Bioinformatics changing the face of information.
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Biotechnology↗
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Bioinformatics for biodiversity: a Web registry.
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Animals↗
[Recent movements in bioinformatics in India].
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Biotechnology↗
Functional and topological characterization of protein interaction networks.
The elucidation of the cell's large-scale organization is a primary challenge for post-genomic biology, and understanding the structure of protein interaction networks offers an important starting point for such studies. We compare four available databases that approximate the protein interaction network of the yeast, Saccharomyces cerevisiae, aiming to uncover the network's generic large-scale properties and the impact of the proteins' function and cellular localization on the network topology. We show how each database supports a scale-free, topology with hierarchical modularity, indicating that these features represent a robust and generic property of the protein interactions network. We also find strong correlations between the network's structure and the functional role and subcellular localization of its protein constituents, concluding that most functional and/or localization classes appear as relatively segregated subnetworks of the full protein interaction network. The uncovered systematic differences between the four protein interaction databases reflect their relative coverage for different functional and localization classes and provide a guide for their utility in various bioinformatics studies.
Algorithms↗
Fractionation of peptides and identification of proteins from Saccharomyces cerevisiae in proteomics with the use of reversed-phase capillary liquid chromatography and pI-based approach.
The aim of the work was to explore the identification of proteins from Saccharomyces cerevisiae using combined capillary reversed-phase liquid chromatography (RPLC) and in-solution isoelectric focusing (sIEF) for fractionation of peptides prior to mass spectrometry analysis. That method was proved to be the alternative separation method for complex mixtures of protein tryptic digests in proteomics. Analysis of the identification of peptides was performed with the use of electrospray ionization-ion trap tandem mass spectrometry (ESI-IT-MS/MS). First, the sIEF fractionation was carried out prior to separation and mass spectrometry identification by nano-LC/ESI-MS/MS instrument. The proposed approach based on sIEF and nano-LC/ESI-MS/MS analysis was proved to be an efficient and accurate alternative fractionation method of complex protein digests and can be considered as the useful tool for identification of proteins. Moreover, analytical information from that approach can be considered as the additional source of database matching constraint and can be valuable tool for analytical and bioinformatics studies of peptides fractionation in proteomics. Based on the MS/MS results obtained with ESI-IT-MS/MS instrument, 851 proteins from S. cerevisiae were identified. However, after careful analysis of the data reduction in number of proteins to 126 was obtained. Those results are discussed and interpreted in the view of the evaluation method used.
Animals↗
Proteome analysis of bacterial pathogens.
Combining two-dimensional electrophoresis with mass spectrometry resulted in a powerful technology ideally suited to recognize and identify proteins of pathogenic microorganisms. This classical proteome analysis is now complemented by capillary chromatography/mass spectrometry combinations, miniaturization by chip technology and protein interaction investigations. Comparative proteomics is used to reveal vaccine candidates and pathogenicity factors. Immunoproteomics identifies specific and nonspecific antigens. For the management of the huge data amounts, bioinformatics is a valuable instrument for the construction of complex protein databases.
Animals↗
Comparative analysis of apoptosis and inflammation genes of mice and humans.
Apoptosis (programmed cell death) plays important roles in many facets of normal mammalian physiology. Host-pathogen interactions have provided evolutionary pressure for apoptosis as a defense mechanism against viruses and microbes, sometimes linking apoptosis mechanisms with inflammatory responses through NFkappaB induction. Proteins involved in apoptosis and NFkappaB induction commonly contain evolutionarily conserved domains that can serve as signatures for identification by bioinformatics methods. Using a combination of public (NCBI) and private (RIKEN) databases, we compared the repertoire of apoptosis and NFkappaB-inducing genes in humans and mice from cDNA/EST/genomic data, focusing on the following domain families: (1) Caspase proteases; (2) Caspase recruitment domains (CARD); (3) Death Domains (DD); (4) Death Effector Domains (DED); (5) BIR domains of Inhibitor of Apoptosis Proteins (IAPs); (6) Bcl-2 homology (BH) domains of Bcl-2 family proteins; (7) Tumor Necrosis Factor (TNF)-family ligands; (8) TNF receptors (TNFR); (9) TIR domains; (10) PAAD (PYRIN; PYD, DAPIN); (11) nucleotide-binding NACHT domains; (12) TRAFs; (13) Hsp70-binding BAG domains; (14) endonuclease-associated CIDE domains; and (15) miscellaneous additional proteins. After excluding redundancy due to alternative splice forms, sequencing errors, and other considerations, we identified cDNAs derived from a total of 227 human genes among these domain families. Orthologous murine genes were found for 219 (96%); in addition, several unique murine genes were found, which appear not to have human orthologs. This mismatch may be due to the still fragmentary information about the mouse genome or genuine differences between mouse and human repertoires of apoptotic genes. With this caveat, we discuss similarities and differences in human and murine genes from these domain families.
Animals↗
Identifying remote protein homologs by network propagation.
