bluuebunny/crossref_metadata_2025_split huggingface dataset:
AbMiner: A bioinformatic resource on available monoclonal antibodies and corresponding gene identifiers for genomic, proteomic, and immunologic studies
Authors: Major Sylvia M , Nishizuka Satoshi , Morita Daisaku , Rowland Rick , Sunshine Margot , Shankavaram Uma , Washburn Frank , Asin Daniel , Kouros-Mehr Hosein , Kane David , Weinstein John N 
Published: April 2006

AbstractBackgroundMonoclonal antibodies are used extensively throughout the biomedical sciences for detection of antigens, either in vitroorin vivo. We, for example, have used them for quantitation of proteins on "reverse-phase" protein lysate arrays. For those studies, we quality-controlled > 600 available monoclonal antibodies and also needed to develop precise information on the genes that encode their antigens. Translation among the various protein and gene identifier types proved non-trivial because of one-to-many and many-to-one relationships. To organize the antibody, protein, and gene information, we initially developed a relational database in Filemaker for our own use. When it became apparent that the information would be useful to many other researchers faced with the need to choose or characterize antibodies, we developed it further as AbMiner, a fully relational web-based database under MySQL, programmed in Java.DescriptionAbMiner is a user-friendly, web-based relational database of information on > 600 commercially available antibodies that we validated by Western blot for protein microarray studies. It includes many types of information on the antibody, the immunogen, the vendor, the antigen, and the antigen's gene. Multiple gene and protein identifier types provide links to corresponding entries in a variety of other public databases, including resources for phosphorylation-specific antibodies. AbMiner also includes our quality-control data against a pool of 60 diverse cancer cell types (the NCI-60) and also protein expression levels for the NCI-60 cells measured using our high-density "reverse-phase" protein lysate microarrays for a selection of the listed antibodies. Some other available database resources give information on antibody specificity for one or a couple of cell types. In contrast, the data in AbMiner indicate specificity with respect to the antigens in a pool of 60 diverse cell types from nine different tissues of origin.ConclusionAbMiner is a relational database that provides extensive information from our own laboratory and other sources on more than 600 available antibodies and the genes that encode the antibodies' antigens. The data will be made freely available athttp://discover.nci.nih.gov/abminer
Profiling alternatively spliced mRNA isoforms for prostate cancer classification
Authors: Zhang Chaolin , Li Hai-Ri , Fan Jian-Bing , Wang-Rodriguez Jessica , Downs Tracy , Fu Xiang-Dong , Zhang Michael Q 
Published: April 2006

Abstract

Background
Prostate cancer is one of the leading causes of cancer illness and death among men in the United States and world wide. There is an urgent need to discover good biomarkers for early clinical diagnosis and treatment. Previously, we developed an exon-junction microarray-based assay and profiled 1532 mRNA splice isoforms from 364 potential prostate cancer related genes in 38 prostate tissues. Here, we investigate the advantage of using splice isoforms, which couple transcriptional and splicing regulation, for cancer classification.

Results
As many as 464 splice isoforms from more than 200 genes are differentially regulated in tumors at a false discovery rate (FDR) of 0.05. Remarkably, about 30% of genes have isoforms that are called significant but do not exhibit differential expression at the overall mRNA level. A support vector machine (SVM) classifier trained on 128 signature isoforms can correctly predict 92% of the cases, which outperforms the classifier using overall mRNA abundance by about 5%. It is also observed that the classification performance can be improved using multivariate variable selection methods, which take correlation among variables into account.

Conclusion
These results demonstrate that profiling of splice isoforms is able to provide unique and important information which cannot be detected by conventional microarrays.
Integrative investigation of metabolic and transcriptomic data
Authors: Pir Pınar , Kırdar Betül , Hayes Andrew , Önsan Z İlsen , Ülgen Kutlu Ö , Oliver Stephen G 
Published: April 2006

Abstract

Background
New analysis methods are being developed to integrate data from transcriptome, proteome, interactome, metabolome, and other investigative approaches. At the same time, existing methods are being modified to serve the objectives of systems biology and permit the interpretation of the huge datasets currently being generated by high-throughput methods.

Results
Transcriptomic and metabolic data from chemostat fermentors were collected with the aim of investigating the relationship between these two data sets. The variation in transcriptome data in response to three physiological or genetic perturbations (medium composition, growth rate, and specific gene deletions) was investigated using linear modelling, and open reading-frames (ORFs) whose expression changed significantly in response to these perturbations were identified. Assuming that the metabolic profile is a function of the transcriptome profile, expression levels of the different ORFs were used to model the metabolic variables via Partial Least Squares (Projection to Latent Structures – PLS) using PLS toolbox in Matlab.

