A European Pathogenic Microorganism Proteome Database: Construction and Maintenance

A relational database structure based on MS-Access and MySQL to store and manage proteomics data was established. This system may be used to publish two-dimensional electrophoretic proteomics data, and also may be accessed by external users who want to compare their own data with those in the databases. The maintenance of the database is managed centrally. The producers of proteomics data do not need to construct a database themselves. Users can introduce mass spectra into the database, which allows the searching of peptide mass fingerprints against their own protein sequence databases. The first release published in January 2002 contains data from Mycobacterium tuberculosis, Helicobacter pylori, Borrelia garinii, Francisella tularensis, Chlamydia pneumoniae, Mycoplasma pneumoniae, Jurkat T-cells and mouse mammary gland projects (http://www.mpiib-berlin. mpg.de/2D-PAGE/)

ExPASy: the proteomics server for in-depth protein knowledge and analysis

The ExPASy (the Expert Protein Analysis System) World Wide Web server (http://www.expasy.org), is provided as a service to the life science community by a multidisciplinary team at the Swiss Institute of Bioinformatics (SIB). It provides access to a variety of databases and analytical tools dedicated to proteins and proteomics. ExPASy databases include SWISS-PROT and TrEMBL, SWISS-2DPAGE, PROSITE, ENZYME and the SWISS-MODEL repository. Analysis tools are available for specific tasks relevant to proteomics, similarity searches, pattern and profile searches, post-translational modification prediction, topology prediction, primary, secondary and tertiary structure analysis and sequence alignment. These databases and tools are tightly interlinked: a special emphasis is placed on integration of database entries with related resources developed at the SIB and elsewhere, and the proteomics tools have been designed to read the annotations in SWISS-PROT in order to enhance their predictions. ExPASy started to operate in 1993, as the first WWW server in the field of life sciences. In addition to the main site in Switzerland, seven mirror sites in different continents currently serve the user communit

Local Pixel Value Collection Algorithm for Spot Segmentation in Two-Dimensional Gel Electrophoresis Research

Two-dimensional gel-electrophoresis (2-DE) images show the expression levels of several hundreds of proteins where each protein is represented as a blob-shaped spot of grey level values. The spot detection, that is, the segmentation process has to be efficient as it is the first step in the gel processing. Such extraction of information is a very complex task. In this paper, we propose a novel spot detector that is basically a morphology-based method with the use of a seeded region growing as a central paradigm and which relies on the spot correlation information. The method is tested on our synthetic as well as on real gels with human samples from SWISS-2DPAGE (two-dimensional polyacrylamide gel electrophoresis) database. A comparison of results is done with a method called pixel value collection (PVC). Since our algorithm efficiently uses local spot information, segments the spot by collecting pixel values and its affinity with PVC, we named it local pixel value collection (LPVC). The results show that LPVC achieves similar segmentation results as PVC, but is much faster than PVC

The Structural Biology Knowledgebase: a portal to protein structures, sequences, functions, and methods

The Protein Structure Initiative’s Structural Biology Knowledgebase (SBKB, URL: http://sbkb.org) is an open web resource designed to turn the products of the structural genomics and structural biology efforts into knowledge that can be used by the biological community to understand living systems and disease. Here we will present examples on how to use the SBKB to enable biological research. For example, a protein sequence or Protein Data Bank (PDB) structure ID search will provide a list of related protein structures in the PDB, associated biological descriptions (annotations), homology models, structural genomics protein target status, experimental protocols, and the ability to order available DNA clones from the PSI:Biology-Materials Repository. A text search will find publication and technology reports resulting from the PSI’s high-throughput research efforts. Web tools that aid in research, including a system that accepts protein structure requests from the community, will also be described. Created in collaboration with the Nature Publishing Group, the Structural Biology Knowledgebase monthly update also provides a research library, editorials about new research advances, news, and an events calendar to present a broader view of structural genomics and structural biology

Proposal for a Standard Representation of Two-Dimensional Gel Electrophoresis Data

The global analysis of proteins is now feasible due to improvements in techniques such as two-dimensional gel electrophoresis (2-DE), mass spectrometry, yeast two-hybrid systems and the development of bioinformatics applications. The experiments form the basis of proteomics, and present significant challenges in data analysis, storage and querying. We argue that a standard format for proteome data is required to enable the storage, exchange and subsequent re-analysis of large datasets. We describe the criteria that must be met for the development of a standard for proteomics. We have developed a model to represent data from 2-DE experiments, including difference gel electrophoresis along with image analysis and statistical analysis across multiple gels. This part of proteomics analysis is not represented in current proposals for proteomics standards. We are working with the Proteomics Standards Initiative to develop a model encompassing biological sample origin, experimental protocols, a number of separation techniques and mass spectrometry. The standard format will facilitate the development of central repositories of data, enabling results to be verified or re-analysed, and the correlation of results produced by different research groups using a variety of laboratory techniques

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

Construction of a nasopharyngeal carcinoma 2D/MS repository with Open Source XML Database – Xindice

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

Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 year

Fifteen years SIB Swiss Institute of Bioinformatics: life science databases, tools and support.

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) was created in 1998 as an institution to foster excellence in bioinformatics. It is renowned worldwide for its databases and software tools, such as UniProtKB/Swiss-Prot, PROSITE, SWISS-MODEL, STRING, etc, that are all accessible on ExPASy.org, SIB's Bioinformatics Resource Portal. This article provides an overview of the scientific and training resources SIB has consistently been offering to the life science community for more than 15 years

An Evolutionary Computation Approach to Optimization of Isoelectric Point Prediction in Proteins

Computational biology has attacked the problem of isoelectric point prediction with little success, achieving a rough accuracy level of only 30%. In 2005, Matthew Conte performed a study focused on the relationship between sequence characteristics and isoelectric point prediction accuracy. Results indicated that charges between adjacent amino acids could have a significant impact on the overall predicted pi for the protein. In this study we introduce an evolutionary computation approach aimed at accounting for these problem dipeptides. For each possible dipeptide involving charged amino acids (7 chargeable groups -\u3e 49 possibilities), the algorithm predicts a pKa value that, when included in the pi prediction algorithm, should result in a more accurate prediction. By accounting for these charged, adjacent amino acids, the pi prediction showed improvements for those proteins with the greatest deviation between experimental and predicted pi value (Apl \u3e 0.7). However, these results were not generalized, as the incorporation of these values had the reverse effect on remaining proteins, most notably those from the most accurate data set (Apl \u3c 0.1). While this research lays a foundation for improving the pi prediction algorithm, additional exploration remains necessary for an overall accuracy increase