Euna Jeong

Cell Illustrator 4.0: a computational platform for systems biology.

Cell Illustrator is a software platform for Systems Biology that uses the concept of Petri net for modeling and simulating biopathways. It is intended for biological scientists working at bench. The latest version of Cell Illustrator 4.0 uses Java Web Start technology and is enhanced with new capabilities, including: automatic graph grid layout algorithms using ontology information; tools using Cell System Markup Language (CSML) 3.0 and Cell System Ontology 3.0; parameter search module; high-performance simulation module; CSML database management system; conversion from CSML model to programming languages (FORTRAN, C, C++, Java, Python and Perl); import from SBML, CellML, and BioPAX; and, export to SVG and HTML. Cell Illustrator employs an extension of hybrid Petri net in an object-oriented style so that biopathway models can include objects such as DNA sequence, molecular density, 3D localization information, transcription with frame-shift, translation with codon table, as well as biochemical reactions.

An efficient grid layout algorithm for biological networks utilizing various biological attributes

BackgroundClearly visualized biopathways provide a great help in understanding biological systems. However, manual drawing of large-scale biopathways is time consuming. We proposed a grid layout algorithm that can handle gene-regulatory networks and signal transduction pathways by considering edge-edge crossing, node-edge crossing, distance measure between nodes, and subcellular localization information from Gene Ontology. Consequently, the layout algorithm succeeded in drastically reducing these crossings in the apoptosis model. However, for larger-scale networks, we encountered three problems: (i) the initial layout is often very far from any local optimum because nodes are initially placed at random, (ii) from a biological viewpoint, human layouts still exceed automatic layouts in understanding because except subcellular localization, it does not fully utilize biological information of pathways, and (iii) it employs a local search strategy in which the neighborhood is obtained by moving one node at each step, and automatic layouts suggest that simultaneous movements of multiple nodes are necessary for better layouts, while such extension may face worsening the time complexity.ResultsWe propose a new grid layout algorithm. To address problem (i), we devised a new force-directed algorithm whose output is suitable as the initial layout. For (ii), we considered that an appropriate alignment of nodes having the same biological attribute is one of the most important factors of the comprehension, and we defined a new score function that gives an advantage to such configurations. For solving problem (iii), we developed a search strategy that considers swapping nodes as well as moving a node, while keeping the order of the time complexity. Though a naïve implementation increases by one order, the time complexity, we solved this difficulty by devising a method that caches differences between scores of a layout and its possible updates.ConclusionLayouts of the new grid layout algorithm are compared with that of the previous algorithm and human layout in an endothelial cell model, three times as large as the apoptosis model. The total cost of the result from the new grid layout algorithm is similar to that of the human layout. In addition, its convergence time is drastically reduced (40% reduction).

A weighted profile based method for Protein-RNA interacting residue prediction

The prediction of putative RNA-interacting residues in proteins is an important problem in a field of molecular recognition. We suggest a weighted profile based method for predicting RNA-interacting residues, which utilizes the trained neural network. Most neural networks have a learning rule which allows the network to adjust its connection weights in order to correctly classify the training data. We focus on the network weights that are dependent on the training data set and give evidence of which inputs were more influential in the network. A large set of the network weights trained on sequence profiles is analyzed and qualified. We explore the feasibility of utilizing the qualified information to improve the prediction performance for protein-RNA interaction. Our proposed method shows a considerable improvement, which has been applied to the profiles of the PSI-BLAST alignment. Results for predictions using alternative representations of profile are included for comparison.

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

BackgroundMany biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level.ResultsWe selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models.ConclusionBy using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Ontology-based instance data validation for high-quality curated biological pathways

BackgroundModeling in systems biology is vital for understanding the complexity of biological systems across scales and predicting system-level behaviors. To obtain high-quality pathway databases, it is essential to improve the efficiency of model validation and model update based on appropriate feedback.ResultsWe have developed a new method to guide creating novel high-quality biological pathways, using a rule-based validation. Rules are defined to correct models against biological semantics and improve models for dynamic simulation. In this work, we have defined 40 rules which constrain event-specific participants and the related features and adding missing processes based on biological events. This approach is applied to data in Cell System Ontology which is a comprehensive ontology that represents complex biological pathways with dynamics and visualization. The experimental results show that the relatively simple rules can efficiently detect errors made during curation, such as misassignment and misuse of ontology concepts and terms in curated models.ConclusionsA new rule-based approach has been developed to facilitate model validation and model complementation. Our rule-based validation embedding biological semantics enables us to provide high-quality curated biological pathways. This approach can serve as a preprocessing step for model integration, exchange and extraction data, and simulation.

Residual bootstrapping and median filtering for robust estimation of gene networks from microarray data

We propose a robust estimation method of gene networks based on microarray gene expression data. It is well-known that microarray data contain a large amount of noise and some outliers that interrupt the estimation of accurate gene networks. In addition, some relationships between genes are nonlinear, and linear models thus are not enough for capturing such a complex structure. In this paper, we utilize the moving boxcel median filter and the residual bootstrap for constructing a Bayesian network in order to attain robust estimation of gene networks. We conduct Monte Carlo simulations to examine the properties of the proposed method. We also analyze Saccharomyces cerevisiae cell cycle data as a real data example.

Systems biology model repository for macrophage pathway simulation

SUMMARY The Macrophage Pathway Knowledgebase (MACPAK) is a computational system that allows biomedical researchers to query and study the dynamic behaviors of macrophage molecular pathways. It integrates the knowledge of 230 reviews that were carefully checked by specialists for their accuracy and then converted to 230 dynamic mathematical pathway models. MACPAK comprises a total of 24 009 entities and 12 774 processes and is described in the Cell System Markup Language (CSML), an XML format that runs on the Cell Illustrator platform and can be visualized with a customized Cytoscape for further analysis. AVAILABILITY MACPAK can be accessed via an interactive web site at http://macpak.csml.org. The CSML pathway models are available under the Creative Commons license.

CSO validator

Summary: Manual curation and validation of large-scale biological pathways are required to obtain high-quality pathway databases. In a typical curation process, model validation and model update based on appropriate feedback are repeated and requires considerable cooperation of scientists. We have developed a CSO (Cell System Ontology) validator to reduce the repetition and time during the curation process. This tool assists in quickly obtaining agreement among curators and domain experts and in providing a consistent and accurate pathway database. Availability: The tool is available on http://csovalidator.csml.org. Contact: masao@hgc.jp