Conclusion
The experimental design allowed the analyses to discriminate between the effects which the growth medium, dilution rate, and the deletion of specific genes had on the transcriptome and metabolite profiles. Metabolite data were modelled as a function of the transcriptome to determine their congruence. The genes that are involved in central carbon metabolism of yeast cells were found to be the ORFs with the most significant contribution to the model.
Dissecting trait heterogeneity: a comparison of three clustering methods applied to genotypic data
Authors: Thornton-Wells Tricia A , Moore Jason H , Haines Jonathan L 
Published: April 2006

Abstract

Background
Trait heterogeneity, which exists when a trait has been defined with insufficient specificity such that it is actually two or more distinct traits, has been implicated as a confounding factor in traditional statistical genetics of complex human disease. In the absence of detailed phenotypic data collected consistently in combination with genetic data, unsupervised computational methodologies offer the potential for discovering underlying trait heterogeneity. The performance of three such methods – Bayesian Classification, Hypergraph-Based Clustering, and Fuzzy k-Modes Clustering – appropriate for categorical data were compared. Also tested was the ability of these methods to detect trait heterogeneity in the presence of locus heterogeneity and/or gene-gene interaction, which are two other complicating factors in discovering genetic models of complex human disease. To determine the efficacy of applying the Bayesian Classification method to real data, the reliability of its internal clustering metrics at finding good clusterings was evaluated using permutation testing.

Results
Bayesian Classification outperformed the other two methods, with the exception that the Fuzzy k-Modes Clustering performed best on the most complex genetic model. Bayesian Classification achieved excellent recovery for 75% of the datasets simulated under the simplest genetic model, while it achieved moderate recovery for 56% of datasets with a sample size of 500 or more (across all simulated models) and for 86% of datasets with 10 or fewer nonfunctional loci (across all simulated models). Neither Hypergraph Clustering nor Fuzzy k-Modes Clustering achieved good or excellent cluster recovery for a majority of datasets even under a restricted set of conditions. When using the average log of class strength as the internal clustering metric, the false positive rate was controlled very well, at three percent or less for all three significance levels (0.01, 0.05, 0.10), and the false negative rate was acceptably low (18 percent) for the least stringent significance level of 0.10.

Conclusion
Bayesian Classification shows promise as an unsupervised computational method for dissecting trait heterogeneity in genotypic data. Its control of false positive and false negative rates lends confidence to the validity of its results. Further investigation of how different parameter settings may improve the performance of Bayesian Classification, especially under more complex genetic models, is ongoing.
ROC and confusion analysis of structure comparison methods identify the main causes of divergence from manual protein classification
Authors: Sam Vichetra , Tai Chin-Hsien , Garnier Jean , Gibrat Jean-Francois , Lee Byungkook , Munson Peter J 
Published: April 2006

Abstract

Background
Current classification of protein folds are based, ultimately, on visual inspection of similarities. Previous attempts to use computerized structure comparison methods show only partial agreement with curated databases, but have failed to provide detailed statistical and structural analysis of the causes of these divergences.

Results
We construct a map of similarities/dissimilarities among manually defined protein folds, using a score cutoff value determined by means of the Receiver Operating Characteristics curve. It identifies folds which appear to overlap or to be "confused" with each other by two distinct similarity measures. It also identifies folds which appear inhomogeneous in that they contain apparently dissimilar domains, as measured by both similarity measures. At a low (1%) false positive rate, 25 to 38% of domain pairs in the same SCOP folds do not appear similar. Our results suggest either that some of these folds are defined using criteria other than purely structural consideration or that the similarity measures used do not recognize some relevant aspects of structural similarity in certain cases. Specifically, variations of the "common core" of some folds are severe enough to defeat attempts to automatically detect structural similarity and/or to lead to false detection of similarity between domains in distinct folds. Structures in some folds vary greatly in size because they contain varying numbers of a repeating unit, while similarity scores are quite sensitive to size differences. Structures in different folds may contain similar substructures, which produce false positives. Finally, the common core within a structure may be too small relative to the entire structure, to be recognized as the basis of similarity to another.

Conclusion
A detailed analysis of the entire available protein fold space by two automated similarity methods reveals the extent and the nature of the divergence between the automatically determined similarity/dissimilarity and the manual fold type classifications. Some of the observed divergences can probably be addressed with better structure comparison methods and better automatic, intelligent classification procedures. Others may be intrinsic to the problem, suggesting a continuous rather than discrete protein fold space.
Quality control for terms and definitions in ontologies and taxonomies
Authors: Köhler Jacob , Munn Katherine , Rüegg Alexander , Skusa Andre , Smith Barry 
Published: April 2006

Abstract

Background
Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO), the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way.

