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PubMed2005

Combining experimental and predicted datasets for determination of the subcellular location of proteins in Arabidopsis.

Substantial experimental datasets defining the subcellular location of Arabidopsis (Arabidopsis thaliana) proteins have been reported in the literature in the form of organelle proteomes built from mass spectrometry data (approximately 2,500 proteins). Subcellular location for specific proteins has also been published based on imaging of chimeric fluorescent fusion proteins in intact cells (approximately 900 proteins). Further, the more diverse history of biochemical determination of subcellular location is stored in the entries of the Swiss-Prot database for the products of many Arabidopsis genes (approximately 1,800 proteins). Combined with the range of bioinformatic targeting prediction tools and comparative genomic analysis, these experimental datasets provide a powerful basis for defining the final location of proteins within the wide variety of subcellular structures present inside Arabidopsis cells. We have analyzed these published experimental and prediction data to answer a range of substantial questions facing researchers about the veracity of these approaches to determining protein location and their interrelatedness. We have merged these data to form the subcellular location database for Arabidopsis proteins (SUBA), providing an integrated understanding of protein location, encompassing the plastid, mitochondrion, peroxisome, nucleus, plasma membrane, endoplasmic reticulum, vacuole, Golgi, cytoskeleton structures, and cytosol (www.suba.bcs.uwa.edu.au). This includes data on more than 4,400 nonredundant Arabidopsis protein sequences. We also provide researchers with an online resource that may be used to query protein sets or protein families and determine whether predicted or experimental location data exist; to analyze the nature of contamination between published proteome sets; and/or for building theoretical subcellular proteomes in Arabidopsis using the latest experimental data.

Arabidopsis↗

PubMed2000

Plant genome databases: from references to inference tools.

Plant genome databases play an important role in the archiving and dissemination of data arising from the international genome projects. Recent developments in bioinformatics, such as new software tools, programming languages and standards, have produced better access across the Internet to the data held within them. An increasing emphasis is placed on data analysis and indeed many resources now provide tools allied to the databases, to aid in the analysis and interpretation of the data. However, a considerable wealth of information lies untapped by considering the databases as single entities and will only be exploited by linking them with a wide range of data sources. Data from research programs such as comparative mapping and germplasm studies may be used as tools, to gain additional knowledge but without additional experimentation. To date, the current plant genome databases are not yet linked comprehensively with each other or with these additional resources, although they are clearly moving toward this. Here, the current wealth of public plant genome databases is reviewed, together with an overview of initiatives underway to bind them to form a single plant genome infrastructure.

Computational Biology↗

PubMed2004

From masking repeats to identifying functional repeats in the mouse transcriptome.

The back-to-back release of the mouse genome and the functionally annotated RIKEN mouse full-length cDNA collection was an important milestone in mammalian genomics. Yet much of the data remain to be explored in terms of biological effects and mechanisms. For example, interspersed repeats account for 39 per cent of the mouse genome sequence and 11 per cent of representative transcripts. A considerable number of transposable repeat elements are still active and propagating in mouse compared with human. While existing repeat databases and tools assist the classification of repeats or identification of new repeats, there is little bioinformatic support towards exploring the extent and role of repeats in transcriptional variation, modulation of protein function, or gene regulatory events. Since the mouse is used as a model organism to study human genes and their disease associations, this review focuses on information extraction and collation that captures the functional context of repeats in mouse transcripts to facilitate the biological interpretation and extrapolation of findings to the human.

Animals↗

PubMed2006

Model-driven user interfaces for bioinformatics data resources: regenerating the wheel as an alternative to reinventing it.

BACKGROUND: The proliferation of data repositories in bioinformatics has resulted in the development of numerous interfaces that allow scientists to browse, search and analyse the data that they contain. Interfaces typically support repository access by means of web pages, but other means are also used, such as desktop applications and command line tools. Interfaces often duplicate functionality amongst each other, and this implies that associated development activities are repeated in different laboratories. Interfaces developed by public laboratories are often created with limited developer resources. In such environments, reducing the time spent on creating user interfaces allows for a better deployment of resources for specialised tasks, such as data integration or analysis. Laboratories maintaining data resources are challenged to reconcile requirements for software that is reliable, functional and flexible with limitations on software development resources. RESULTS: This paper proposes a model-driven approach for the partial generation of user interfaces for searching and browsing bioinformatics data repositories. Inspired by the Model Driven Architecture (MDA) of the Object Management Group (OMG), we have developed a system that generates interfaces designed for use with bioinformatics resources. This approach helps laboratory domain experts decrease the amount of time they have to spend dealing with the repetitive aspects of user interface development. As a result, the amount of time they can spend on gathering requirements and helping develop specialised features increases. The resulting system is known as Pierre, and has been validated through its application to use cases in the life sciences, including the PEDRoDB proteomics database and the e-Fungi data warehouse. CONCLUSION: MDAs focus on generating software from models that describe aspects of service capabilities, and can be applied to support rapid development of repository interfaces in bioinformatics. The Pierre MDA is capable of supporting common database access requirements with a variety of auto-generated interfaces and across a variety of repositories. With Pierre, four kinds of interfaces are generated: web, stand-alone application, text-menu, and command line. The kinds of repositories with which Pierre interfaces have been used are relational, XML and object databases.

