bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilization of two sample t-test statistics from redundant probe sets to evaluate different probe set algorithms in GeneChip studies
Authors: Hu Zihua , Willsky Gail R 
Published: January 2006

AbstractBackgroundThe choice of probe set algorithms for expression summary in a GeneChip study has a great impact on subsequent gene expression data analysis. Spiked-in cRNAs with known concentration are often used to assess the relative performance of probe set algorithms. Given the fact that the spiked-in cRNAs do not represent endogenously expressed genes in experiments, it becomes increasingly important to have methods to study whether a particular probe set algorithm is more appropriate for a specific dataset, without using such external reference data.ResultsWe propose the use of the probe set redundancy feature for evaluating the performance of probe set algorithms, and have presented three approaches for analyzing data variance and result bias using two samplet-test statistics from redundant probe sets. These approaches are as follows: 1) analyzing redundant probe set variance based ont-statistic rank order, 2) computing correlation oft-statistics between redundant probe sets, and 3) analyzing the co-occurrence of replicate redundant probe sets representing differentially expressed genes. We applied these approaches to expression summary data generated from three datasets utilizing individual probe set algorithms ofMAS5.0,dChip, orRMA. We also utilized combinations of options from the three probe set algorithms. We found that results from the three approaches were similar within each individual expression summary dataset, and were also in good agreement with previously reported findings by others. We also demonstrate the validity of our findings by independent experimental methods.ConclusionAll three proposed approaches allowed us to assess the performance of probe set algorithms using the probe set redundancy feature. The analyses of redundant probe set variance based ont-statistic rank order and correlation oft-statistics between redundant probe sets provide useful tools for data variance analysis, and the co-occurrence of replicate redundant probe sets representing differentially expressed genes allows estimation of result bias. The results also suggest that individual probe set algorithms have dataset-specific performance.
Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML Database – Xindice
Authors: Li Feng , Li Maoyu , Xiao Zhiqiang , Zhang Pengfei , Li Jianling , Chen Zhuchu 
Published: January 2006

Abstract

Background
Many proteomics initiatives require integration of all information with uniformcriteria from collection of samples and data display to publication of experimental results. The integration and exchanging of these data of different formats and structure imposes a great challenge to us. The XML technology presents a promise in handling this task due to its simplicity and flexibility. Nasopharyngeal carcinoma (NPC) is one of the most common cancers in southern China and Southeast Asia, which has marked geographic and racial differences in incidence. Although there are some cancer proteome databases now, there is still no NPC proteome database.

Results
The raw NPC proteome experiment data were captured into one XML document with Human Proteome Markup Language (HUP-ML) editor and imported into native XML database Xindice. The 2D/MS repository of NPC proteome was constructed with Apache, PHP and Xindice to provide access to the database via Internet. On our website, two methods, keyword query and click query, were provided at the same time to access the entries of the NPC proteome database.

Conclusion
Our 2D/MS repository can be used to share the raw NPC proteomics data that are generated from gel-based proteomics experiments. The database, as well as the PHP source codes for constructing users' own proteome repository, can be accessed at http://www.xyproteomics.org/.
preAssemble: a tool for automatic sequencer trace data processing
Authors: Adzhubei Alexei A , Laerdahl Jon K , Vlasova Anna V 
Published: January 2006

Abstract

Background
Trace or chromatogram files (raw data) are produced by automatic nucleic acid sequencing equipment or sequencers. Each file contains information which can be interpreted by specialised software to reveal the sequence (base calling). This is done by the sequencer proprietary software or publicly available programs. Depending on the size of a sequencing project the number of trace files can vary from just a few to thousands of files. Sequencing quality assessment on various criteria is important at the stage preceding clustering and contig assembly. Two major publicly available packages – Phred and Staden are used by preAssemble to perform sequence quality processing.

Results
The preAssemble pre-assembly sequence processing pipeline has been developed for small to large scale automatic processing of DNA sequencer chromatogram (trace) data. The Staden Package Pregap4 module and base-calling program Phred are utilized in the pipeline, which produces detailed and self-explanatory output that can be displayed with a web browser. preAssemble can be used successfully with very little previous experience, however options for parameter tuning are provided for advanced users. preAssemble runs under UNIX and LINUX operating systems. It is available for downloading and will run as stand-alone software. It can also be accessed on the Norwegian Salmon Genome Project web site where preAssemble jobs can be run on the project server.

