weighting schemes. Furthermore, we show that the classical Haseman-Elston method keeps its nominal significance level when applied to the same data. We therefore recommend to use Haseman-Elston with marker informativity weights only in conjunction with empirical p-values. Whether this approach in fact yields an increase in power needs to be investigated further.
Whole-genome association analysis to identify markers associated with recombination rates using single-nucleotide polymorphisms and microsatellites
Authors: Huang Song , Wang Shuang , Liu Nianjun , Chen Liang , Oh Cheongeun , Zhao Hongyu 
Published: January 2006

Abstract
Recombination during meiosis is one of the most important biological processes, and the level of recombination rates for a given individual is under genetic control. In this study, we conducted genome-wide association studies to identify chromosomal regions associated with recombination rates. We analyzed genotype data collected on the pedigrees in the Collaborative Study on the Genetics on Alcoholism data provided by Genetic Analysis Workshop 14. A total of 315 microsatellites and 10,081 single-nucleotide polymorphisms from Affymetrix on 22 autosomal chromosomes were used in our association analysis. Genome-wide gender-specific recombination counts for family founders were inferred first and association analysis was performed using multiple linear regressions. We used the positive false discovery rate (pFDR) to account for multiple comparisons in the two genome-wide scans. Eight regions showed some evidence of association with recombination counts based on the single-nucleotide polymorphism analysis after adjusting for multiple comparisons. However, no region was found to be significant using microsatellites.
Application of the regression of offspring on mid-parent method to detect associations between single-nucleotide polymorphisms and the beta 2 electroencephalogram phenotype in the COGA data
Authors: Roy-Gagnon Marie-Hélène , Mathias Rasika A , Wilson Alexander F 
Published: January 2006

Abstract
The beta 2 electroencephalogram (EEG) phenotype is used as a quantitative measure related to alcoholism, and evidence of linkage and association has previously been reported in the Collaborative Study on the Genetics of Alcoholism data. In this study, associations between the beta 2 EEG phenotype and single nucleotide polymorphisms from whole-genome Illumina and Affymetrix panels were investigated with the regression of offspring on mid-parent method to identify significant genetic effects and to estimate their heritability. Separate regressions on father and mother were performed to identify parent-specific effects. Estimates of the heritability of the beta 2 EEG phenotype were 0.68 ± 0.12 and 0.52 ± 0.07 based on father-offspring and mother-offspring pairs, respectively. Significant associations at the 0.0005 level, some of which were parent-specific, were found on chromosomes 1, 2, 5, 6, 7, 8, 11, 12, 15, 16, 17, 18, and 19 with heritability attributable to each SNP ranging from 0.01 to 8%.
A comparison of discrete versus continuous environment in a variance components-based linkage analysis of the COGA data
Authors: Viel Kevin R , Warren Diane M , Buil Alfonso , Dyer Thomas D , Howard Tom E , Almasy Laura 
Published: January 2006

Abstract

Background
The information content of a continuous variable exceeds that of its categorical counterpart. The parameterization of a model may diminish the benefit of using a continuous variable. We explored the use of continuous versus discrete environment in variance components based analyses examining gene × environment interaction in the electrophysiological phenotypes from the Collaborative Study on the Genetics of Alcoholism.

Results
The parameterization using the continuous environment produced a greater number of significant gene × environment interactions and lower AICs (Akaike's information criterion). In these cases, the genetic variance increased with increasing cigarette pack-years, the continuous environment of interest. This did not, however, result in enhanced LOD scores when linkage analyses incorporated the gene × continuous environment interaction.

Conclusion
Alternative parameterizations may better represent the functional relationship between the continuous environment and the genetic variance.