Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “proteomics database”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,693 records · Page 94Linked to original sources
PubMed2005

Interactome: gateway into systems biology.

Protein-protein interactions are fundamental to all biological processes, and a comprehensive determination of all protein-protein interactions that can take place in an organism provides a framework for understanding biology as an integrated system. The availability of genome-scale sets of cloned open reading frames has facilitated systematic efforts at creating proteome-scale data sets of protein-protein interactions, which are represented as complex networks or 'interactome' maps. Protein-protein interaction mapping projects that follow stringent criteria, coupled with experimental validation in orthogonal systems, provide high-confidence data sets immanently useful for interrogating developmental and disease mechanisms at a system level as well as elucidating individual protein function and interactome network topology. Although far from complete, currently available maps provide insight into how biochemical properties of proteins and protein complexes are integrated into biological systems. Such maps are also a useful resource to predict the function(s) of thousands of genes.

Animals↗
PubMed2004

Two-dimensional gel electrophoresis database of murine R1 embryonic stem cells.

Embryonic stem (ES) cell lines represent a population of undifferentiated pluripotent cells capable of multilineage differentiation in vitro. Although very useful for studying developmental processes, human ES cell lines have also been suggested as a potential and unlimited source for cellular transplantation and the treatment of human disease. The proteomic basis of embryonic stemness (pluripotentiality and multilineage differentiation) and the transitions that lead to specific cell lineages however, remain to be defined. As an important first step in defining these processes, we have performed a proteomic analysis of undifferentiated mouse R1 ES cell lines using pH 3-10, 4-7 and 6-11 two-dimensional electrophoresis gels, matrix-assisted laser desorption/ionization and tandem mass spectrometry. Of the 700 gel spots analyzed, 241 distinct protein species were identified corresponding to 218 unique proteins, with a significant proportion functionally related to protein expression.

Animals↗
PubMed2004

The application of proteomics to the human alcoholic brain.

Alcoholism results in changes in the human brain that reinforce the cycle of craving and dependency, and these changes are manifest in the pattern of expression of proteins in key cells and brain areas. Described here is a proteomics-based approach aimed at determining the identity of proteins in the superior frontal cortex (SFC) of the human brain that show different levels of expression in autopsy samples taken from healthy and long-term alcohol abuse subjects. Soluble protein fractions constituting pooled samples combined from SFC biopsies of four well-characterized chronic alcoholics (mean consumption > 80 g ethanol/day throughout adulthood) and four matched controls (<20 g/day) were generated. Two-dimensional electrophoresis was performed in triplicate on alcoholic and control samples and the resultant protein profiles analyzed for differential expression. Overall, 182 proteins differed by the criterion of twofold or more between case and control samples. Of these, 139 showed significantly lower expression in alcoholics, 35 showed significantly higher expression, and 8 were new or had disappeared. To date, 63 proteins have been identified using MALDI-MS and MS-MS. The finding that the expression level of differentially expressed proteins is preponderantly lower in the alcoholic brain is supported by recent results from parallel studies using microarray mRNA transcript.

Aged↗
PubMed2001

BIND--The Biomolecular Interaction Network Database.

The Biomolecular Interaction Network Database (BIND; http://binddb. org) is a database designed to store full descriptions of interactions, molecular complexes and pathways. Development of the BIND 2.0 data model has led to the incorporation of virtually all components of molecular mechanisms including interactions between any two molecules composed of proteins, nucleic acids and small molecules. Chemical reactions, photochemical activation and conformational changes can also be described. Everything from small molecule biochemistry to signal transduction is abstracted in such a way that graph theory methods may be applied for data mining. The database can be used to study networks of interactions, to map pathways across taxonomic branches and to generate information for kinetic simulations. BIND anticipates the coming large influx of interaction information from high-throughput proteomics efforts including detailed information about post-translational modifications from mass spectrometry. Version 2.0 of the BIND data model is discussed as well as implementation, content and the open nature of the BIND project. The BIND data specification is available as ASN.1 and XML DTD.

Binding, Competitive↗
PubMed2006

Molecular phenotype of zebrafish ovarian follicle by serial analysis of gene expression and proteomic profiling, and comparison with the transcriptomes of other animals.