Conclusion
preAssemble is a tool allowing to perform quality assessment of sequences generated by automatic sequencing equipment. preAssemble is flexible since both interactive jobs on the preAssemble server and the stand alone downloadable version are available.
Virtually no previous experience is necessary to run a default preAssemble job, on the other hand options for parameter tuning are provided. Consequently preAssemble can be used as efficiently for just several trace files as for large scale sequence processing.
Evaluation of methods for oligonucleotide array data via quantitative real-time PCR
Authors: Qin Li-Xuan , Beyer Richard P , Hudson Francesca N , Linford Nancy J , Morris Daryl E , Kerr Kathleen F 
Published: January 2006

AbstractBackgroundThere are currently many different methods for processing and summarizing probe-level data from Affymetrix oligonucleotide arrays. It is of great interest to validate these methods and identify those that are most effective. There is no single best way to do this validation, and a variety of approaches is needed. Moreover, gene expression data are collected to answer a variety of scientific questions, and the same method may not be best for all questions. Only a handful of validation studies have been done so far, most of which rely on spike-in datasets and focus on the question of detecting differential expression. Here we seek methods that excel at estimating relative expression. We evaluate methods by identifying those that give the strongest linear association between expression measurements by array and the "gold-standard" assay.Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) is generally considered the "gold-standard" assay for measuring gene expression by biologists and is often used to confirm findings from microarray data. Here we use qRT-PCR measurements to validate methods for the components of processing oligo array data: background adjustment, normalization, mismatch adjustment, and probeset summary. An advantage of our approach over spike-in studies is that methods are validated on a real dataset that was collected to address a scientific question.ResultsWe initially identify three of six popular methods that consistently produced the best agreement between oligo array and RT-PCR data for medium- and high-intensity genes. The three methods are generally known as MAS5, gcRMA, and the dChip mismatch mode. For medium- and high-intensity genes, we identified use of data from mismatch probes (as in MAS5 and dChip mismatch) and a sequence-based method of background adjustment (as in gcRMA) as the most important factors in methods' performances. However, we found poor reliability for methods using mismatch probes for low-intensity genes, which is in agreement with previous studies.ConclusionWe advocate use of sequence-based background adjustment in lieu of mismatch adjustment to achieve the best results across the intensity spectrum. No method of normalization or probeset summary showed any consistent advantages.
Analysis and visualization of chromosomal abnormalities in SNP data with SNPscan
Authors: Ting Jason C , Ye Ying , Thomas George H , Ruczinski Ingo , Pevsner Jonathan 
Published: January 2006

Abstract

Background
A variety of diseases are caused by chromosomal abnormalities such as aneuploidies (having an abnormal number of chromosomes), microdeletions, microduplications, and uniparental disomy. High density single nucleotide polymorphism (SNP) microarrays provide information on chromosomal copy number changes, as well as genotype (heterozygosity and homozygosity). SNP array studies generate multiple types of data for each SNP site, some with more than 100,000 SNPs represented on each array. The identification of different classes of anomalies within SNP data has been challenging.

Results
We have developed SNPscan, a web-accessible tool to analyze and visualize high density SNP data. It enables researchers (1) to visually and quantitatively assess the quality of user-generated SNP data relative to a benchmark data set derived from a control population, (2) to display SNP intensity and allelic call data in order to detect chromosomal copy number anomalies (duplications and deletions), (3) to display uniparental isodisomy based on loss of heterozygosity (LOH) across genomic regions, (4) to compare paired samples (e.g. tumor and normal), and (5) to generate a file type for viewing SNP data in the University of California, Santa Cruz (UCSC) Human Genome Browser. SNPscan accepts data exported from Affymetrix Copy Number Analysis Tool as its input. We validated SNPscan using data generated from patients with known deletions, duplications, and uniparental disomy. We also inspected previously generated SNP data from 90 apparently normal individuals from the Centre d'Étude du Polymorphisme Humain (CEPH) collection, and identified three cases of uniparental isodisomy, four females having an apparently mosaic X chromosome, two mislabelled SNP data sets, and one microdeletion on chromosome 2 with mosaicism from an apparently normal female. These previously unrecognized abnormalities were all detected using SNPscan. The microdeletion was independently confirmed by fluorescence in situ hybridization, and a region of homozygosity in a UPD case was confirmed by sequencing of genomic DNA.

Conclusion
SNPscan is useful to identify chromosomal abnormalities based on SNP intensity (such as chromosomal copy number changes) and heterozygosity data (including regions of LOH and some cases of UPD). The program and source code are available at the SNPscan website http://pevsnerlab.kennedykrieger.org/snpscan.htm.
WholePathwayScope: a comprehensive pathway-based analysis tool for high-throughput data
Authors: Yi Ming , Horton Jay D , Cohen Jonathan C , Hobbs Helen H , Stephens Robert M 
Published: January 2006

Abstract

Background
Analysis of High Throughput (HTP) Data such as microarray and proteomics data has provided a powerful methodology to study patterns of gene regulation at genome scale. A major unresolved problem in the post-genomic era is to assemble the large amounts of data generated into a meaningful biological context. We have developed a comprehensive software tool, WholePathwayScope (WPS), for deriving biological insights from analysis of HTP data.

