共查询到20条相似文献，搜索用时 15 毫秒
1.
Recently, many software tools have been developed to perform quantification in LC-MS analyses. However, most of them are specific to either a quantification strategy (e.g. label-free or isotopic labelling) or a mass-spectrometry system (e.g. high or low resolution). In this context, we have developed MassChroQ (Mass Chromatogram Quantification), a versatile software that performs LC-MS data alignment and peptide quantification by peak area integration on extracted ion chromatograms. MassChroQ is suitable for quantification with or without labelling and is not limited to high-resolution systems. Peptides of interest (for example all the identified peptides) can be determined automatically, or manually by providing targeted m/z and retention time values. It can handle large experiments that include protein or peptide fractionation (as SDS-PAGE, 2-D LC). It is fully configurable. Every processing step is traceable, the produced data are in open standard formats and its modularity allows easy integration into proteomic pipelines. The output results are ready for use in statistical analyses. Evaluation of MassChroQ on complex label-free data obtained from low and high-resolution mass spectrometers showed low CVs for technical reproducibility (1.4%) and high coefficients of correlation to protein quantity (0.98). MassChroQ is freely available under the GNU General Public Licence v3.0 at http://pappso.inra.fr/bioinfo/masschroq/. 相似文献
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We present MassSieve, a Java‐based platform for visualization and parsimony analysis of single and comparative LC‐MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC‐MS/MS‐based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments. 相似文献
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农业生物信息数据库发展现状及应用 总被引：4，自引：0，他引：4
农业生物信息数据库是农业科学研究者的基础工具,利用数据库中的大量信息,便于进行农业生物的改良与保护。本文介绍了农业生物信息数据库的发展状况及其应用,并讨论了目前农业生物信息数据库存在的问题。 相似文献
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Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open‐source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years. 相似文献
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In this work, the commonly used algorithms for mass spectrometry based protein identification, Mascot, MS-Fit, ProFound and SEQUEST, were studied in respect to the selectivity and sensitivity of their searches. The influence of various search parameters were also investigated. Approximately 6600 searches were performed using different search engines with several search parameters to establish a statistical basis. The applied mass spectrometric data set was chosen from a current proteome study. The huge amount of data could only be handled with computational assistance. We present a software solution for fully automated triggering of several peptide mass fingerprinting (PMF) and peptide fragmentation fingerprinting (PFF) algorithms. The development of this high-throughput method made an intensive evaluation based on data acquired in a typical proteome project possible. Previous evaluations of PMF and PFF algorithms were mainly based on simulations. 相似文献
6.
Levin Y 《Proteomics》2011,11(12):2565-2567
Designing an experiment for quantitative proteomic analysis is not a trivial task. One of the key factors influencing the success of such studies is the number of biological replicates included in the analysis. This, along with the measured variation will determine the statistical power of the analysis. Presented is a simple yet powerful analysis to determine the appropriate sample size required for reliable and reproducible results, based on the total variation (technical and biological). This approach can also be applied retrospectively for the interpretation of results as it takes into account both significance (p value) and quantitative difference (fold change) of the results. 相似文献
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We describe Abacus, a computational tool for extracting spectral counts from MS/MS data sets. The program aggregates data from multiple experiments, adjusts spectral counts to accurately account for peptides shared across multiple proteins, and performs common normalization steps. It can also output the spectral count data at the gene level, thus simplifying the integration and comparison between gene and protein expression data. Abacus is compatible with the widely used Trans-Proteomic Pipeline suite of tools and comes with a graphical user interface making it easy to interact with the program. The main aim of Abacus is to streamline the analysis of spectral count data by providing an automated, easy to use solution for extracting this information from proteomic data sets for subsequent, more sophisticated statistical analysis. 相似文献
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The two central problems in protein identification by searching a protein sequence collection with MS data are the optimal use of experimental information to allow for identification of low abundance proteins and the accurate assignment of the probability that a result is false. For comprehensive MS-based protein identification, it is necessary to choose an appropriate algorithm and optimal search conditions. We report a systematic study of the quality of PMF-based protein identifications under different sequence collection search conditions using the Probability algorithm, which assigns the statistical significance to each result. We employed 2244 PMFs from 2-DE-separated human blood plasma proteins, and performed identification under various search constraints: mass accuracy (0.01-0.3 Da), maximum number of missed cleavage sites (0-2), and size of the sequence collection searched (5.6 x 10(4)-1.8 x 10(5)). By counting the number of significant results (significance levels 0.05, 0.01, and 0.001) for each condition, we demonstrate the search condition impact on the successful outcome of proteome analysis experiments. A mass correction procedure utilizing mass deviations of albumin matching peptides was tested in an attempt to improve the statistical significance of identifications and iterative searching was employed for identification of multiple proteins from each PMF. 相似文献
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The isobaric peptide termini labeling (IPTL) method is a promising strategy in quantitative proteomics for its high accuracy, while the increased complexity of MS2 spectra originated from the paired b, y ions has adverse effect on the identification and the coverage of quantification. Here, a paired ions scoring algorithm (PISA) based on Morpheus, a database searching algorithm specifically designed for high‐resolution MS2 spectra, was proposed to address this issue. PISA was first tested on two 1:1 mixed IPTL datasets, and increases in peptide to spectrum matchings, distinct peptides and protein groups compared to Morpheus itself and MASCOT were shown. Furthermore, the quantification is simultaneously performed and 100% quantification coverage is achieved by PISA since each of the identified peptide to spectrum matchings has several pairs of fragment ions which could be used for quantification. Then the PISA was applied to the relative quantification of human hepatocellular carcinoma cell lines with high and low metastatic potentials prepared by an IPTL strategy. 相似文献
12.