BACKGROUND: The ability of an oocyte to develop into a viable embryo depends on the accumulation of specific maternal information and molecules, such as RNAs and proteins. A serial analysis of gene expression (SAGE) was carried out in parallel with proteomic analysis on fully-grown ovarian follicles from zebrafish (Danio rerio). The data obtained were compared with ovary/follicle/egg molecular phenotypes of other animals, published or available in public sequence databases. RESULTS: Sequencing of 27,486 SAGE tags identified 11,399 different ones, including 3,329 tags with an occurrence superior to one. Fifty-eight genes were expressed at over 0.15% of the total population and represented 17.34% of the mRNA population identified. The three most expressed transcripts were a rhamnose-binding lectin, beta-actin 2, and a transcribed locus similar to the H2B histone family. Comparison with the large-scale expressed sequence tags sequencing approach revealed highly expressed transcripts that were not previously known to be expressed at high levels in fish ovaries, like the short-sized polarized metallothionein 2 transcript. A higher sensitivity for the detection of transcripts with a characterized maternal genetic contribution was also demonstrated compared to large-scale sequencing of cDNA libraries. Ferritin heavy polypeptide 1, heat shock protein 90-beta, lactate dehydrogenase B4, beta-actin isoforms, tubulin beta 2, ATP synthase subunit 9, together with 40 S ribosomal protein S27a, were common highly-expressed transcripts of vertebrate ovary/unfertilized egg. Comparison of transcriptome and proteome data revealed that transcript levels provide little predictive value with respect to the extent of protein abundance. All the proteins identified by proteomic analysis of fully-grown zebrafish follicles had at least one transcript counterpart, with two exceptions: eosinophil chemotactic cytokine and nothepsin. CONCLUSION: This study provides a complete sequence data set of maternal mRNA stored in zebrafish germ cells at the end of oogenesis. This catalogue contains highly-expressed transcripts that are part of a vertebrate ovarian expressed gene signature. Comparison of transcriptome and proteome data identified downregulated transcripts or proteins potentially incorporated in the oocyte by endocytosis. The molecular phenotype described provides groundwork for future experimental approaches aimed at identifying functionally important stored maternal transcripts and proteins involved in oogenesis and early stages of embryo development.

Animals↗
PubMedDate not supplied

Visual analysis of gel-free proteome data.

We present a visual exploration system supporting protein analysis when using gel-free data acquisition methods. The data to be analyzed is obtained by coupling liquid chromatography (LC) with mass spectrometry (MS). LC-MS data have the properties of being nonequidistantly distributed in the time dimension (measured by LC) and being scattered in the mass-to-charge ratio dimension (measured by MS). We describe a hierarchical data representation and visualization method for large LC-MS data. Based on this visualization, we have developed a tool that supports various data analysis steps. Our visual tool provides a global understanding of the data, intuitive detection and classification of experimental errors, and extensions to LC-MS/MS, LC/LC-MS, and LC/LC-MS/MS data analysis. Due to the presence of randomly occurring rare isotopes within the same protein molecule, several intensity peaks may be detected that all refer to the same peptide. We have developed methods to unite such intensity peaks. This deisotoping step is visually documented by our system, such that misclassification can be detected intuitively. For differential protein expression analysis, we compute and visualize the differences in protein amounts between experiments. In order to compute the differential expression, the experimental data need to be registered. For registration, we perform a nonrigid warping step based on landmarks. The landmarks can be assigned automatically using protein identification methods. We evaluate our methods by comparing protein analysis with and without our interactive visualization-based exploration tool.

Chromatography, Gel↗
PubMed2003

An evolutionarily structured universe of protein architecture.

Protein structural diversity encompasses a finite set of architectural designs. Embedded in these topologies are evolutionary histories that we here uncover using cladistic principles and measurements of protein-fold usage and sharing. The reconstructed phylogenies are inherently rooted and depict histories of protein and proteome diversification. Proteome phylogenies showed two monophyletic sister-groups delimiting Bacteria and Archaea, and a topology rooted in Eucarya. This suggests three dramatic evolutionary events and a common ancestor with a eukaryotic-like, gene-rich, and relatively modern organization. Conversely, a general phylogeny of protein architectures showed that structural classes of globular proteins appeared early in evolution and in defined order, the alpha/beta class being the first. Although most ancestral folds shared a common architecture of barrels or interleaved beta-sheets and alpha-helices, many were clearly derived, such as polyhedral folds in the all-alpha class and beta-sandwiches, beta-propellers, and beta-prisms in all-beta proteins. We also describe transformation pathways of architectures that are prevalently used in nature. For example, beta-barrels with increased curl and stagger were favored evolutionary outcomes in the all-beta class. Interestingly, we found cases where structural change followed the alpha-to-beta tendency uncovered in the tree of architectures. Lastly, we traced the total number of enzymatic functions associated with folds in the trees and show that there is a general link between structure and enzymatic function.