Computational Biology↗

PubMed1998

Informatics for mouse genetics and genome mapping.

Bioinformatics has become an essential part of biological research. The rapid pace of technology development and the ability to carry out biological experimentation in large scale require computerized systems for data management, analysis, and display. Experimentation with the mouse, a major model organism of the Human Genome Initiative, has intensified the need for bioinformatics tools for mouse mapping and genome analysis. This article describes the Mouse Genome Database in the United States, a primary resource for mouse genomic data, as well as resources at the Mammalian Genetics Unit in the United Kingdom and the Animal Genome Database of Japan. Internet addresses are provided for major genetic and physical mapping resources, major genome data sites, and resources of molecular information.

Animals↗

PubMed2003

Gene expression patterns define pathways correlated with loss of differentiation in lung adenocarcinomas.

An analysis of microarray data from 86 lung adenocarcinomas reveals hundreds of genes significantly correlated with tumor cell differentiation. A bioinformatics approach of linking these genes to public information from the Locuslink and KEGG databases yields evidence for a loss of tumor cell differentiation being associated with biological processes of cell division, protein degradation, pyrimidine and purine metabolism, oxidative phosphorylation, glyoxylate and dicarboxylate metabolism, folate biosynthesis, and glutamate metabolism. The increased expression of genes involved in these processes is consistent with increased proliferation and metabolism characteristics of poorly differentiated tumors. The complete results of this analysis are available at http://dot.ped.med.umich.edu:2000/pub/diff/index.htm.

Adenocarcinoma↗

PubMed2003

Bioinformatics approaches for the classification of G-protein-coupled receptors.

G-protein-coupled receptors are found abundantly in the human genome, and are the targets of numerous prescribed drugs. However, many receptors remain orphaned (i.e. with unknown ligand specificity), and others remain poorly characterised, with little structural information available. Consequently, there is often a gulf between sequence data and structural and functional knowledge of a receptor. Bioinformatics approaches may offer one approach to bridging this gap. In particular, protein family databases, which distil information from multiple sequence alignments into characteristic signatures, could be used to identify the families to which orphan receptors belong, and might facilitate discovery of novel motifs associated with ligand binding and G-protein-coupling.

Animals↗

PubMed2002

Genomes to Life "Center for Molecular and Cellular Systems": a research program for identification and characterization of protein complexes.

Goal 1 of Department of Energy's Genomes to Life (GTL) program seeks to identify and characterize the complete set of protein complexes within a cell. Goal 1 forms the foundation necessary to accomplish the other objectives of the GTL program, which focus on gene regulatory networks and molecular level characterization of interactions in microbial communities. Together this information would allow cells and their components to be understood in sufficient detail to predict, test and understand the responses of a biological system to its environment. The Center for Molecular and Cellular Systems has been established to identify and characterize protein complexes using high through-put analytical technologies.A dynamic research program is being developed that supports the goals of the Center by focusing on the development new capabilities for sample preparation and complex separations, molecular level identification of the protein complexes by mass spectrometry, characterization of the complexes in living cells by imaging techniques, and bioinformatics and computational tools for the collection and interpretation of data and formation of databases and tools to allow the data to be shared by the biological community.

Animals↗

PubMed2001

XML, bioinformatics and data integration.

MOTIVATION: The eXtensible Markup Language (XML) is an emerging standard for structuring documents, notably for the World Wide Web. In this paper, the authors present XML and examine its use as a data language for bioinformatics. In particular, XML is compared to other languages, and some of the potential uses of XML in bioinformatics applications are presented. The authors propose to adopt XML for data interchange between databases and other sources of data. Finally the discussion is illustrated by a test case of a pedigree data model in XML. CONTACT: Emmanuel.Barillot@infobiogen.fr

Computational Biology↗

PubMed2025

Clinically relevant pseudoexons of the GALNS gene and their antisense-based correction.