Results
We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO.

Conclusion
Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation.
Measuring change in activities of daily living in nursing home residents with moderate to severe cognitive impairment
Authors: Carpenter G Iain , Hastie Charlotte L , Morris John N , Fries Brant E , Ankri Joel 
Published: April 2006

Abstract

Background
The objective of this study was to assess the responsiveness of the Minimum Data Set Activities of Daily Living (MDS-ADL) Scale to change over time by examining the change in physical function in adults with moderate to severe dementia with no comorbid illness who had been resident in a nursing home for over 90 days.

Methods
Longitudinal data were collected on nursing home residents with moderate (n = 7001) or severe (n = 4616) dementia in one US state from the US national Minimum Data Set (MDS). Severity of dementia was determined by the MDS Cognitive Performance Scale (CPS). Physical function was assessed by summing the seven items (bed mobility, transfer, locomotion, dressing, eating, toilet use, personal hygiene) on the MDS activities of daily living (ADL) Long Form scale. Mean change over time of MDS-ADL scores were estimated at three and six months for residents with moderate (CPS score of 3) and severe (CPS score of 4 or 5) dementia.

Results
Physical function in residents with moderate cognitive impairment deteriorated over six months by an average of 1.78 points on the MDS-ADL Long Form scale, while those with severe cognitive impairment declined by an average of 1.70 points. Approximately one quarter of residents in both groups showed some improvement in physical function over the six month period. Residents with moderate cognitive impairment experienced the greatest deterioration in early-loss and mid-loss ADL items (personal hygiene, dressing, toilet use) and residents with severe cognitive impairment showed the greatest deterioration in activities related to eating, a late loss ADL.

Conclusion
The MDS-ADL Long Form scale detected clinically meaningful change in physical function in a large cohort of long-stay nursing home residents with moderate to severe dementia, supporting its use as a research tool in future studies.
A bibliometric analysis of research productivity in Parasitology by different world regions during a 9-year period (1995–2003)
Authors: Falagas Matthew E , Papastamataki Paraskevi A , Bliziotis Ioannis A 
Published: April 2006

Abstract

Background
The objective of this study was to estimate the research productivity of different world regions in the field of Parasitology.

Methods
Using the PubMed database we retrieved articles from journals included in the "Parasitology" category of the "Journal Citation Reports" database of the Institute for Scientific Information for the period 1995–2003. Research productivity was evaluated based on a methodology we developed and used in other bibliometric studies by analysing: (1) the total number of publications, (2) the mean impact factor of all papers, and (3) the product of the above two parameters, (4) the research productivity in relation to gross domestic product of each region, and (5) the research productivity in relation to gross national income per capita and population of each region.

Results
Data on the country of origin of the research was available for 18,110 out of 18,377 articles (98.6% of all articles from the included journals). Western Europe exceeds all world regions in research production for the period studied (34.8% of total articles), with USA ranking second (19.9%), and Latin America & the Caribbean ranking third (17.2%). The mean impact factor in articles published in Parasitology journals was highest for the USA (1.88). Oceania ranked first in research productivity when adjustments for both the gross national income per capita (GNIPC) and population were made. Eastern Europe almost tripled the production of articles from only 1.9% of total production in 1995 to 4.3% in 2003. Similarly, Latin America and the Caribbean and Asia doubled their production. However, the absolute and relative production by some developing areas, including Africa, is still very low, despite the fact that parasitic diseases are major public health problems in these areas.

Conclusion
Our data suggest that more help should be provided by the developed nations to developing areas for improvement of the infrastructure of research.
A study of the relationships between KLF2polymorphisms and body weight control in a French population
Authors: Meirhaeghe Aline , Cottel Dominique , Amouyel Philippe 
Published: April 2006

Abstract

Background
Factors governing adipose tissue differentiation play a major role in obesity development in humans. The Krüppel-like zinc finger transcription factor KLF2/Lung KLF (LKLF) is a negative regulator of adipocyte differentiation. In this study, we sequenced the human KLF2 gene and several common polymorphisms were found, among them the Pro104Leu and 3'UTR 1239C>A polymorphisms.

Methods
To evaluate the impact of these polymorphisms on anthropometric variables in humans, we genotyped a general population composed of 1155 French individuals (including 232 obese subjects) for these polymorphisms and looked for potential statistical associations with obesity-related variables.

Results
The frequency of the Leu104 and 1239A alleles were 0.22 and 0.18 respectively. Genotype and allele frequencies of the two polymorphisms were comparable in obese, overweight and normal weight subjects. No association between the rare alleles of the polymorphisms and anthropometric variables (BMI, weight, waist and hip circumferences, waist-to-hip ratio and plasma leptin levels) could be detected. Haplotype analyses did not reveal further significant associations.