Result
WPS extracts gene lists with shared biological themes through color cue templates. WPS statistically evaluates global functional category enrichment of gene lists and pathway-level pattern enrichment of data. WPS incorporates well-known biological pathways from KEGG (Kyoto Encyclopedia of Genes and Genomes) and Biocarta, GO (Gene Ontology) terms as well as user-defined pathways or relevant gene clusters or groups, and explores gene-term relationships within the derived gene-term association networks (GTANs). WPS simultaneously compares multiple datasets within biological contexts either as pathways or as association networks. WPS also integrates Genetic Association Database and Partial MedGene Database for disease-association information. We have used this program to analyze and compare microarray and proteomics datasets derived from a variety of biological systems. Application examples demonstrated the capacity of WPS to significantly facilitate the analysis of HTP data for integrative discovery.

Conclusion
This tool represents a pathway-based platform for discovery integration to maximize analysis power. The tool is freely available at http://www.abcc.ncifcrf.gov/wps/wps_index.php.
Similarity-based gene detection: using COGs to find evolutionarily-conserved ORFs
Authors: Powell Bradford C , Hutchison Clyde A 
Published: January 2006

Abstract

Background
Experimental verification of gene products has not kept pace with the rapid growth of microbial sequence information. However, existing annotations of gene locations contain sufficient information to screen for probable errors. Furthermore, comparisons among genomes become more informative as more genomes are examined. We studied all open reading frames (ORFs) of at least 30 codons from the genomes of 27 sequenced bacterial strains. We grouped the potential peptide sequences encoded from the ORFs by forming Clusters of Orthologous Groups (COGs). We used this grouping in order to find homologous relationships that would not be distinguishable from noise when using simple BLAST searches. Although COG analysis was initially developed to group annotated genes, we applied it to the task of grouping anonymous DNA sequences that may encode proteins.

Results
"Mixed COGs" of ORFs (clusters in which some sequences correspond to annotated genes and some do not) are attractive targets when seeking errors of gene predicion. Examination of mixed COGs reveals some situations in which genes appear to have been missed in current annotations and a smaller number of regions that appear to have been annotated as gene loci erroneously. This technique can also be used to detect potential pseudogenes or sequencing errors. Our method uses an adjustable parameter for degree of conservation among the studied genomes (stringency). We detail results for one level of stringency at which we found 83 potential genes which had not previously been identified, 60 potential pseudogenes, and 7 sequences with existing gene annotations that are probably incorrect.

Conclusion
Systematic study of sequence conservation offers a way to improve existing annotations by identifying potentially homologous regions where the annotation of the presence or absence of a gene is inconsistent among genomes.
A domain-oriented approach to the reduction of combinatorial complexity in signal transduction networks
Authors: Conzelmann Holger , Saez-Rodriguez Julio , Sauter Thomas , Kholodenko Boris N , Gilles Ernst D 
Published: January 2006

Abstract

Background:
Receptors and scaffold proteins possess a number of distinct domains and bind multiple partners. A common problem in modeling signaling systems arises from a combinatorial explosion of different states generated by feasible molecular species. The number of possible species grows exponentially with the number of different docking sites and can easily reach several millions. Models accounting for this combinatorial variety become impractical for many applications.

Results:
Our results show that under realistic assumptions on domain interactions, the dynamics of signaling pathways can be exactly described by reduced, hierarchically structured models. The method presented here provides a rigorous way to model a large class of signaling networks using macro-states (macroscopic quantities such as the levels of occupancy of the binding domains) instead of micro-states (concentrations of individual species). The method is described using generic multidomain proteins and is applied to the molecule LAT.

Conclusion:
The presented method is a systematic and powerful tool to derive reduced model structures describing the dynamics of multiprotein complex formation accurately.
Finding biological process modifications in cancer tissues by mining gene expression correlations
Authors: Gamberoni Giacomo , Storari Sergio , Volinia Stefano 
Published: January 2006

Abstract

Background
Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This technology yields a global view of gene expression that can be used in several ways. Functional insight into expression profiles is routinely obtained by using Gene Ontology terms associated to the cellular genes. In this paper, we deal with functional data mining from expression profiles, proposing a novel approach that studies the correlations between genes and their relations to Gene Ontology (GO). By using this "functional correlations comparison" we explore all possible pairs of genes identifying the affected biological processes by analyzing in a pair-wise manner gene expression patterns and linking correlated pairs with Gene Ontology terms.

Results
We apply here this "functional correlations comparison" approach to identify the existing correlations in hepatocarcinoma (161 microarray experiments) and to reveal functional differences between normal liver and cancer tissues. The number of well-correlated pairs in each GO term highlights several differences in genetic interactions between cancer and normal tissues. We performed a bootstrap analysis in order to compute false detection rates (FDR) and confidence limits.

