Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Computational proteomics”

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 271 records · Page 15Linked to original sources
PubMed2006

Human Protein Atlas charts a diverse terrain.

A complete set of high-quality antibodies against the human proteome would constitute a remarkable resource for the analysis of protein abundances in tissues, facilitating systematic protein expression profiling in health and disease. In two recent papers, Swedish researchers describe a concerted effort towards producing a 'Human Protein Atlas' by combining high-throughput antibody generation with immunohistochemical profiling of tissue microarrays.

Database Management Systems↗
PubMed2025

Single-cell proteomics using mass spectrometry.

Over the past 2 to 3 years, mass-spectrometry-based single-cell proteomics (SCP) has experienced transformative improvements in microfluidic and robotic sample preparation, innovative MS1- and MS2-based multiplexing strategies, and specialized hardware (e.g., timsTOF Ultra 2, Astral), which have dramatically boosted sensitivity, throughput, and proteome coverage from picogram-level protein inputs. Concurrently, tailored computational workflows that encompass normalization, imputation, and no-code platforms have addressed pervasive missing data challenges and standardized analyses, collectively enabling high-throughput, reproducible profiling of cellular heterogeneity. This minireview summarizes the latest progress in SCP technology and software solutions, highlighting how the closer integration of analytical, computational, and experimental strategies will facilitate a deeper and broader coverage of single-cell proteomes.

Single-Cell Analysis↗
PubMed2003

Analysis of the Candida albicans proteome. II. Protein information technology on the Net (update 2002).

Candida albicans is an important fungal model organism of noteworthy clinical interest in modern medicine. Different initiatives addressing its sequencing and physical mapping have been carried out. The C. albicans genome sequence is currently near to completion at Stanford University, heralding new challenges in proteomic research and functional analyses of its gene products. This review presents an update of the most relevant data resources that are available through the World Wide Web to scientists working in the area of the analysis of the C. albicans proteome. An overview of the current status of the main universal protein sequence databases and specialized data collections for C. albicans is given. Various issues of the single public C. albicans 2D-PAGE database are also described, highlighting the significance of setting up graphical query interface-based databanks to visualize 2D-PAGE images through the Net. Finally, we also emphasize the pressing need to create a "cyber-bioknowledge library" that will integrate all the databases developed at the different levels for the understanding of life processes as well as bioinformatic tools for interpreting this deluge of data generated through the Internet.

Candida albicans↗
PubMed2002

NMR-based metabolomics.

Similar to genomics and proteomics which yield vast amounts of data about the expression of genes and proteins, metabolomics refers to the whole metabolic profile of the cell. The focus of this report concerns the use of nuclear magnetic resonance (NMR) spectroscopy for metabolic analyses and, in particular, its use in toxicology for examining the metabolic profile of biofluids. Examples from the literature will demonstrate how 1H NMR and pattern recognition methods are used to obtain the urinary metabolic profile, and how this profile is affected by exposure to various toxicants. These particular studies which focus on the metabolic profiles of biofluids, specifically urine, are referred to as metabonomics. NMR-based metabonomics provides a means to categorize organ-specific toxicity, monitor the onset and progression of toxicological effects, and identify biomarkers of toxicity. A future challenge, however, is to describe the cellular metabolome for purposes of understanding cellular functions (i.e., metabolomics). Thus the capabilities and advantages of multinuclear NMR to provide metabolic information in cells and tissues will also be discussed. Such information is essential if metabolomics is to provide a complementary dataset which together with genomics and proteomics can be used to construct computer network models to describe cellular functions.

Animals↗
PubMed2026

OmicsQ: a user-friendly platform for interactive quantitative omics data analysis.

MOTIVATION: High-throughput omics technologies generate complex datasets with thousands of features that are quantified across multiple experimental conditions, but often suffer from incomplete measurements, missing values, and individually fluctuating variances. This requires analytical tools for accurate, deep and insightful biological interpretation, capable of dealing with a large variety of data properties and different amounts of completeness. Software capable of handling such data complexity and integrating with external applications for downstream analysis remains rare and mostly relies on programming-based environments, limiting accessibility for researchers without computational expertise. RESULTS: We present OmicsQ, an interactive, web-based platform designed to streamline quantitative omics data analysis. OmicsQ provides an intuitive, browser-based visualization interface that integrates established statistical processing tools. Those include robust batch correction, automated experimental design annotation, and handling of missing data without imputation, which maintains data integrity and avoids artifacts from a priori assumptions. OmicsQ seamlessly interacts with external applications (e.g. PolySTest, VSClust, ComplexBrowser) for statistical testing, clustering, analysis of protein complex behavior, and pathway enrichment, offering a comprehensive and flexible workflow from data import to biological interpretation that is broadly applicable across domains. AVAILABILITY AND IMPLEMENTATION: OmicsQ is implemented in R and Shiny and is available at https://computproteomics.bmb.sdu.dk/app_direct/OmicsQ. Source code and installation instructions: https://github.com/computproteomics/OmicsQ, DOI: 10.5281/zenodo.17778420.

