bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of absolute quantitation by nonlinear regression in probe-based real-time PCR
Authors: Goll Rasmus , Olsen Trine , Cui Guanglin , Florholmen Jon 
Published: March 2006

Abstract

Background
In real-time PCR data analysis, the cycle threshold (CT) method is currently the gold standard. This method is based on an assumption of equal PCR efficiency in all reactions, and precision may suffer if this condition is not met. Nonlinear regression analysis (NLR) or curve fitting has therefore been suggested as an alternative to the cycle threshold method for absolute quantitation. The advantages of NLR are that the individual sample efficiency is simulated by the model and that absolute quantitation is possible without a standard curve, releasing reaction wells for unknown samples. However, the calculation method has not been evaluated systematically and has not previously been applied to a TaqMan platform. Aim: To develop and evaluate an automated NLR algorithm capable of generating batch production regression analysis.

Results
Total RNA samples extracted from human gastric mucosa were reverse transcribed and analysed for TNFA, IL18 and ACTB by TaqMan real-time PCR. Fluorescence data were analysed by the regular CT method with a standard curve, and by NLR with a positive control for conversion of fluorescence intensity to copy number, and for this purpose an automated algorithm was written in SPSS syntax. Eleven separate regression models were tested, and the output data was subjected to Altman-Bland analysis. The Altman-Bland analysis showed that the best regression model yielded quantitative data with an intra-assay variation of 58% vs. 24% for the CT derived copy numbers, and with a mean inter-method deviation of × 0.8.

Conclusion
NLR can be automated for batch production analysis, but the CT method is more precise for absolute quantitation in the present setting. The observed inter-method deviation is an indication that assessment of the fluorescence conversion factor used in the regression method can be improved. However, the versatility depends on the level of precision required, and in some settings the increased cost effectiveness of NLR may justify the lower precision.
Metabolite coupling in genome-scale metabolic networks
Authors: Becker Scott A , Price Nathan D , Palsson Bernhard Ø 
Published: March 2006

Abstract

Background
Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜ
T, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S.

Results
Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual metabolites.

Conclusion
The coupling of metabolites is an important topological property of metabolic networks. By computing coupling quantitatively for the first time in genome-scale metabolic networks, we provide insight into the basic structure of these networks.
An improved map of conserved regulatory sites for Saccharomyces cerevisiae
Authors: MacIsaac Kenzie D , Wang Ting , Gordon D Benjamin , Gifford David K , Stormo Gary D , Fraenkel Ernest 
Published: March 2006

Abstract

Background
The regulatory map of a genome consists of the binding sites for proteins that determine the transcription of nearby genes. An initial regulatory map for S. cerevisiae was recently published using six motif discovery programs to analyze genome-wide chromatin immunoprecipitation data for 203 transcription factors. The programs were used to identify sequence motifs that were likely to correspond to the DNA-binding specificity of the immunoprecipitated proteins. We report improved versions of two conservation-based motif discovery algorithms, PhyloCon and Converge. Using these programs, we create a refined regulatory map for S. cerevisiae by reanalyzing the same chromatin immunoprecipitation data.

Results
Applying the same conservative criteria that were applied in the original study, we find that PhyloCon and Converge each separately discover more known specificities than the combination of all six programs in the previous study. Combining the results of PhyloCon and Converge, we discover significant sequence motifs for 36 transcription factors that were previously missed. The new set of motifs identifies 636 more regulatory interactions than the previous one. The new network contains 28% more regulatory interactions among transcription factors, evidence of greater cross-talk between regulators.

Conclusion
Combining two complementary computational strategies for conservation-based motif discovery improves the ability to identify the specificity of transcriptional regulators from genome-wide chromatin immunoprecipitation data. The increased sensitivity of these methods significantly expands the map of yeast regulatory sites without the need to alter any of the thresholds for statistical significance. The new map of regulatory sites reveals a more elaborate and complex view of the yeast genetic regulatory network than was observed previously.
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Authors: Wang Haiying , Zheng Huiru , Simpson David , Azuaje Francisco 
Published: March 2006

Abstract

Background
Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfunction of the rod and cone photoreceptor cells. Development and maintenance of photoreceptors requires appropriate regulation of the many genes specifically or highly expressed in these cells. Over the last decades, different experimental approaches have been developed to identify photoreceptor enriched genes. Recent progress in RNA analysis technology has generated large amounts of gene expression data relevant to retinal development. This paper assesses a machine learning methodology for supporting the identification of photoreceptor enriched genes based on expression data.