Perhaps the most widely used applications of bioinformatics are tools such as psi-blast for searching sequence databases. We describe a recently developed protein database search algorithm called rankprop. rankprop relies upon a precomputed network of pairwise protein similarities. The algorithm performs a diffusion operation from a specified query protein across the protein similarity network. The resulting activation scores, assigned to each database protein, encode information about the global structure of the protein similarity network. This type of algorithm has a rich history in associationist psychology, artificial intelligence and web search. We describe the rankprop algorithm and its relatives, and we provide evidence that the algorithm successfully improves upon the rankings produced by psi-blast.
Algorithms↗
Nucleotide sequence analysis of a transforming gene isolated from nasopharyngeal carcinoma cell line CNE2: an aberrant human immunoglobulin kappa light chain which lacks variable region.
A transforming gene, designated Tx, was isolated from a human nasopharyngeal carcinoma (NPC) cell line CNE2 by transfection and molecular cloning techniques. The Tx gene was analyzed using computer-based bioinformatics and compared with the known sequences in EMBL and GenBank databases. We found that Tx contains human immunoglobulin kappa light chain constant region, five intact joining regions J1-J5, five recombination signal sequences and an N-segment besides classic regulatory sequences such as TATA boxes, CAAT boxes, poly A signals, etc. Interestingly, Tx also contains several binding sites for nuclear transcription factors such as NF-kappaB, NF-IL6, TFIID, etc. In conclusion, there are only several base pairs mutations or deletions compared with normal Ig K JC gDNA fragment. In all, Tx is an aberrant human immunoglobulin kappa light chain that contains the constant region, five joining regions, which lacks the variable regions.
Genes, Immunoglobulin↗
Novel techniques for visualising biological information.
The major challenge facing the bioinformatics community is the continuing increase in the number, size and complexity of biological databases with which it must contend. The goal of the research discussed herein is the development and utilisation of techniques that allow researchers to extract new and useful information from these burgeoning information resources using advanced visualisation methods and paradigms, coupled with distributed object technologies that allow communications between applications and remote databases. Visualisation has roles not only in analysis, but also in building more user-friendly interfaces, implementing methods to navigate large information spaces intuitively and powerful techniques to browse and query data. By using platform-independent object-oriented programming languages, these resources may be developed as reusable pieces of software componentry with their methods and interfaces defined fully, and then distributed through organisations such as the bioWidget Consortium. The widget and object-oriented approach is a powerful paradigm in developing new applications from existing components. Development time is reduced and greater time is spent on analysing these data, rather than in the writing of monolithic applications. More powerful applications can be constructed from components interacting in concert and offers the opportunity of a new generation of bioinformatics tools.
Base Composition↗
The TGF-beta--Smad network: introducing bioinformatic tools.
The TGF-beta superfamily is an important class of intercellular signalling molecule, including TGF-beta and bone morphogenetic proteins. Intracellular signalling cascades triggered by these molecules eventually activate transcription factors of the Smad family, which then regulate expression of their respective target genes. This article will discuss the TGF-beta--Smad signalling networks and how these processes are represented in databases of signal transduction and transcription control mechanisms. These databases can provide a well-structured overview of the subject and a basis for advanced bioinformatics analyses to interpret the function of genomic sequences or to analyse signalling networks.
Animals↗
Bioinformatics and proteomics approaches for aging research.
Aging is a natural phenomenon that affects the entire physiology of an organism. Elucidating the molecular mechanisms underlying this complex process remains a major challenge today. Humans make poor models for research into aging because of their long life span. Thus, most of the current knowledge is through studies conducted in lower organisms. Large differences in life spans make it difficult to extrapolate the results of experiments carried out in model organisms to humans. Recent advances in genomic and proteomic technologies now permit generation of data pertaining to aging on a large-scale. In addition, several web-based community resources and databases are available that provide easy access to the available data. Use of bioinformatics and systems biology type of approaches provide a framework to start dissecting this complex biological phenomenon. Here, we discuss various genomic, transcriptomic and proteomic approaches that have the potential to provide a comprehensive mechanistic insight into the aging process.
Aging↗
The PEDANT genome database.
The PEDANT genome database (http://pedant.gsf.de) provides exhaustive automatic analysis of genomic sequences by a large variety of established bioinformatics tools through a comprehensive Web-based user interface. One hundred and seventy seven completely sequenced and unfinished genomes have been processed so far, including large eukaryotic genomes (mouse, human) published recently. In this contribution, we describe the current status of the PEDANT database and novel analytical features added to the PEDANT server in 2002. Those include: (i) integration with the BioRS data retrieval system which allows fast text queries, (ii) pre-computed sequence clusters in each complete genome, (iii) a comprehensive set of tools for genome comparison, including genome comparison tables and protein function prediction based on genomic context, and (iv) computation and visualization of protein-protein interaction (PPI) networks based on experimental data. The availability of functional and structural predictions for 650 000 genomic proteins in well organized form makes PEDANT a useful resource for both functional and structural genomics.
