SEARCH · PubMed Health

Results for “biological pathway”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 19 recordsLinked to original sources

PubMed2006

cPath: open source software for collecting, storing, and querying biological pathways.

BACKGROUND: Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. RESULTS: We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. CONCLUSION: cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.

Computational Biology↗

PubMed2005

Illuminating drug discovery with biological pathways.

Systems biology promises to impact significantly on the drug discovery process. One of its ultimate goals is to provide an understanding of the complete set of molecular mechanisms describing an organism. Although this goal is a long way off, many useful insights can already come from currently available information and technology. One of the biggest challenges in drug discovery today is the high attrition rate: many promising candidates prove ineffective or toxic owing to a poor understanding of the molecular mechanisms of biological systems they target. A "systems" approach can help identify pathways related to a disease and can suggest secondary effects of drugs that might cause these problems and thus ultimately improve the drug discovery pipeline.

Animals↗

PubMed2004

ArrayXPath: mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics.

Biological pathways can provide key information on the organization of biological systems. ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data for integrated biological pathway resources using Scalable Vector Graphics (SVG). By integrating major bio-databases and searching pathway resources, ArrayXPath automatically maps different types of identifiers from microarray probes and pathway elements. When one inputs gene-expression clusters, ArrayXPath produces a list of the best matching pathways for each cluster. We applied Fisher's exact test and the false discovery rate (FDR) to evaluate the statistical significance of the association between a cluster and a pathway while correcting the multiple-comparison problem. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of pathways integrated with gene-expression profiles.

Cluster Analysis↗

PubMed2004

Genomic approaches in dissecting complex biological pathways.

Advances in genomic research have provided many types of large-scale data that contain rich information on various biological pathways. Intensive efforts have been made to qualitatively or quantitatively model biological pathways using these genomic data. Some general network properties, such as the scale-free property and network motifs, have been discussed and various network models have been applied to reconstruct pathways. However, there is a lack of systematic integration of prior knowledge and different genomic data in these analyses. In this review, we discuss pathway reconstruction under the consideration of the complexity embedded in the biological system, and the global and local properties of biological pathways. We review major methodologies, including clustering methods, scale-free networks models, Bayesian networks models, Boolean networks models, systems of differential equations, and data integration methods. We focus on the difficulty of each methodology in modeling biological pathways, and emphasize that different models capture different aspects of biological pathways or genomic data. The 'noisy' large-scale genomic data require the mathematical models and computational methods to be both robust and identifiable. In addition, we believe that ideal models should have the capability of incorporating various data types and these models need to be assessed through rigorous comparisons with empirical data.

Bayes Theorem↗

PubMed2004

Constructing biological pathway models with hybrid functional Petri nets.

In many research projects on modeling and analyzing biological pathways, the Petri net has been recognized as a promising method for representing biological pathways. From the pioneering works by Reddy et al., 1993, and Hofestädt, 1994, that model metabolic pathways by traditional Petri net, several enhanced Petri nets such as colored Petri net, stochastic Petri net, and hybrid Petri net have been used for modeling biological phenomena. Recently, Matsuno et al., 2003b, introduced the hybrid functional Petri net (HFPN) in order to give a more intuitive and natural modeling method for biological pathways than these existing Petri nets. Although the paper demonstrates the effectiveness of HFPN with two examples of gene regulation mechanism for circadian rhythms and apoptosis signaling pathway, there has been no detailed explanation about the method of HFPN construction for these examples. The purpose of this paper is to describe method to construct biological pathways with the HFPN step-by-step. The method is demonstrated by the well-known glycolytic pathway controlled by the lac operon gene regulatory mechanism.

Adenosine Diphosphate↗

PubMed2003

Pathways database system: an integrated system for biological pathways.

MOTIVATION: During the next phase of the Human Genome Project, research will focus on functional studies of attributing functions to genes, their regulatory elements, and other DNA sequences. To facilitate the use of genomic information in such studies, a new modeling perspective is needed to examine and study genome sequences in the context of many kinds of biological information. Pathways are the logical format for modeling and presenting such information in a manner that is familiar to biological researchers. RESULTS: In this paper we present an integrated system, called Pathways Database System, with a set of software tools for modeling, storing, analyzing, visualizing, and querying biological pathways data at different levels of genetic, molecular, biochemical and organismal detail. The novel features of the system include: (a) genomic information integrated with other biological data and presented from a pathway, rather than from the DNA sequence, perspective; (b) design for biologists who are possibly unfamiliar with genomics, but whose research is essential for annotating gene and genome sequences with biological functions; (c) database design, implementation and graphical tools which enable users to visualize pathways data in multiple abstraction levels, and to pose predetermined queries; and (d) an implementation that allows for web(XML)-based dissemination of query outputs (i.e. pathways data) to researchers in the community, giving them control on the use of pathways data. AVAILABILITY: Available on request from the authors.

