An online model composition tool for system biology models

Background: There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results: We present the design and implementation of the Model Composition Tool (Interface) within the PathCaseSB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions: Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well

Discovering gene annotations in biomedical text databases

<p>Abstract</p> <p>Background</p> <p>Genes and gene products are frequently annotated with Gene Ontology concepts based on the evidence provided in genomics articles. Manually locating and curating information about a genomic entity from the biomedical literature requires vast amounts of human effort. Hence, there is clearly a need forautomated computational tools to annotate the genes and gene products with Gene Ontology concepts by computationally capturing the related knowledge embedded in textual data.</p> <p>Results</p> <p>In this article, we present an automated genomic entity annotation system, GEANN, which extracts information about the characteristics of genes and gene products in article abstracts from PubMed, and translates the discoveredknowledge into Gene Ontology (GO) concepts, a widely-used standardized vocabulary of genomic traits. GEANN utilizes textual "extraction patterns", and a semantic matching framework to locate phrases matching to a pattern and produce Gene Ontology annotations for genes and gene products.</p> <p>In our experiments, GEANN has reached to the precision level of 78% at therecall level of 61%. On a select set of Gene Ontology concepts, GEANN either outperforms or is comparable to two other automated annotation studies. Use of WordNet for semantic pattern matching improves the precision and recall by 24% and 15%, respectively, and the improvement due to semantic pattern matching becomes more apparent as the Gene Ontology terms become more general.</p> <p>Conclusion</p> <p>GEANN is useful for two distinct purposes: (i) automating the annotation of genomic entities with Gene Ontology concepts, and (ii) providing existing annotations with additional "evidence articles" from the literature. The use of textual extraction patterns that are constructed based on the existing annotations achieve high precision. The semantic pattern matching framework provides a more flexible pattern matching scheme with respect to "exactmatching" with the advantage of locating approximate pattern occurrences with similar semantics. Relatively low recall performance of our pattern-based approach may be enhanced either by employing a probabilistic annotation framework based on the annotation neighbourhoods in textual data, or, alternatively, the statistical enrichment threshold may be adjusted to lower values for applications that put more value on achieving higher recall values.</p

1 Web Search with Metadata Links and Multimedia Presentations

In this paper, we propose adding metadata to web for the purpose of performing semantics-based web searches and for producing multimedia presentations as a response to users ’ requests. The model uses (a) topics and “topic maps ” as metadata in reaching to relevant worldwide web documents, (b) topic prerequisites and corequisites, also called topic metalinks, to define metadata-based navigational pathways on the web and to reach to web documents that constitute sources, and (c) multimedia presentations, called Topic Comprehension Presentations, for presenting possibly large sources to users in a controlled manner. We investigate automated searching techniques that utilize in an integrated manner (i) topic metalink- and source-information in web documents and in topic map databases, (ii) webaccessible topic map databases, and (iii) local “user-profile ” databases that contain users’ knowledge on topics. The query output of such a search will be a list of Topic Comprehension Presentations, from which the user for playout purposes will choose one. We describe the first version of a Topic Comprehension Tool that partially implements the proposed framework, and report its preliminary testing

Genomic Pathways Database and Biological Data Management

In this paper we discuss the properties of biological data, and challenges it poses for data management, and argue that, in order to meet the data management requirements for “digital biology”, careful integration of the existing technologies and the development of new data management techniques for biological data are needed. Based on this premise, we present PathCase: Case Pathways Database System. PathCase is an integrated 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 starting from pathways, (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 exploratory queries, (d) a wide range of different types of queries including, “path ” and “neighborhood queries”, and graphical visualization of query outputs, and, (e) an implementation that allows for web(XML)-based dissemination of query outputs (i.e., pathways data in BIOPAX format) to researchers in the community, giving them control on the use of pathways data

A language and a physical organization technique for summary tables

A summary table IS a tabular representation of summary data, and is a useful data structure for statistical databases Priventive summary tables are basic building blocks of summmy tables, and can be represented as relations with set-valued attributes In this paper, we propose a set of summary table manipulation operators that, together with an algebra of set-valued relations, form an algebraic language for mampulatmg set-valued relations and arbitrary summary tables We then describe a physlcal orgamzatlon technique for summary tables, and discuss an lmplementatlon for summary table operators utlltzmg this techmque.Case Western Reserve University // // United State

A Graphical Icon-Based Query Language

VISUAL is a graphical icon-based query language designed for scientific databases where visualization of the relationships are important for the domain scientist to express queries. Graphical objects are not tied to the underlying formalism; instead, they represent the relationships of the application domain. VISUAL supports relational, nested, and object-oriented models naturally and has formal basis. In addition to set and bag constructs for complex objects, sequences are also supported by the data model. Concepts of external and internal queries are developed as modularization tools. A new parallel/distributed query processing paradigm is presented. VISUAL query processing techniques are also discussed. * 1. Introduction VISUAL is an object-oriented graphical database query language. It is designed for scientific databases where the data has spatial properties, includes sequences and complex objects, and queries are of exploratory in nature. Although many query languages have been..

Metadata-based modeling of information resources on the web

This paper deals with the problem of modeling Web information resources using expert knowledge and personalized user information for improved Web searching capabilities. We propose a "Web information space" model, which is composed of Web-based information resources (HTML/XML [Hypertext Markup Language/Extensible Markup Language] documents on the Web), expert advice repositories (domain-expert-specified meta-data for information resources), and personalized information about users (captured as user profiles that indicate users' preferences about experts as well as users' knowledge about topics)