The ACNUC biological sequence database system provides powerful and fast query and extraction capabilities to a variety of nucleotide and protein sequence databases. The collection of ACNUC databases served by the Pôle Bio-Informatique Lyonnais includes the EMBL, GenBank, RefSeq and UniProt nucleotide and protein sequence databases and a series of other sequence databases that support comparative genomics analyses: HOVERGEN and HOGENOM containing families of homologous protein-coding genes from vertebrate and prokaryotic genomes, respectively; Ensembl and Genome Reviews for analyses of prokaryotic and of selected eukaryotic genomes. This report describes the main features of the ACNUC system and the access to ACNUC databases from any internet-connected computer. Such access was made possible by the definition of a remote ACNUC access protocol and the implementation of Application Programming Interfaces between the C, Python and R languages and this communication protocol. Two retrieval programs for ACNUC databases, Query_win, with a graphical user interface and raa_query, with a command line interface, are also described. Altogether, these bioinformatics tools provide users with either ready-to-use means of querying remote sequence databases through a variety of selection criteria, or a simple way to endow application programs with an extensive access to these databases. Remote access to ACNUC databases is open to all and fully documented (http://pbil.univ-lyon1.fr/databases/acnuc/acnuc.html). 相似文献
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Dominique Tessier Pascal Yclon Ingrid Jacquemin Colette Larré Hélène Rogniaux 《Proteomics》2010,10(9):1794-1801
Several academic software are available to help the validation and reporting of proteomics data generated by MS analyses. However, to our knowledge, none of them have been conceived to meet the particular needs generated by the study of organisms whose genomes are not sequenced. In that context, we have developed OVNIp, an open‐source application which facilitates the whole process of proteomics results interpretation. One of its unique attributes is its capacity to compile multiple results (from several search engines and/or several databank searches) with a resolution of conflicting interpretations. Moreover, OVNIp enables automated exploitation of de novo sequences generated from unassigned MS/MS spectra leading to higher sequence coverage and enhancing confidence in the identified proteins. The exploitation of these additional spectra might also identify novel proteins through a MS‐BLAST search, which can be easily ran from the OVNIp interface. Beyond this primary scope, OVNIp can also benefit to users who look for a simple standalone application to both visualize and confirm MS/MS result interpretations through a simple graphical interface and generate reports according to user‐defined forms which may integrate the prerequisites for publication. Sources, documentation and a stable release for Windows are available at http://wwwappli.nantes.inra.fr:8180/OVNIp . 相似文献
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Novel and improved computational tools are required to transform large-scale proteomics data into valuable information of biological relevance. To this end, we developed ProteoConnections, a bioinformatics platform tailored to address the pressing needs of proteomics analyses. The primary focus of this platform is to organize peptide and protein identifications, evaluate the quality of the acquired data set, profile abundance changes, and accelerate data interpretation. Peptide and protein identifications are stored into a relational database to facilitate data mining and to evaluate the quality of data sets using graphical reports. We integrated databases of known PTMs and other bioinformatics tools to facilitate the analysis of phosphoproteomics data sets and to provide insights for subsequent biological validation experiments. Phosphorylation sites are also annotated according to kinase consensus motifs, contextual environment, protein domains, binding motifs, and evolutionary conservation across different species. The practical application of ProteoConnections is further demonstrated for the analysis of the phosphoproteomics data sets from rat intestinal IEC-6 cells where we identified 9615 phosphorylation sites on 2108 phosphoproteins. Combined proteomics and bioinformatics analyses revealed valuable biological insights on the regulation of phosphoprotein functions via the introduction of new binding sites on scaffold proteins or the modulation of protein-protein, protein-DNA, or protein-RNA interactions. Quantitative proteomics data can be integrated into ProteoConnections to determine the changes in protein phosphorylation under different cell stimulation conditions or kinase inhibitors, as demonstrated here for the MEK inhibitor PD184352. 相似文献
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Data processing and analysis of proteomics data are challenging and time consuming. In this paper, we present MS Data Miner (MDM) (http://sourceforge.net/p/msdataminer), a freely available web-based software solution aimed at minimizing the time required for the analysis, validation, data comparison, and presentation of data files generated in MS software, including Mascot (Matrix Science), Mascot Distiller (Matrix Science), and ProteinPilot (AB Sciex). The program was developed to significantly decrease the time required to process large proteomic data sets for publication. This open sourced system includes a spectra validation system and an automatic screenshot generation tool for Mascot-assigned spectra. In addition, a Gene Ontology term analysis function and a tool for generating comparative Excel data reports are included. We illustrate the benefits of MDM during a proteomics study comprised of more than 200 LC-MS/MS analyses recorded on an AB Sciex TripleTOF 5600, identifying more than 3000 unique proteins and 3.5 million peptides. 相似文献
16.