Animals↗
PubMed2005

Different techniques for urinary protein analysis of normal and lung cancer patients.

Many components in urine are useful in clinical diagnosis and urinary proteins are known as important components to define many diseases such as proteinuria, kidney, bladder and urinary tract diseases. In this study, we focused on the comparison of different sample preparation methods for isolating urinary proteins prior to protein analysis of pooled healthy and lung cancer patient samples. Selective method was used for preliminary investigation of some putative urinary protein markers. Urine samples were passed first through a gel filtration column (PD-10 desalting column) to remove high salts and subsequently concentrated. Remaining interferences were removed by ultrafiltration or four precipitation methods. The analysis of urinary proteins by high-performance liquid chromatography and sodium dodecyl sulfate-polyacrylamide gel electrophoresis showed many similarities in profiles among preparation methods and a few profiles were different between normal and lung cancer patients. In contrast, the results of two-dimensional gel electrophoresis (2-DE) showed more distinctly different protein patterns. Our finding showed that the sequential preparation of urinary proteins by gel filtration and ultrafiltration could retain most urinary proteins which demonstrated the highest protein spots on 2-D gels and able to identify preliminary urinary protein markers related to cancer. Although sequential preparation of urine samples by gel filtration and protein precipitation resulted in low amounts of proteins on 2-D gels, high Mr proteins were easily detected. Therefore, there are alternative choices for urine sample preparation for studying the urinary proteome and identifying urinary protein markers important for further preclinical diagnostic and therapeutic applications.

Acetone↗
PubMed2004

Has the yo-yo stopped? An assessment of human protein-coding gene number.

Since the identification of approximately 25,000 proteins from the draft human genome assembly in 2001, estimates of the total have oscillated between 30,000 and 70,000. The recently announced genome closure has not generated a consensus gene count despite this being a key parameter for many areas of biology including drug target discovery and characterization of the human proteome. Contrary to earlier predictions of constitutive under-detection for eukaryotic genes, the latest model organism updates have produced minor increases in the worm but fly and yeast gene numbers have decreased. The postdraft, precompletion interval has produced large increases in human transcript coverage, continuous improvements in genome assembly and refinements in automated genomic annotation. Notably these enhancements have resulted in an Ensembl human protein-coding gene number of 22,184, a decrease of 1862 since the first release. Longitudinal database surveys indicate that redundancy-reduced human mRNA and protein collections are flattening out at approximately 28,000, although Ensembl maps approximately 20,000 known sequences. Observations suggest high-throughput cloning projects are predominantly extending known genes or sampling new splice forms and novel protein discovery has slowed to a trickle. The hypothesis that substantial numbers of short proteins remain experimentally and computationally undetected in mammalian genomes is neither supported by sequence data nor by the extensive homology between mouse and human proteins. Aggregating the independent annotations for complete transcripts from seven completed human chromosomes extrapolates to approximately 25,000 genes. The inclusion of partial putative genes would increase this to above 30,000 but recent data suggest these represent predominantly nonprotein-coding transcripts. Mass spectrometry-based proteomics has already verified more than 10% of human genes but has not identified significant numbers of unpredicted proteins. The available data are thus converging to a basal protein-coding gene number well below 30,000, which could even be as low as 25,000.

Chromosomes, Human↗
PubMed2003

GeneViTo: visualizing gene-product functional and structural features in genomic datasets.