Software↗
PubMed2005

AGML Central: web based gel proteomic infrastructure.

SUMMARY: AGML Central is a web-based open-source public infrastructure for dissemination of two-dimensional Gel Electrophoresis (2-DE) proteomics data in AGML format (Annotated Gel Markup Language). It includes a growing collection of converters from proprietary formats such as those produced by PDQUEST (BioRad), PHORETIX 2-D (Nonlinear Dynamics) and Melanie (GenBio SA). The resulting unifying AGML formatted entry, with or without the raw gel images, is optionally stored in a database for future reference. AGML Central was developed to provide a common platform for data dissemination and development of 2-DE data analysis tools. This resource responds to an increasing use of AGML for 2-DE public source data representation which requires automated tools for conversion from proprietary formats. Conversion and short-term storage is made publicly available, permanent storage requires prior registering. A JAVA applet visualizer was developed to visualize the AGML data with cross-reference links. In order to facilitate automated access a SOAP web service is also included in the AGML Central infrastructure. AVAILABILITY: http://bioinformatics.musc.edu/agmlcentral.

Database Management Systems↗
PubMed2005

Online predicted human interaction database.

MOTIVATION: High-throughput experiments are being performed at an ever-increasing rate to systematically elucidate protein-protein interaction (PPI) networks for model organisms, while the complexities of higher eukaryotes have prevented these experiments for humans. RESULTS: The Online Predicted Human Interaction Database (OPHID) is a web-based database of predicted interactions between human proteins. It combines the literature-derived human PPI from BIND, HPRD and MINT, with predictions made from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Mus musculus. The 23,889 predicted interactions currently listed in OPHID are evaluated using protein domains, gene co-expression and Gene Ontology terms. OPHID can be queried using single or multiple IDs and results can be visualized using our custom graph visualization program. AVAILABILITY: Freely available to academic users at http://ophid.utoronto.ca, both in tab-delimited and PSI-MI formats. Commercial users, please contact I.J. CONTACT: juris@ai.utoronto.ca SUPPLEMENTARY INFORMATION: http://ophid.utoronto.ca/supplInfo.pdf.

Database Management Systems↗
PubMed2006

Cell++--simulating biochemical pathways.

MOTIVATION: With the generation of a wealth of information, detailing cellular components, their functions and interactions, there is a growing need for the development of new computational tools capable of interpreting these data within spatial and dynamic contexts. Here, we introduce Cell++, a novel stochastic simulation environment with the capacity to study a wide variety of biochemical processes within a spatial context. RESULTS: Focusing on three case studies, we highlight the potential impact of spatial organization in the evolution and engineering of signaling and metabolic pathways. In addition to altering signaling and metabolic efficiency, simulations also demonstrated features consistent with the phenomenon of metabolic channeling. AVAILABILITY: Cell++ is licensed under the GNU general public license (GPL) and has been successfully implemented under Linux and IRIX operating systems. Source code together with a simple tutorial is available at http://www.compsysbio.org/CellSim/.

Biochemistry↗
PubMed2004

The Centre for Modeling Human Disease Gene Trap resource.

Gene trap mutagenesis of mouse embryonic stem cells generates random loss-of-function mutations, which can be identified by a sequence tag and can often report the endogenous expression of the mutated gene. The Centre for Modeling Human Disease is performing expression- and sequence-based screens of gene trap insertions to generate new mouse mutations as a resource for the scientific community. The gene trap insertions are screened using multiplexed in vitro differentiation and induction assays, and sequence tags are generated to complement expression profiles. Researchers may search for insertions in genes expressed in target cell lineages, under specific in vitro conditions, or based upon sequence identity via an online searchable database (http://www.cmhd.ca/sub/genetrap.asp). The clones are available as a resource to researchers worldwide to help to functionally annotate the mammalian genome and will serve as a source to test candidate loci identified by phenotype-driven mutagenesis screens.

Animals↗
PubMed2005

DynaProt 2D: an advanced proteomic database for dynamic online access to proteomes and two-dimensional electrophoresis gels.

DynaProt 2D presents an advanced online database for dynamic access to proteomes and two-dimensional (2D) gels. The database was designed to administer complete in silico proteomes and links them with experimental proteomic data in the manner of 2D electrophoresis gels (IPG-Dalt). The 2D gels serve as reference maps in 2D gel analysis as well as tools for navigation of the database to switch between experimental and predicted data. Therefore, all identified spots in the gels are clickable and linked with summarized protein information. The protein information tables contain calculated characteristics, which are often used in proteomics, such as the molecular weight, isoelectric point, codon adaptation index, grand average of hydropathicity, etc. The design of the database permits online extension of gel data and protein attributes without knowledge of any software language. Besides navigation via 2D gels, the clear graphical user interface permits quick and intuitive searching throughout complete proteomes and supports, e.g. the search for proteins with isoelectric points within pH ranges of interest or protein classes (e.g. ribosomal proteins or transporters). The first organism implemented in the database is Lactococcus lactis. The database is available at www.wzw.tum.de/proteomik/lactis.