Results
Based on the analysis of publicly-available gene expression data from the developing mouse retina generated by serial analysis of gene expression (SAGE), this paper presents a predictive methodology comprising several in silico models for detecting key complex features and relationships encoded in the data, which may be useful to distinguish genes in terms of their functional roles. In order to understand temporal patterns of photoreceptor gene expression during retinal development, a two-way cluster analysis was firstly performed. By clustering SAGE libraries, a hierarchical tree reflecting relationships between developmental stages was obtained. By clustering SAGE tags, a more comprehensive expression profile for photoreceptor cells was revealed. To demonstrate the usefulness of machine learning-based models in predicting functional associations from the SAGE data, three supervised classification models were compared. The results indicated that a relatively simple instance-based model (KStar model) performed significantly better than relatively more complex algorithms, e.g. neural networks. To deal with the problem of functional class imbalance occurring in the dataset, two data re-sampling techniques were studied. A random over-sampling method supported the implementation of the most powerful prediction models. The KStar model was also able to achieve higher predictive sensitivities and specificities using random over-sampling techniques.

Conclusion
The approaches assessed in this paper represent an efficient and relatively inexpensive in silico methodology for supporting large-scale analysis of photoreceptor gene expression by SAGE. They may be applied as complementary methodologies to support functional predictions before implementing more comprehensive, experimental prediction and validation methods. They may also be combined with other large-scale, data-driven methods to facilitate the inference of transcriptional regulatory networks in the developing retina. Furthermore, the methodology assessed may be applied to other data domains.
Microbial identification by mass cataloging
Authors: Zhang Zhengdong , Jackson George W , Fox George E , Willson Richard C 
Published: March 2006

Abstract

Background
The public availability of over 180,000 bacterial 16S ribosomal RNA (rRNA) sequences has facilitated microbial identification and classification using hybridization and other molecular approaches. In their usual format, such assays are based on the presence of unique subsequences in the target RNA and require a prior knowledge of what organisms are likely to be in a sample. They are thus limited in generality when analyzing an unknown sample.
Herein, we demonstrate the utility of catalogs of masses to characterize the bacterial 16S rRNA(s) in any sample. Sample nucleic acids are digested with a nuclease of known specificity and the products characterized using mass spectrometry. The resulting catalogs of masses can subsequently be compared to the masses known to occur in previously-sequenced 16S rRNAs allowing organism identification. Alternatively, if the organism is not in the existing database, it will still be possible to determine its genetic affinity relative to the known organisms.

Results
Ribonuclease T1 and ribonuclease A digestion patterns were calculated for 1,921 complete 16S rRNAs. Oligoribonucleotides generated by RNase T1 of length 9 and longer produce sufficient diversity of masses to be informative. In addition, individual fragments or combinations thereof can be used to recognize the presence of specific organisms in a complex sample. In this regard, 140 strains out of 1,921 organisms (7.3%) could be identified by the presence of a unique RNase T1-generated oligoribonucleotide mass. Combinations of just two and three oligoribonucleotide masses allowed 54% and 72% of the specific strains to be identified, respectively. An initial algorithm for recovering likely organisms present in complex samples is also described.

Conclusion
The use of catalogs of compositions (masses) of characteristic oligoribonucleotides for microbial identification appears extremely promising. RNase T1 is more useful than ribonuclease A in generating characteristic masses, though RNase A produces oligomers which are more readily distinguished due to the large mass difference between A and G. Identification of multiple species in mixtures is also feasible. Practical applicability of the method depends on high performance mass spectrometric determination, and/or use of methods that increase the one dalton (Da) mass difference between uracil and cytosine.
Prediction of cis/trans isomerization in proteins using PSI-BLAST profiles and secondary structure information
Authors: Song Jiangning , Burrage Kevin , Yuan Zheng , Huber Thomas 
Published: March 2006

Abstract

Background
The majority of peptide bonds in proteins are found to occur in the trans conformation. However, for proline residues, a considerable fraction of Prolyl peptide bonds adopt the cis form. Proline cis/trans isomerization is known to play a critical role in protein folding, splicing, cell signaling and transmembrane active transport. Accurate prediction of proline cis/trans isomerization in proteins would have many important applications towards the understanding of protein structure and function.