Animals↗
PEDANT genome database: 10 years online.
The PEDANT genome database provides exhaustive annotation of 468 genomes by a broad set of bioinformatics algorithms. We describe recent developments of the PEDANT Web server. The all-new Graphical User Interface (GUI) implemented in Javatrade mark allows for more efficient navigation of the genome data, extended search capabilities, user customization and export facilities. The DNA and Protein viewers have been made highly dynamic and customizable. We also provide Web Services to access the entire body of PEDANT data programmatically. Finally, we report on the application of association rule mining for automatic detection of potential annotation errors. PEDANT is freely accessible to academic users at http://pedant.gsf.de.
Computer Graphics↗
Information processing for the analysis of metabolic pathways and inborn errors.
Methods of biotechnology allow the analysis of molecular structures and molecular processes. Different molecular database systems are available which allow worldwide data access. Methods and concepts of bioinformatics are important for the analysis of these molecular data, which represent complex regulatory networks. The detection of metabolic diseases is one application of information systems, which represents molecular and medical data and allows the stimulation of metabolic processes. In this paper we present the architecture of our molecular information system.
Database Management Systems↗
IARC Database of p53 gene mutations in human tumors and cell lines: updated compilation, revised formats and new visualisation tools.
Since 1989, about 570 different p53 mutations have been identified in more than 8000 human cancers. A database of these mutations was initiated by M. Hollstein and C. C. Harris in 1990. This database originally consisted of a list of somatic point mutations in the p 53 gene of human tumors and cell lines, compiled from the published literature and made available in a standard electronic form. The database is maintained at the International Agency for Research on Cancer (IARC) and updated versions are released twice a year (January and July). The current version (July 1997) contains records on 6800 published mutations and will surpass the 8000 mark in the January 1998 release. The database now contains information on somatic and germline mutations in a new format to facilitate data retrieval. In addition, new tools are constructed to improve data analysis, such as a Mutation Viewer Java applet developed at the European Bioinformatics Institute (EBI) to visualise the location and impact of mutations on p53 protein structure. The database is available in different electronic formats at IARC (http://www.iarc. fr/p53/homepage.htm ) or from the EBI server (http://www.ebi.ac.uk ). The IARC p53 website also provides reports on database analysis and links with other p53 sites as well as with related databases. In this report, we describe the criteria for inclusion of data, the revised format and the new visualisation tools. We also briefly discuss the relevance of p 53 mutations to clinical and biological questions.
Computer Communication Networks↗
AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis.
BACKGROUND: Sequence data analyses such as gene identification, structure modeling or phylogenetic tree inference involve a variety of bioinformatics software tools. Due to the heterogeneity of bioinformatics tools in usage and data requirements, scientists spend much effort on technical issues including data format, storage and management of input and output, and memorization of numerous parameters and multi-step analysis procedures. RESULTS: In this paper, we present the design and implementation of AnaBench, an interactive, Web-based bioinformatics Analysis workBench allowing streamlined data analysis. Our philosophy was to minimize the technical effort not only for the scientist who uses this environment to analyze data, but also for the administrator who manages and maintains the workbench. With new bioinformatics tools published daily, AnaBench permits easy incorporation of additional tools. This flexibility is achieved by employing a three-tier distributed architecture and recent technologies including CORBA middleware, Java, JDBC, and JSP. A CORBA server permits transparent access to a workbench management database, which stores information about the users, their data, as well as the description of all bioinformatics applications that can be launched from the workbench. CONCLUSION: AnaBench is an efficient and intuitive interactive bioinformatics environment, which offers scientists application-driven, data-driven and protocol-driven analysis approaches. The prototype of AnaBench, managed by a team at the Université de Montréal, is accessible on-line at: http://malawimonas.bcm.umontreal.ca:8091/anabench. Please contact the authors for details about setting up a local-network AnaBench site elsewhere.
Computational Biology↗
Incorporating a new bioinformatics component into genetics at a historically black college: outcomes and lessons.
Many students at minority-serving institutions are underexposed to Internet resources such as the human genome project, PubMed, NCBI databases, and other Web-based technologies because of a lack of financial resources. To change this, we designed and implemented a new bioinformatics component to supplement the undergraduate Genetics course at Clark Atlanta University. The outcomes of the Bioinformatics course were assessed. During the first week of the semester, students were assigned the Felder-Soloman's Index of Learning Styles Inventory. The overwhelming majority of students were visual (82.1%) and sequential (75.0%) learners. Furthermore, pre- and postcourse surveys were administered during the first and the last week of the course to assess learning, confidence level, and mental activity. These indicated students increased the number of hours spent using computers and doing homework. Students reported confidence in using computers to study genetics increased, enabling them to better visualize and understand genetics. Furthermore, students were more mentally engaged in a more social learning environment. Although the students appreciated the value of the bioinformatics component, they reported the additional work load was substantial enough to receive additional course credit.
Adolescent↗