BACKGROUND: Biallelic pathogenic variants in the GALNS gene lead to Mucopolysaccharidosis Type IVA (MPS IVA), a rare lysosomal storage disorder. GALNS encodes the enzyme N-acetylgalactosamine-6-sulfatase, whose deficiency causes accumulation of glycosaminoglycans and leads to a broad spectrum of clinical manifestations primarily affecting the osteoarticular system. Several studies have shown that, in 10%-15% of patients with the biochemical phenotype of MPS IVA, standard molecular genetic testing fails to identify one or both causative variants in the GALNS gene. METHODS: We performed an in-depth investigation of GALNS' splicing, with a special focus on deep-intronic mutations that lead to activation of pseudoexons (PEs). Using bioinformatic tools, we analyzed all deep-intronic variants in GALNS available in public databases and subjected the most relevant ones to in vitro analyses using minigenes. RESULTS: We characterized eight PE-activating variants, one of which (c.121-210C > T) represents a recurrent pathogenic variant which has long been hidden behind the mask of a polymorphic variant. In addition, we demonstrate that GALNS' splicing can produce a diverse range of mRNA isoforms containing so-called wild-type PEs, which are present at low levels as part of non-productive splicing, and weak canonical exons which are prone to skipping. We show that PE-activating variants cluster within wild-type PEs, highlighting the need for closer scrutiny of these regions during genetic testing. Finally, we applied modified U7 small nuclear RNAs and circular RNAs to efficiently block the identified PEs and pave the way for personalized antisense-based therapy for MPS IVA patients. CONCLUSION: The results of this study expand the understanding of GALNS gene splicing, indicating hotspots for splicing mutations. The presented data not only help to increase the diagnostic yield for MPS IVA but also unveil new therapeutic approaches for a number of MPS IVA patients.

Humans↗

PubMed2026

KLHL17 as a Prognostic Indicator and Therapeutic Target in Cervical Cancer: A Comprehensive Analysis.

INTRODUCTION: This study aims to clarify the role of kelch like family member 17 (KLHL17) in cervical cancer (CESC) is unclear. OBJECTIVE: To clarify this uncertainty, our research employed bioinformatics analysis coupled with experimental corroboration. METHODS: We utilized the Cancer Genome Atlas (TCGA) database to assess the expression of KLHL17 in various cancers, specifically CESC, and to explore its association with clinical characteristics, diagnostic utility, and prognostic significance in CESC. The current investigation delved into the potential regulatory pathways related to KLHL17, examining its connection with the infiltration of immune cells, the expression of immune checkpoint genes, the status of microsatellite instability (MSI), and the efficacy of diverse therapeutic agents in CESC. The research analyzed KLHL17 expression patterns using single-cell sequencing data from CESC samples and investigated the genetic variations of KLHL17 within this context. KLHL17 expression was validated using GSE145372. The presence and levels of KLHL17 in different cell lines were validated through quantitative real-time PCR (qRT-PCR) assays. RESULTS: KLHL17 exhibited irregular expression profiles across various cancer types, including CESC. Furthermore, increased KLHL17 levels in CESC patients were significantly associated with a lower progression-free survival (PFS) rate (hazard ratio: 1.62; 95% confidence interval: 1.01-2.60, p = 0.044). Moreover, KLHL17 expression emerged as a distinct prognostic indicator for CESC patients (p = 0.031). It has been associated with various biological pathways, such as cytokine-cytokine receptor interaction, primary immunodeficiency, cell adhesion molecules (CAMs), chemokine signaling pathway, steroid hormone biosynthesis, and others. The expression levels of KLHL17 were found to correlate with the presence of immune cells, the expression of immune checkpoint genes, and the status of MSI within CESC. Furthermore, KLHL17 expression exhibited a significant and inverse correlation with XMD15-27, rTRAIL, Paclitaxel, tp4ek, and tp4ek-k6. Furthermore, KLHL17 was found to be significantly positively regulated in CESC cell lines. DISCUSSION: The findings suggest that KLHL17 is involved in the progression of CESC and may serve as a potential prognostic marker and therapeutic target. KLHL17's association with immune cell infiltration and immune checkpoint genes indicates a role in immuneevasion. Future research should focus on validating these findings through independent datasets and experimental studies to elucidate the molecular mechanisms underlying KLHL17's role in CESC progression and immune regulation. CONCLUSION: KLHL17 is a promising prognostic marker and potential therapeutic target in CESC.

Humans↗

PubMed1998

A integrative molecular information system.

Methods of biotechnology allow the isolation, sequencing, and synthesis of molecular structures. Molecular database systems are available, which allow the worldwide data access. Methods and concepts of bioinformatics are important for the analysis of these molecular data, which represent complex regulatory networks. In this paper we present the architecture of our molecular information system.

Biotechnology↗

PubMed2000

[A new approach to pharmacogenomics].