Database Management Systems↗

PubMed2005

Mapping of orthologous genes in the context of biological pathways: An application of integer programming.

Mapping biological pathways across microbial genomes is a highly important technique in functional studies of biological systems. Existing methods mainly rely on sequence-based orthologous gene mapping, which often leads to suboptimal mapping results because sequence-similarity information alone does not contain sufficient information for accurate identification of orthology relationship. Here we present an algorithm for pathway mapping across microbial genomes. The algorithm takes into account both sequence similarity and genomic structure information such as operons and regulons. One basic premise of our approach is that a microbial pathway could generally be decomposed into a few operons or regulons. We formulated the pathway-mapping problem to map genes across genomes to maximize their sequence similarity under the constraint that the mapped genes be grouped into a few operons, preferably coregulated in the target genome. We have developed an integer-programming algorithm for solving this constrained optimization problem and implemented the algorithm as a computer software program, p-map. We have tested p-map on a number of known homologous pathways. We conclude that using genomic structure information as constraints could greatly improve the pathway-mapping accuracy over methods that use sequence-similarity information alone.

Algorithms↗

PubMed1999

Genetic selection of peptide inhibitors of biological pathways.

Genetic selections were used to find peptides that inhibit biological pathways in budding yeast. The peptides were presented inside cells as peptamers, surface loops on a highly expressed and biologically inert carrier protein, a catalytically inactive derivative of staphylococcal nuclease. Peptamers that inhibited the pheromone signaling pathway, transcriptional silencing, and the spindle checkpoint were isolated. Putative targets for the inhibitors were identified by a combination of two-hybrid analysis and genetic dissection of the target pathways. This analysis identified Ydr517w as a component of the spindle checkpoint and reinforced earlier indications that Ste50 has both positive and negative roles in pheromone signaling. Analysis of transcript arrays showed that the peptamers were highly specific in their effects, which suggests that they may be useful reagents in organisms that lack sophisticated genetics as well as for identifying components of existing biological pathways that are potential targets for drug discovery.

Amino Acid Sequence↗

PubMed2006

Gene expression profiles of head and neck carcinomas from Sudanese and Norwegian patients reveal common biological pathways regardless of race and lifestyle.

PURPOSE: To explore possible range of gene expression profiles in head and neck squamous cell carcinomas (HNSCC) and pairwised normal controls from Sudanese (n = 72) and Norwegian (n = 45) patients using a 15K cDNA microarray and to correlate the findings with clinicopathologic variables. EXPERIMENTAL DESIGN: Samples from Sudan were grouped according to anatomic location/patients' habit of toombak (snuff) use, and 37 pools of 2 to 11 tumors matched to 37 pools of their normal controls from the same patients, respectively, were prepared. For Norway, eight pools of 3 to 11 tumors matched to eight pools of their normal controls from the same patients, respectively, were prepared according to anatomic location. Pools (n = 45) were hybridized to microarrays. For controls, 33 of the pools were hybridized against Human Reference RNA. Scanned array images were recorded, and data analysis was done in groups. For verification, results for selected genes were analyzed using quantitative real-time PCR/immunohistochemistry. RESULTS: We identified 136 genes from Sudan and 154 from Norway as differentially expressed between tumors and controls. Changes of the genes found were confirmed in >70% of the pools by hybridization against Reference RNA. Seventy-three genes and three main pathways (signal transduction, cell communication, and ligand-receptor interaction) were of relevance to the HNSCCs from both countries. Hierarchical clustering of the 73 genes identified subclasses of mixed tumors from the two populations, two independent subgroups for Norwegian tumors by their anatomic sites, and five subgroups for Sudanese tumors by their toombak habits. Quantitative real-time PCR/immunohistochemistry validated the microarray-based data. CONCLUSIONS: Differences in gene expression between tumor and nontumor tissues were identified in HNSCCs. Analysis of the two population groups revealed a common set of 73 genes within three main biological pathways. This indicates that the development of HNSCCs is mediated by similar biological pathways regardless of differences related to race, ethnicity, lifestyle, and/or exposure to environmental carcinogens. Of particular interest, however, was the valuable association of gene expression signature found with toombak use and anatomic site of the tumors.

Aged↗

PubMed2003

Java editor for biological pathways.

