Kouichi Takahashi

The systems biology markup language (SBML) : a medium for representation and exchange of biochemical network models

MOTIVATION Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY The specification of SBML Level 1 is freely available from http://www.sbml.org/

Space in systems biology of signaling pathways--towards intracellular molecular crowding in silico.

How cells utilize intracellular spatial features to optimize their signaling characteristics is still not clearly understood. The physical distance between the cell‐surface receptor and the gene expression machinery, fast reactions, and slow protein diffusion coefficients are some of the properties that contribute to their intricacy. This article reviews computational frameworks that can help biologists to elucidate the implications of space in signaling pathways. We argue that intracellular macromolecular crowding is an important modeling issue, and describe how recent simulation methods can reproduce this phenomenon in either implicit, semi‐explicit or fully explicit representation.

Computational challenges in cell simulation: a software engineering approach

Molecular biologys advent in the 20th century has exponentially increased our knowledge about the inner workings of life. We have dozens of completed genomes and an array of high-throughput methods to characterize gene encodings and gene product operation. The question now is how we will assemble the various pieces. In other words, given sufficient information about a living cells molecular components, can we predict its behavior? We introduce the major classes of cellular processes relevant to modeling, discuss software engineerings role in cell simulation, and identify cell simulation requirements. Our E-Cell project aims to develop the theories, techniques, and software platforms necessary for whole-cell-scale modeling, simulation, and analysis. Since the projects launch in 1996, we have built a variety of cell models, and we are currently developing new models that vary with respect to species, target subsystem, and overall scale.

Viscosity and drag force involved in organelle transport: Investigation of the fluctuation dissipation theorem

We observed the motion of an organelle transported by motor proteins in cells using fluorescence microscopy. Particularly, among organelles, the mitochondria in PC12 cells were studied. A mitochondrion was dragged at a constant speed for several seconds without pausing. We investigated the fluctuation dissipation theorem for this constant drag motion by comparing it with the motion of Brownian beads that were incorporated into the cells by an electroporation method. We estimated the viscosity value inside cells from the diffusion coefficients of the beads. Then the viscosity value obtained by using the beads was found to be slightly lower than that obtained from the diffusion coefficient for the organelle motion via the Einstein relation. This discrepancy indicates the violation of the Einstein relation for the organelle motion.Graphical abstract

Distributed cell biology simulations with e-cell system

Many useful applications of simulation in computational cell biology, e.g. kinetic parameter estimation, Metabolic Control Analysis (MCA), and bifurcation analysis, require a large number of repetitive runs with different input parameters. The heavy requirements imposed by these analysis methods on computational resources has led to an increased interest in parallel- and distributed computing technologies. We have developed a scripting environment that can execute, and where possible, automatically parallelize those mathematical analysis sessions transparently on any of (1) single-processor workstations, (2) Shared-memory Multiprocessor (SMP) servers, (3) workstation clusters, and (4) computational grid environments. This computational framework, E-Cell SessionManager (ESM), is built upon E-Cell System Version 3, a generic software environment for the modeling, simulation, and analysis of whole-cell scale biological systems. Here we introduce the ESM architecture and provide results from benchmark experiments that addressed 2 typical computationally intensive biological problems, (1) a parameter estimation session of a small hypothetical pathway and (2) simulations of a stochastic E. coli heat-shock model with different random number seeds to obtain the statistical characteristics of the stochastic fluctuations.