BACKGROUND: The availability of increasing amounts of sequence data from completely sequenced genomes boosts the development of new computational methods for automated genome annotation and comparative genomics. Therefore, there is a need for tools that facilitate the visualization of raw data and results produced by bioinformatics analysis, providing new means for interactive genome exploration. Visual inspection can be used as a basis to assess the quality of various analysis algorithms and to aid in-depth genomic studies. RESULTS: GeneViTo is a JAVA-based computer application that serves as a workbench for genome-wide analysis through visual interaction. The application deals with various experimental information concerning both DNA and protein sequences (derived from public sequence databases or proprietary data sources) and meta-data obtained by various prediction algorithms, classification schemes or user-defined features. Interaction with a Graphical User Interface (GUI) allows easy extraction of genomic and proteomic data referring to the sequence itself, sequence features, or general structural and functional features. Emphasis is laid on the potential comparison between annotation and prediction data in order to offer a supplement to the provided information, especially in cases of "poor" annotation, or an evaluation of available predictions. Moreover, desired information can be output in high quality JPEG image files for further elaboration and scientific use. A compilation of properly formatted GeneViTo input data for demonstration is available to interested readers for two completely sequenced prokaryotes, Chlamydia trachomatis and Methanococcus jannaschii. CONCLUSIONS: GeneViTo offers an inspectional view of genomic functional elements, concerning data stemming both from database annotation and analysis tools for an overall analysis of existing genomes. The application is compatible with Linux or Windows ME-2000-XP operating systems, provided that the appropriate Java Runtime Environment is already installed in the system.

Bacterial Proton-Translocating ATPases↗
PubMed2002

Low-energy collision-induced dissociation fragmentation analysis of cysteinyl-modified peptides.

The development of methods to chemically modify and isolate cysteinyl-residue-containing peptides (Cys-peptides) for LC-MS/MS analysis has generated considerable interest in the field of proteomics. Methods using isotope-coded affinity tags (ICAT) and (+)-biotinyl-iodoacetamidyl-3,6-dioxaoctanediamine (iodoacetyl-PEO-biotin) employ similar Cys-modifying reagents that contain a thiolate-specific biotin group to modify and isolate Cys-containing peptides in conjunction with immobilized avidin. For these strategies to be effective on a proteome-wide level, the presence of the ICAT or acetyl-PEO-biotin tag should not interfere with the efficiency of induced dissociation in MS/MS experiments or with the identification of the modified Cys-peptides by automated database searching algorithms. We have compared the collision-induced dissociation (CID) fragmentation patterns of peptides labeled with iodoacetyl-PEO-biotin and the ICAT reagent to those of the unmodified peptides. CID of Cys-peptides modified with either reagent resulted in the formation of ions attributed to the modified Cys-peptides as well as those unique to the labeling reagent. As demonstrated by analyzing acetyl-PEO-biotin labeled peptides from ribonuclease A and the ICAT-labeled proteome of Deinococcus radiodurans, the presence of these label-specific product ions provides a useful identifier to discern whether a peptide has been modified with the Cys-specific reagent, especially when a number of peptides analyzed using these methods do not contain a modified Cys residue, and to differentiate identical Cys-peptides labeled with either ICAT-d0 or ICAT-d8.

Animals↗
PubMed2003

Current status of protein chip development in terms of fabrication and application.

Sequencing of the human genome revealed that more than 30 000 genes encode proteins comprising the human proteome. "Proteomics" can be defined as a field of research studying proteins in terms of their function, expression, structure, modification and their interaction in physiological and in pathological states. The concentration, modification and interaction of proteins in cells, plasma, and in tissues are crucial in determining the phenotype of living organisms. Although fluctuation of protein concentration is essential to maintain homeostasis, protein expression levels are also pathognomonic features. Estimating protein concentration by analyzing the quantity of mRNA in cells through conventional technologies, such as DNA chips, does not provide precise values since the half-life and translation efficacy of mRNA is variable. In addition, polypeptides undergo post-translational modification. For these reasons, novel techniques are needed to analyze multiple proteins simultaneously using protein microarrays. In the near future, protein chips may allow construction of complete relational databases for metabolic and signal transduction pathways. This article reviews the current status of technologies for fabricating protein microarrays and their applications.

Biotin↗
PubMed2000

Accurate prediction of protein functional class from sequence in the Mycobacterium tuberculosis and Escherichia coli genomes using data mining.