Bacterial Proteins↗
PubMed2006

NOPdb: Nucleolar Proteome Database.

The Nucleolar Proteome Database (NOPdb) archives data on >700 proteins that were identified by multiple mass spectrometry (MS) analyses from highly purified preparations of human nucleoli, the most prominent nuclear organelle. Each protein entry is annotated with information about its corresponding gene, its domain structures and relevant protein homologues across species, as well as documenting its MS identification history including all the peptides sequenced by tandem MS/MS. Moreover, data showing the quantitative changes in the relative levels of approximately 500 nucleolar proteins are compared at different timepoints upon transcriptional inhibition. Correlating changes in protein abundance at multiple timepoints, highlighted by visualization means in the NOPdb, provides clues regarding the potential interactions and relationships between nucleolar proteins and thereby suggests putative functions for factors within the 30% of the proteome which comprises novel/uncharacterized proteins. The NOPdb (http://www.lamondlab.com/NOPdb) is searchable by either gene names, nucleotide or protein sequences, Gene Ontology terms or motifs, or by limiting the range for isoelectric points and/or molecular weights and links to other databases (e.g. LocusLink, OMIM and PubMed).

Cell Nucleolus↗
PubMed2006

The Online Bioinformatics Resources Collection at the University of Pittsburgh Health Sciences Library System--a one-stop gateway to online bioinformatics databases and software tools.

To bridge the gap between the rising information needs of biological and medical researchers and the rapidly growing number of online bioinformatics resources, we have created the Online Bioinformatics Resources Collection (OBRC) at the Health Sciences Library System (HSLS) at the University of Pittsburgh. The OBRC, containing 1542 major online bioinformatics databases and software tools, was constructed using the HSLS content management system built on the Zope Web application server. To enhance the output of search results, we further implemented the Vivísimo Clustering Engine, which automatically organizes the search results into categories created dynamically based on the textual information of the retrieved records. As the largest online collection of its kind and the only one with advanced search results clustering, OBRC is aimed at becoming a one-stop guided information gateway to the major bioinformatics databases and software tools on the Web. OBRC is available at the University of Pittsburgh's HSLS Web site (http://www.hsls.pitt.edu/guides/genetics/obrc).

Computational Biology↗
PubMed2006

The TIGR Rice Genome Annotation Resource: improvements and new features.

In The Institute for Genomic Research Rice Genome Annotation project (http://rice.tigr.org), we have continued to update the rice genome sequence with new data and improve the quality of the annotation. In our current release of annotation (Release 4.0; January 12, 2006), we have identified 42,653 non-transposable element-related genes encoding 49,472 gene models as a result of the detection of alternative splicing. We have refined our identification methods for transposable element-related genes resulting in 13,237 genes that are related to transposable elements. Through incorporation of multiple transcript and proteomic expression data sets, we have been able to annotate 24 799 genes (31,739 gene models), representing approximately 50% of the total gene models, as expressed in the rice genome. All structural and functional annotation is viewable through our Rice Genome Browser which currently supports 59 tracks. Enhanced data access is available through web interfaces, FTP downloads and a Data Extractor tool developed in order to support discrete dataset downloads.

DNA Transposable Elements↗
PubMed2006

plprot: a comprehensive proteome database for different plastid types.

Different plant plastid types contain a distinct protein complement for specialized functions and metabolic activities. plprot was established as a plastid proteome database to provide information about the proteomes of chloroplasts, etioplasts and undifferentiated plastids. The current version of plprot features 2,043 protein entries and consists of two modules. Module one contains a BLAST search option and provides comparative information on the proteomes of different plastid types. The second module contains four searchable databases, three for each individual plastid type and one comprehensive composite database that provides the results of plastid proteome analyses from different laboratories. plprot is accessible at http://www.plprot.ethz.ch.

Databases, Protein↗
PubMed2001

Proteins induced during adaptation of Acetobacter aceti to high acetate concentrations.

As a typical product of microbial metabolism, the weak acid acetate is well known for its cytotoxic effects. In contrast to most other microbes, the so-called acetic acid bacteria can acquire significant resistance to high acetate concentrations when properly adapted to such hostile conditions. To characterize the molecular events that are associated with this adaptation, we analyzed global protein expression levels during adaptation of Acetobacter aceti by two-dimensional gel electrophoresis. Adaptation was achieved by using serial batch and continuous cultivations with increasing acetate supplementation. Computer-aided analysis revealed a complex proteome response with at least 50 proteins that are specifically induced by adaptation to acetate but not by other stress conditions, such as heat or oxidative or osmotic stress. Of these proteins, 19 were significantly induced in serial batch and continuous cultures and were thus noted as acetate adaptation proteins (Aaps). Here we present first microsequence information on such Aaps from A. aceti. Membrane-associated processes appear to be of major importance for adaptation, because some of the Aap bear N-terminal sequence homology to membrane proteins and 11 of about 40 resolved proteins from membrane protein-enriched fractions are significantly induced.

Acetates↗