Conclusion
Experimental results show the main advantage of the applied method: it both picks up general and specific GO terms (in particular it shows a fine resolution in the specific GO terms). The results obtained by this novel method are highly coherent with the ones proposed by other cancer biology studies. But additionally they highlight the most specific and interesting GO terms helping the biologist to focus his/her studies on the most relevant biological processes.
Pim kinases phosphorylate multiple sites on Bad and promote 14-3-3 binding and dissociation from Bcl-XL
Authors: Macdonald Andrew , Campbell David G , Toth Rachel , McLauchlan Hilary , Hastie C James , Arthur J Simon C 
Published: January 2006

Abstract

Background
Pim-1, 2 and 3 are a group of enzymes related to the calcium calmodulin family of protein kinases. Over-expression of Pim-1 and Pim-2 in mice promotes the development of lymphomas, and up-regulation of Pim expression has been observed in several human cancers.

Results
Here we show that the pim kinases are constitutively active when expressed in HEK-293 cells and are able to phosphorylate the Bcl-2 family member Bad on three residues, Ser112, Ser136 and Ser155 in vitro and in cells. In vitro mapping showed that Pim-2 predominantly phosphorylated Ser112, while Pim-1 phosphorylated Ser112, but also Ser136 and Ser155 at a reduced rate compared to Ser112. Pim-3 was found to be the least specific for Ser112, and the most effective at phosphorylating Ser136 and Ser155. Pim-3 was also able to phosphorylate other sites in Bad in vitro, including Ser170, another potential in vivo site. Mutation of Ser136 to alanine prevented the phosphorylation of Ser112 and Ser155 by Pim kinases in HEK-293 cells, suggesting that this site must be phosphorylated first in order to make the other sites accessible. Pim phosphorylation of Bad was also found to promote the 14-3-3 binding of Bad and block its association with Bcl-XL.

Conclusion
All three Pim kinase family members predominantly phosphorylate Bad on Ser112 and in addition are capable of phosphorylating Bad on multiple sites associated with the inhibition of the pro-apoptotic function of Bad in HEK-293 cells. This would be consistent with the proposed function of Pim kinases in promoting cell proliferation and preventing cell death.
Wnt signaling induces epithelial differentiation during cutaneous wound healing
Authors: Fathke Carrie , Wilson Lynne , Shah Kavita , Kim Brian , Hocking Anne , Moon Randall , Isik Frank 
Published: January 2006

Abstract

Background
Cutaneous wound repair in adult mammals does not regenerate the original epithelial architecture and results in altered skin function. We propose that lack of regeneration may be due to the absence of appropriate molecular signals to promote regeneration. In this study, we investigated the regulation of Wnt signaling during cutaneous wound healing and the consequence of activating either the beta-catenin-dependent or beta-catenin-independent Wnt signaling on epidermal architecture during wound repair.

Results
We determined that the expression of Wnt ligands that typically signal via the beta-catenin-independent pathway is up-regulated in the wound while the beta-catenin-dependent Wnt signaling is activated in the hair follicles adjacent to the wound edge. Ectopic activation of beta-catenin-dependent Wnt signaling with lithium chloride in the wound resulted in epithelial cysts and occasional rudimentary hair follicle structures within the epidermis. In contrast, forced expression of Wnt-5a in the deeper wound induced changes in the interfollicular epithelium mimicking regeneration, including formation of epithelia-lined cysts in the wound dermis, rudimentary hair follicles and sebaceous glands, without formation of tumors.

Conclusion
These findings suggest that adult interfollicular epithelium is capable of responding to Wnt morphogenic signals necessary for restoring epithelial tissue patterning in the skin during wound repair.
Proteomics of early zebrafish embryos
Authors: Link Vinzenz , Shevchenko Andrej , Heisenberg Carl-Philipp 
Published: January 2006

AbstractBackgroundZebrafish (D. rerio) has become a powerful and widely used model system for the analysis of vertebrate embryogenesis and organ development. While genetic methods are readily available in zebrafish, protocols for two dimensional (2D) gel electrophoresis and proteomics have yet to be developed.ResultsAs a prerequisite to carry out proteomic experiments with early zebrafish embryos, we developed a method to efficiently remove the yolk from large batches of embryos. This method enabled high resolution 2D gel electrophoresis and improved Western blotting considerably. Here, we provide detailed protocols for proteomics in zebrafish from sample preparation to mass spectrometry (MS), including a comparison of databases for MS identification of zebrafish proteins.ConclusionThe provided protocols for proteomic analysis of early embryos enable research to be taken in novel directions in embryogenesis.