The analysis of genomics data needs to become as automated as its generation. Here we present a novel data-mining approach to predicting protein functional class from sequence. This method is based on a combination of inductive logic programming clustering and rule learning. We demonstrate the effectiveness of this approach on the M. tuberculosis and E. coli genomes, and identify biologically interpretable rules which predict protein functional class from information only available from the sequence. These rules predict 65% of the ORFs with no assigned function in M. tuberculosis and 24% of those in E. coli, with an estimated accuracy of 60-80% (depending on the level of functional assignment). The rules are founded on a combination of detection of remote homology, convergent evolution and horizontal gene transfer. We identify rules that predict protein functional class even in the absence of detectable sequence or structural homology. These rules give insight into the evolutionary history of M. tuberculosis and E. coli.

Amino Acid Sequence↗
PubMed2001

GlycoMod--a software tool for determining glycosylation compositions from mass spectrometric data.

GlycoMod (http://www.expasy.ch/tools/glycomod/) is a software tool designed to find all possible compositions of a glycan structure from its experimentally determined mass. The program can be used to predict the composition of any glycoprotein-derived oligosaccharide comprised of either underivatised, methylated or acetylated monosaccharides, or with a derivatised reducing terminus. The composition of a glycan attached to a peptide can be computed if the sequence or mass of the peptide is known. In addition, if the protein is known and is contained in the SWISS-PROT or TrEMBL databases, the program will match the experimentally determined masses against all the predicted protease-produced peptides (including any post-translational modifications annotated in these databases) which have the potential to be glycosylated with either N- or O-linked oligosaccharides. Since many possible glycan compositions can be generated from the same mass, the program can apply compositional constraints to the output if the user supplies either known or suspected monosaccharide constituents. Furthermore, known oligosaccharide structural constraints on monosaccharide composition are also incorporated into the program to limit the output.

Carbohydrate Sequence↗
PubMed2003

Computing motif correlations in proteins.

Protein motifs, which are specific regions and conserved regions, are found by comparing multiple protein sequences. These conserved regions in general play an important role in protein functions and protein folds, for example, for their binding properties or enzymatic activities. The aim here is to find the existence correlations of protein motifs. The knowledge of protein motif/domain sharing should be important in shedding new light on the biologic functions of proteins and offering a basis in analyzing the evolution in the human genome or other genomes. The protein sequences used here are obtained from the PIR-NREF database and the protein motifs are retrieved from the PROSITE database. We apply data mining approach to discover the occurrence correlations of motif in protein sequences. The correlation of motifs mined can be used in evolution analyses and protein structure prediction. We discuss the latter, i.e., protein structure prediction in this study. The correlations mined are stored and maintained in a database system. The database is now available at http://bioinfo.csie.ncu.edu.tw/ProMotif/.

Algorithms↗
PubMedDate not supplied

Mass spectrometry-based metabolomics.

This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.

Databases, Protein↗
PubMed2005

A novel strategy using MASCOT Distiller for analysis of cleavable isotope-coded affinity tag data to quantify protein changes in plasma.

A novel strategy consisting of cleavable Isotope-Coded Affinity Tag (cICAT) combined with MASCOT Distiller was evaluated as a tool for the quantification of proteins in "abnormal" patient plasma, prepared by pooling samples from patients with acute stroke. Quantification of all light and heavy cICAT-labelled peptide ion pairs was obtained using MASCOT Distiller combined with a proprietary software. Peptides displaying differences were selected for identification by MS. These preliminary results show the promise of our approach to identify potential biomarkers.

Algorithms↗
PubMed2005

Assessment of fold recognition predictions in CASP6.

The Sixth Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP6) held in December 2004 focused on the prediction of the structures of 90 protein domains from 64 targets. Thirty-eight of these were classified as "fold recognition," defined as being similar in fold to proteins of known structure at the time of submission of the predictions. Only the "first" predictions and those longer than 20 amino acids for each domain were assessed, resulting in 4527 predictions from 165 groups. The assessment was accomplished by the use of six structure alignment programs and three scoring measures based on these alignments. The use of a variety of measures resulted in scoring insensitive to the peculiarities of any one alignment method. The top-ranked methods in the prediction of structures that were clearly homologous to proteins in the Protein Data Bank primarily used servers and other programs based on achieving a consensus of many remote homology detection and fold recognition methods. The top-ranked methods in prediction of structures less clearly related or unrelated to proteins of known structures used fragment building methods in addition to the fold recognition meta methods.

Algorithms↗