The medicine in the 21st century will be so called "evidence based medicine" or "personalized medicine," based on the principle of "right drug to right patient." Pharmacogenomics covers the entire spectrum of genes that determines drug behavior and sensitivity, and we anticipate it will bring major impact on the healthcare system as well as the drug discovery process in the near future. Three waves of genomic impact are predicted to arise as follows: The first wave will hit on existing drugs and late-phase development candidates within the next 2-3 years, aiming to minimize the risks in clinical trials (adverse events, resistance, etc.). The wave will then affect the candidate selection process in the early pre-development stage, and finally the disease gene finding to target discovery process. The driving force will be technologies such as SNPs database, differential gene expression (DGE) analysis, proteomics, serial analysis of gene expression (SAGE) and bioinformatics. This new approach of genomic discovery (so called "integrated approach") requires knowledge on how to implement and integrate new valuable technologies from an early stage of the discovery process. The implication of SNPs, high throughput proteomics and application of structural genomics will be the key issues in the pharmacogenomics era.

Genome↗

PubMed2001

Golgi enzymes that synthesize plant cell wall polysaccharides: finding and evaluating candidates in the genomic era.

Although the synthesis of cell wall polysaccharides is a critical process during plant cell growth and differentiation, many of the wall biosynthetic genes have not yet been identified. This review focuses on the synthesis of noncellulosic matrix polysaccharides formed in the Golgi apparatus. Our consideration is limited to two types of plant cell wall biosynthetic enzymes: glycan synthases and glycosyltransferases. Classical means of identifying these enzymes and the genes that encode them rely on biochemical purification of enzyme activity to obtain amino acid sequence data that is then used to identify the corresponding gene. This type of approach is difficult, especially when acceptor substrates for activity assays are unavailable, as is the case for many enzymes. However, bioinformatics and functional genomics provide powerful alternative means of identifying and evaluating candidate genes. Database searches using various strategies and expression profiling can identify candidate genes. The involvement of these genes in wall biosynthesis can be evaluated using genetic, reverse genetic, biochemical, and heterologous expression methods. Recent advances using these methods are considered in this review.

Amino Acid Sequence↗

PubMed1998

GeneExpress: a computer system for description, analysis, and recognition of regulatory sequences in eukaryotic genome.

GeneExpress system has been designed to integrate description, analysis, and recognition of eukaryotic regulatory sequences. The system includes 5 basic units: (1) GeneNet contains an object-oriented database for accumulation of data on gene networks and signal transduction pathways and a Java-based viewer that allows an exploration and visualization of the GeneNet information; (2) Transcription Regulation combines the database on transcription regulatory regions of eukaryotic genes (TRRD) and TRRD Viewer; (3) Transcription Factor Binding Site Recognition contains a compilation of transcription factor binding sites (TFBSC) and programs for their analysis and recognition; (4) mRNA Translation is designed for analysis of structural and contextual features of mRNA 5'UTRs and prediction of their translation efficiency; and (5) ACTIVITY is the module for analysis and site activity prediction of a given nucleotide sequence. Integration of the databases in the GeneExpress is based on the Sequence Retrieval System (SRS) created in the European Bioinformatics Institute.

Artificial Intelligence↗

PubMed2005

The Mouse Tumor Biology Database: integrated access to mouse cancer biology data.

Mice have long been used as models for the study of human cancer. The National Cancer Institute has included among its research areas of extraordinary opportunity the development of new mouse genetic models of human cancer and the exploration of cancer imaging as a research tool. Because of the volume and interconnectedness of relevant data, the creation and maintenance of bioinformatics resources of mouse tumor biology is necessary to facilitate current and future cancer research. The Mouse Tumor Biology (MTB) Database provides electronic access to data generated through the study of spontaneous and induced tumors in genetically defined mice (inbred, hybrid, spontaneous and induced mutant, and genetically engineered strains of mice).

Animals↗

PubMed2002

An expectation maximization algorithm for training hidden substitution models.

We derive an expectation maximization algorithm for maximum-likelihood training of substitution rate matrices from multiple sequence alignments. The algorithm can be used to train hidden substitution models, where the structural context of a residue is treated as a hidden variable that can evolve over time. We used the algorithm to train hidden substitution matrices on protein alignments in the Pfam database. Measuring the accuracy of multiple alignment algorithms with reference to BAliBASE (a database of structural reference alignments) our substitution matrices consistently outperform the PAM series, with the improvement steadily increasing as up to four hidden site classes are added. We discuss several applications of this algorithm in bioinformatics.

Algorithms↗

PubMed1996

Programs, databases, and expert systems for human geneticists--a survey.

We present an overview of the variety of databases and programs that offer substantial aid to medical and molecular geneticists. Databases and expert systems for genetic diseases and birth defects, programs for segregation and linkage analysis, certain DNA and protein sequence databases, and information resources in general for molecular biology are addressed. These systems cannot be used effectively without the newly developed techniques of information exchange based on international computer networks. A short introduction is given to the Internet and to European institutions and organizations that offer help with the acquisition and use of bioinformatic resources.

Computer Communication Networks↗