Results
In this paper, we propose a new approach to predict the proline cis/trans isomerization in proteins using support vector machine (SVM). The preliminary results indicated that using Radial Basis Function (RBF) kernels could lead to better prediction performance than that of polynomial and linear kernel functions. We used single sequence information of different local window sizes, amino acid compositions of different local sequences, multiple sequence alignment obtained from PSI-BLAST and the secondary structure information predicted by PSIPRED. We explored these different sequence encoding schemes in order to investigate their effects on the prediction performance. The training and testing of this approach was performed on a newly enlarged dataset of 2424 non-homologous proteins determined by X-Ray diffraction method using 5-fold cross-validation. Selecting the window size 11 provided the best performance for determining the proline cis/trans isomerization based on the single amino acid sequence. It was found that using multiple sequence alignments in the form of PSI-BLAST profiles could significantly improve the prediction performance, the prediction accuracy increased from 62.8% with single sequence to 69.8% and Matthews Correlation Coefficient (MCC) improved from 0.26 with single local sequence to 0.40. Furthermore, if coupled with the predicted secondary structure information by PSIPRED, our method yielded a prediction accuracy of 71.5% and MCC of 0.43, 9% and 0.17 higher than the accuracy achieved based on the singe sequence information, respectively.

Conclusion
A new method has been developed to predict the proline cis/trans isomerization in proteins based on support vector machine, which used the single amino acid sequence with different local window sizes, the amino acid compositions of local sequence flanking centered proline residues, the position-specific scoring matrices (PSSMs) extracted by PSI-BLAST and the predicted secondary structures generated by PSIPRED. The successful application of SVM approach in this study reinforced that SVM is a powerful tool in predicting proline cis/trans isomerization in proteins and biological sequence analysis.
REtools: A laboratory program for restriction enzyme work: enzyme selection and reaction condition assistance
Authors: Martin Patrick , Boulukos Kim E , Pognonec Philippe 
Published: March 2006

Abstract

Background
Restriction enzymes are one of the everyday tools used in molecular biology. The continuously expanding panel of known restriction enzymes (several thousands) renders their optimal use virtually impossible without computerized assistance. Several manufacturers propose on-line sites that assist scientists in their restriction enzyme work, however, none of these sites meet all the actual needs of laboratory workers, and they do not take into account the enzymes actually present in one's own laboratory.

Results
Using FileMaker Pro, we developed a stand-alone application which can run on both PCs and Macintoshes. We called it REtools, for Restriction Enzyme tools. This program, which references all currently known enzymes (>3500), permits the creation and update of a personalized list of restriction enzymes actually available in one's own laboratory. Upon opening the program, scientists will be presented with a user friendly interface that will direct them to different menus, each one corresponding to different situations that restriction enzyme users commonly encounter. We particularly emphasized the ease of use to make REtools a solution that laboratory members would actually want to use.

Conclusion
REtools, a user friendly and easily customized program to organize any laboratory enzyme stock, brings a software solution that will make restriction enzyme use and reaction condition determination straightforward and efficient. The usually unexplored potential of isoschizomers also becomes accessible to all, since REtools proposes all possible enzymes similar to the one(s) chosen by the user. Finally, many of the commonly overlooked subtleties of restriction enzyme work, such as methylation requirement, unusual reaction conditions, or the number of flanking bases required for cleavage, are automatically provided by REtools.
Disruption of nucleocytoplasmic trafficking of cyclin D1 and topoisomerase II by sanguinarine
Authors: Holy Jon , Lamont Genelle , Perkins Edward 
Published: March 2006