Conclusion
These data indicate that the Pro104Leu and 3'UTR 1239C>A polymorphisms in KLF2 are not associated with obesity and obesity-related traits in humans.
Abnormal glucose tolerance and insulin resistance in polycystic ovary syndrome amongst the Taiwanese population- not correlated with insulin receptor substrate-1 Gly972Arg/Ala513Pro polymorphism
Authors: Lin Ta-Chin , Yen Jui-Mei , Gong Kum-Bing , Kuo Tsung-Cheng , Ku Dong-Chi , Liang Shu-Fen , Wu Ming-Jiuan 
Published: April 2006

Abstract

Background
Insulin resistance and glucose dysmetabolism in polycystic ovary syndrome (PCOS) are related with the polymorphisms in the genes encoding the insulin receptor substrate (IRS) proteins, especially Gly972Arg/Ala513Pro polymorphism being reported to be associated with type-2 diabetes and PCOS. We intended to assess the prevalence of abnormal glucose tolerance (AGT) and insulin resistance in Taiwanese PCOS women. We also tried to assess whether the particular identity of Gly972Arg/Ala513Pro polymorphic alleles of the IRS-1 gene mutation can be used as an appropriate diagnostic indicator for PCOS.

Methods
We designed a prospective clinical study. Forty-seven Taiwanese Hoklo and Hakka women, diagnosed with PCOS were enrolled in this study as were forty-five healthy Hoklo and Hakka women as the control group. Insulin resistance was evaluated with fasting insulin, fasting glucose/insulin ratio, and homeostasis model assessment index for insulin resistance (HOMAIR). The genomic DNA of the subjects was amplified by PCR and digested by restriction fragmented length polymorphism (RFLP) with Bst N1 used for codon 972 and Dra III for codon 513.

Results
AGT was found in 46.8% of these PCOS patients and was significantly related to high insulin resistance rather than the low insulin resistance. Those patients with either insulin resistance or AGT comprised the majority of PCOS affected patients (AGT + fasting insulin ≥17: 83%, AGT + glucose/insulin ratio ≥6.5: 85.1%, AGT + HOMAIR ≥ 2: 87.2%, and AGT + HOMAIR ≥ 3.8: 72.3%). None of the tested samples revealed any polymorphism due to the absence of any Dra III recognition site or any Bst N1 recognition site in the amplified PCR fragment digested by restriction fragmented length polymorphism.

Conclusion
There is significantly high prevalence of AGT and insulin resistance in PCOS women, but Gly972Arg and Ala513Pro polymorphic alleles of IRS-1 are rare and are not associated with the elevated risk of PCOS amongst Taiwanese subjects. This is quite different from the similar study in phylogenetically diverged Caucasian subjects.
Modest induction of phase 2 enzyme activity in the F-344 rat prostate
Authors: Jones Sunita B , Brooks James D 
Published: April 2006

Abstract

Background
Prostate cancer is the most commonly diagnosed malignancy in men and is thought to arise as a result of endogenous oxidative stress in the face of compromised carcinogen defenses. We tested whether carcinogen defense (phase 2) enzymes could be induced in the prostate tissues of rats after oral feeding of candidate phase 2 enzyme inducing compounds.

Methods
Male F344 rats were gavage fed sulforaphane, β-naphthoflavone, curcumin, dimethyl fumarate or vehicle control over five days, and on the sixth day, prostate, liver, kidney and bladder tissues were harvested. Cytosolic enzyme activities of nicotinamide quinone oxidoreductase (NQO1), total glutathione transferase (using DCNB) and mu-class glutathione transferase (using CDNB) were determined in the treated and control animals and compared.

Results
In prostatic tissues, sulforaphane produced modest but significant increases in the enzymatic activities of NQO1, total GST and GST-mu compared to control animals. β-naphthoflavone significantly increased NQO1 and GST-mu activities and curcumin increased total GST and GST-mu enzymatic activities. Dimethyl fumarate did not significantly increase prostatic phase 2 enzyme activity. Compared to control animals, sulforaphane also significantly induced NQO1 or total GST enzyme activity in the liver, kidney and, most significantly, in the bladder tissues. All compounds were well tolerated over the course of the gavage feedings.

Conclusion
Orally administered compounds will induce modestly phase 2 enzyme activity in the prostate although the significance of this degree of induction is unknown. The 4 different compounds also altered phase 2 enzyme activity to different degrees in different tissue types. Orally administered sulforaphane potently induces phase 2 enzymes in bladder tissues and should be investigated as a bladder cancer preventive agent.