SUMMARY: A visual Java-based tool for drawing and annotating biological pathways was developed. This tool integrates the possibilities of charting elements with different attributes (size, color, labels), drawing connections between elements in distinct characteristics (color, structure, width, arrows), as well as adding links to molecular biology databases, promoter sequences, information on the function of the genes or gene products, and references. It is easy to use and system independent. The result of the editing process is a PNG (portable network graphics) file for the images and XML (extended markup language) file for the appropriate links.

Documentation↗

PubMed2003

KnowledgeEditor: a new tool for interactive modeling and analyzing biological pathways based on microarray data.

UNLABELLED: KnowledgeEditor is a graphical workbench for biological experts to model biomolecular network graphs. The modeled network data are represented by SRML, and can be published via the internet with the help of plug-in module 'GSCope'. KnowledgeEditor helps us to model and analyze biological pathways based on microarray data. It is possible to analyze the drawn networks by simulating up-down regulatory cascade in molecular interactions. AVAILABILITY: KnowledgeEditor is available at http://gscope.gsc.riken.go.jp/.

Cluster Analysis↗

PubMed2005

PATIKAweb: a Web interface for analyzing biological pathways through advanced querying and visualization.

Patikaweb provides a Web interface for retrieving and analyzing biological pathways in the Patika database, which contains data integrated from various prominent public pathway databases. It features a user-friendly interface, dynamic visualization and automated layout, advanced graph-theoretic queries for extracting biologically important phenomena, local persistence capability and exporting facilities to various pathway exchange formats.

Computer Graphics↗

PubMedDate not supplied

Common biological pathways in eating disorders and obesity.

The purpose of this article is to summarize briefly potential biological pathways that are common among anorexia nervosa, bulimia nervosa, and obesity. We conclude that data on serotonergic and beta-endorphin regulatory systems provide the most promising leads for potential trait-based etiological theories. We then discuss the contribution of current data to a better understanding of the etiology and maintenance of eating disorders. Finally, we comment on how the exploration for common biological mechanisms highlights problems in nosological diagnosis (i.e., the lack of symptom specificity among disorders) and obscures the etiological significance of social stressors and cultural factors.

Anorexia Nervosa↗

PubMed2005

ArrayXPath II: mapping and visualizing microarray gene-expression data with biomedical ontologies and integrated biological pathway resources using Scalable Vector Graphics.

SUMMARY: ArrayXPath (http://www.snubi.org/software/ArrayXPath/) is a web-based service for mapping and visualizing microarray gene-expression data with integrated biological pathway resources using Scalable Vector Graphics (SVG). Deciphering the crosstalk among pathways and integrating biomedical ontologies and knowledge bases may help biological interpretation of microarray data. ArrayXPath is empowered by integrating gene-pathway, disease-pathway, drug-pathway and pathway-pathway correlations with integrated Gene Ontology, Medical Subject Headings and OMIM Morbid Map-based annotations. We applied Fisher's exact test and relative risk to evaluate the statistical significance of the correlations. ArrayXPath produces Javascript-enabled SVGs for web-enabled interactive visualization of gene-expression profiles integrated with gene-pathway-disease interactions enriched by biomedical ontologies.

Cluster Analysis↗

PubMed2004

Model validation of biological pathways using Petri nets--demonstrated for apoptosis.

This paper demonstrates the first steps of a new integrating methodology to develop and analyse models of biological pathways in a systematic manner using well established Petri net technologies. The whole approach comprises step-wise modelling, animation, model validation as well as qualitative and quantitative analysis for behaviour prediction. In this paper, the first phase is addressed how to develop and validate a qualitative model, which might be extended afterwards to a quantitative model. The example used in this paper is devoted to apoptosis, the genetically programmed cell death. Apoptosis is an essential part of normal physiology for most metazoan species. Disturbances in the apoptotic process could lead to several diseases. The signal transduction pathway of apoptosis includes highly complex mechanisms to control and execute programmed cell death. This paper explains how to model and validate this pathway using qualitative Petri nets. The results provide a mathematically unique and valid model enabling the confirmation of known properties as well as new insights in this pathway.

Apoptosis↗

PubMed2005

Explore biological pathways from noisy array data by directed acyclic Boolean networks.