AbstractBackgroundThe quaternary isoquinoline alkaloid sanguinarine is receiving increasing attention as a potential chemotherapeutic agent in the treatment of cancer. Previous studies have shown that this DNA-binding phytochemical can arrest a number of different types of transformed cells in G0/G1, and upregulate the CKIs p21 and p27 while downregulating multiple cyclins and CDKs. To more closely examine the responses of some of these cell cycle regulatory molecules to sanguinarine, we used immunocytochemical methods to visualize cyclin D1 and topoisomerase II behavior in MCF-7 breast cancer cells.Results5 – 10 μM sanguinarine effectively inhibits MCF-7 proliferation after a single application of drug. This growth inhibition is accompanied by a striking relocalization of cyclin D1 and topoisomerase II from the nucleus to the cytoplasm, and this effect persists for at least three days after drug addition. DNA synthesis is transiently inhibited by sanguinarine, but cells recover their ability to synthesize DNA within 24 hours. Taking advantage of the fluorescence characteristics of sanguinarine to follow its uptake and distribution suggests that these effects arise from a window of activity of a few hours immediately after drug addition, when sanguinarine is concentrated in the nucleus. These effects occur in morphologically healthy-looking cells, and thus do not simply represent part of an apoptotic response.ConclusionIt appears that sub-apoptotic concentrations of sanguinarine can suppress breast cancer cell proliferation for extended lengths of time, and that this effect results from a relatively brief period of activity when the drug is concentrated in the nucleus. Sanguinarine transiently inhibits DNA synthesis, but a novel mechanism of action appears to involve disrupting the trafficking of a number of molecules involved in cell cycle regulation and progression. The ability of sub-apoptotic concentrations of sanguinarine to inhibit cell growth may be a useful feature for potential chemotherapeutic applications; however, a narrow effective range for these effects may exist.
Aging of mesenchymal stem cell in vitro
Authors: Bonab Mandana Mohyeddin , Alimoghaddam Kamran , Talebian Fatemeh , Ghaffari Syed Hamid , Ghavamzadeh Ardeshir , Nikbin Behrouz 
Published: March 2006

Abstract

Background
A hot new topic in medical treatment is the use of mesenchymal stem cells (MSC) in therapy. The low frequency of this subpopulation of stem cells in bone marrow (BM) necessitates their in vitro expansion prior to clinical use. We evaluated the effect of long term culture on the senescence of these cells.

Results
The mean long term culture was 118 days and the mean passage number was 9. The average number of PD decreased from 7.7 to 1.2 in the 10th passage. The mean telomere length decreased from 9.19 Kbp to 8.7 kbp in the 9th passage. Differentiation potential dropped from the 6th passage on. The culture's morphological abnormalities were typical of the Hayflick model of cellular aging.

Conclusion
We believe that MSC enter senescence almost undetectably from the moment of in vitro culturing. Simultaneously these cells are losing their stem cell characteristics. Therefore, it is much better to consider them for cell and gene therapy early on.
The evolution of the histone methyltransferase gene Su(var)3-9 in metazoans includes a fusion with and a re-fission from a functionally unrelated gene
Authors: Krauss Veiko , Fassl Anne , Fiebig Petra , Patties Ina , Sass Heinz 
Published: March 2006

Abstract

Background
In eukaryotes, histone H3 lysine 9 (H3K9) methylation is a common mechanism involved in gene silencing and the establishment of heterochromatin. The loci of the major heterochromatic H3K9 methyltransferase Su(var)3-9 and the functionally unrelated γ subunit of the translation initiation factor eIF2 are fused in Drosophila melanogaster. Here we examined the phylogenetic distribution of this unusual gene fusion and the molecular evolution of the H3K9 HMTase Su(var)3-9.

Results
We show that the gene fusion had taken place in the ancestral line of winged insects and silverfishs (Dicondylia) about 400 million years ago. We cloned Su(var)3-9 genes from a collembolan and a spider where both genes ancestrally exist as independent transcription units. In contrast, we found a Su(var)3-9-specific exon inside the conserved intron position 81-1 of the eIF2γ gene structure in species of eight different insect orders. Intriguinly, in the pea aphid Acyrthosiphon pisum, we detected only sequence remains of this Su(var)3-9 exon in the eIF2γ intron, along with an eIF2γ-independent Su(var)3-9 gene. This reveals an evolutionary re-fission of both genes in aphids. Su(var)3-9 chromo domains are similar to HP1 chromo domains, which points to a potential binding activity to methylated K9 of histone H3. SET domain comparisons suggest a weaker methyltransferase activity of Su(var)3-9 in comparison to other H3K9 HMTases. Astonishingly, 11 of 19 previously described, deleterious amino acid substitutions found in Drosophila Su(var)3-9 are seemingly compensable through accompanying substitutions during evolution.

Conclusion
Examination of the Su(var)3-9 evolution revealed strong evidence for the establishment of the Su(var)3-9/eIF2γ gene fusion in an ancestor of dicondylic insects and a re-fission of this fusion during the evolution of aphids. Our comparison of 65 selected chromo domains and 93 selected SET domains from Su(var)3-9 and related proteins offers functional predictions concerning both domains in Su(var)3-9 proteins.