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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(More)
We propose a state space representation of vector autoregressive model and its sparse learning based on L1 regularization to achieve efficient estimation of dynamic gene networks based on time course microarray data. The proposed method can overcome drawbacks of the vector autoregressive model and state space model; the assumption of equal time interval and(More)
MOTIVATION Many human genes express multiple transcript isoforms through alternative splicing, which greatly increases diversity of protein function. Although RNA sequencing (RNA-Seq) technologies have been widely used in measuring amounts of transcribed mRNA, accurate estimation of transcript isoform abundances from RNA-Seq data is challenging because(More)
A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable(More)
BACKGROUND Clearly 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(More)
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the superstructure. The previously derived constrained optimal search (COS) remains limited even for sparse superstructures. To extend its feasibility, we propose to divide the superstructure(More)
The Tohoku Medical Megabank Organization reports the whole-genome sequences of 1,070 healthy Japanese individuals and construction of a Japanese population reference panel (1KJPN). Here we identify through this high-coverage sequencing (32.4 × on average), 21.2 million, including 12 million novel, single-nucleotide variants (SNVs) at an estimated false(More)
Structural variations (SVs), such as insertions, deletions, inversions, and duplications, are a common feature in human genomes, and a number of studies have reported that such SVs are associated with human diseases. Although the progress of next generation sequencing (NGS) technologies has led to the discovery of a large number of SVs, accurate and(More)
High-throughput RNA sequencing (RNA-Seq) enables quantification and identification of transcripts at single-base resolution. Recently, longer sequence reads become available thanks to the development of new types of sequencing technologies as well as improvements in chemical reagents for the Next Generation Sequencers. Although several computational methods(More)