《Molecular & cellular proteomics : MCP》2019,18(3):561-570
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- •Unified identification and quantification error rates for protein quantification.
- •Error propagation using graphical models and Bayesian statistics.
- •Account for uncertainty of missing values instead of overconfident point estimates.
- •Control of differential expression false discovery rate at increased sensitivity.
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Abigail G. Herrmann James L. Searcy Thierry Le Bihan James McCulloch Ruth F. Deighton 《Proteomics》2013,13(22):3251-3255
Quantitative proteomics is entering its “third generation,” where intricate experimental designs aim to increase the spatial and temporal resolution of protein changes. This paper re‐analyses multiple internally consistent proteomic datasets generated from whole cell homogenates and fractionated brain tissue samples providing a unique opportunity to explore the different factors influencing experimental outcomes. The results clearly indicate that improvements in data handling are required to compensate for the increased mean CV associated with complex study design and intricate upstream tissue processing. Furthermore, applying arbitrary inclusion thresholds such as fold change in protein abundance between groups can lead to unnecessary exclusion of important and biologically relevant data. 相似文献
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UniProt(https://www.uniprot.org/)是国际知名蛋白质数据库,主要包括UniProtKB知识库、UniParc归档库和UniRef参考序列集三部分。UniProtKB知识库是UniProt的核心,除蛋白质序列数据外,还包括大量注释信息。UniProtKB知识库分Swiss-Prot和TrEMBL两个子库。Swiss-Prot子库中50多万条序列均由人工审阅和注释,而TrEMBL子库中1.4亿多条序列是由核酸序列数据库EMBL中的蛋白质编码序列翻译所得,并由计算机根据一定规则进行注释。UniParc归档库将存放于不同数据库中的同一个蛋白质归并到一个记录中以避免冗余,并赋予序列唯一性特定标识符。UniRef参考序列集按相似性程度将UniProtKB和UniParc中的序列分为UniRef100、UniRef90和UniRef50三个数据集。UniProt网站为用户提供了高效实用的高级检索系统和大量帮助文档。UniProt数据库每4周发布新版的同时也发布统计报表,用户可通过统计报表了解该数据库的数据量及更新情况、数据类别和物种分布等基本信息,查看常规注释信息、序列特征注释信息和数据库交叉链接等统计数据。UniProt是目前国际上序列数据最完整、注释信息最丰富的非冗余蛋白质序列数据库,自本世纪初创建以来,为生命科学领域提供了宝贵资源。 相似文献
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Bioactive peptide database (BioPD) is a web-based knowledge base that contains more than 1100 protein sequences from human, mouse and rat, which are putative or are known to be bioactive peptides. In addition to peptide sequences and the annotation, the database also contains gene sequences with annotation, protein interaction and disease data related to the peptides. Each entry has as many references as possible to support the information represented. BioPD consists of six parts: PROTEIN, GENE, DISEASE, LINKS, INTERACTION, and REFERENCE. The database is searchable through keyword, gene and protein name, receptor name, etc. The links to PDB, InterPro, Pfam, OMIM, etc. are provided in each entry. Thus BioPD is formed as an information center for the bioactive peptide and serves as a gateway for exploration of bioactive peptides. The database can be accessed at http://biopd.bjmu.edu.cn. 相似文献
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