We consider the structure of directed acyclic Boolean (DAB) networks as a tool for exploring biological pathways. In a DAB network, the basic objects are binary elements and their Boolean duals. A DAB is characterized by two kinds of pairwise relations: similarity and prerequisite. The latter is a partial order relation, namely, the on-status of one element is necessary for the on-status of another element. A DAB network is uniquely determined by the state space of its elements. We arrange samples from the state space of a DAB network in a binary array and introduce a random mechanism of measurement error. Our inference strategy consists of two stages. First, we consider each pair of elements and try to identify their most likely relation. In the meantime, we assign a score, s-p-score, to this relation. Second, we rank the s-p-scores obtained from the first stage. We expect that relations with smaller s-p-scores are more likely to be true, and those with larger s-p-scores are more likely to be false. The key idea is the definition of s-scores (referring to similarity), p-scores (referring to prerequisite), and s-p-scores. As with classical statistical tests, control of false negatives and false positives are our primary concerns. We illustrate the method by a simulated example, the classical arginine biosynthetic pathway, and show some exploratory results on a published microarray expression dataset of yeast Saccharomyces cerevisiae obtained from experiments with activation and genetic perturbation of the pheromone response MAPK pathway.

Algorithms↗

PubMed2004

Distinguishing key biological pathways between primary breast cancers and their lymph node metastases by gene function-based clustering analysis.

In order to identify key biological pathways that can distinguish between primary breast cancers and their lymph node metastases, we employed gene expression profiling together with gene function-based clustering analysis. We first acquired gene expression profiles of 9 matched primary tumors and the corresponding metastases that contained at least 75% of tumor cells. Then, we applied a clustering algorithm to the preprocessed data. In order to focus on the most informative genes, we ranked all the genes individually based on their abilities to separate the primary breast tumor and metastases samples. Further, we separated these genes into six functional groups according to the Stanford SOURCE database: 'cell cycle,' 'apoptosis,' 'metabolism,' 'cell adhesion and migration,' 'signal transduction,' and 'transcriptional factor and DNA binding molecules.' Unsupervised clustering analysis using all of the 2,303 genes on the microarrays was not able to separate the primary and metastases samples. Clustering analysis using the most informative genes revealed that primary tumors were more tightly clustered, whereas the metastases samples were relatively heterogeneous. The clustering analysis with the genes belonging to different functional groups showed that different functional gene sets varied in their abilities to separate primary tumors and their metastases. Marked separations were found with genes involved in metabolism, signal transduction, cell cycle, and transcriptional factor and DNA binding molecules. In contrast, apoptosis and cell adhesion and migration genes did not provide a clear separation of the two groups of samples. These results suggest that metastatic cells have different metabolism and signal transduction activities, regulated by transcriptional events, from the primary tumor cells. The results also suggest that the altered cell adhesion and migration potentials that are required for tumors to metastasize already exist in the primary tumors as a whole.

Biomarkers, Tumor↗

PubMed2006

Cross-sectional relations of multiple biomarkers from distinct biological pathways to brachial artery endothelial function.

BACKGROUND: Endothelial dysfunction is a critical intermediate phenotype in the pathogenesis of cardiovascular disease. We evaluated the relative contributions of distinct biological pathways to interindividual variation in endothelial function by relating prototype biomarkers (representing these pathways) to brachial artery vasodilator function. METHODS AND RESULTS: We investigated the cross-sectional relations of a panel of 7 biomarkers measured at a routine examination to brachial artery vasodilator function (flow-mediated dilation [FMD] and reactive hyperemia) assessed at a subsequent examination (mean interval, 2.9 years) in 2113 Framingham Heart Study participants (mean age, 61 years; 54% women). We selected biomarkers from 4 biological domains: neurohormonal (N-terminal pro-atrial natriuretic peptide [N-ANP], B-type natriuretic peptide [BNP], renin, aldosterone), hemostatic factors (plasminogen activator inhibitor-1 [PAI-1]), inflammation (C-reactive protein [CRP]), and target organ damage (urine albumin-creatinine ratio). In age- and sex-adjusted models, several biomarkers were related to baseline brachial artery diameter (PAI-1, CRP, urine albumin-creatinine ratio), baseline mean flow (N-ANP, BNP, PAI-1, CRP, aldosterone), FMD (N-ANP, PAI-1, CRP, renin), and reactive hyperemia (BNP, PAI-1, CRP, renin, urine albumin-creatinine ratio). In multivariable analyses relating the 7 biomarkers conjointly to each vascular function measure (adjusting for known risk factors), N-ANP and renin were positively related to FMD (P=0.001 and P=0.04, respectively), and N-ANP was inversely related to baseline mean flow velocity (P=0.01). None of the other biomarkers was significantly related to the vascular function measures studied. CONCLUSIONS: In our large community-based sample, a conservative strategy relating several biomarkers to vascular endothelial function identified plasma N-ANP as a key correlate of mean flow under basal conditions and of FMD in response to forearm cuff occlusion.

Aged↗