Comprehensive experimental resources, such as ORFeome clone libraries and deletion mutant collections, are fundamental tools for elucidation of gene function. Data sets by omics analysis using these resources provide key information for functional analysis, modeling and simulation both in individual and systematic approaches. With the long-term goal of complete understanding of a cell, we have over the past decade created a variety of clone and mutant sets for functional genomics studies of Escherichia coli K-12. We have made these experimental resources freely available to the academic community worldwide. Accordingly, these resources have now been used in numerous investigations of a multitude of cell processes. Quality control is extremely important for evaluating results generated by these resources. Because the annotation has been changed since 2005, which we originally used for the construction, we have updated these genomic resources accordingly. Here, we describe GenoBase (http://ecoli.naist.jp/GB/), which contains key information about comprehensive experimental resources of E. coli K-12, their quality control and several omics data sets generated using these resources.

Motivation: Rapid advances in live-cell imaging analysis and mathematical modeling have produced a large amount of quantitative data on spatiotemporal dynamics of biological objects ranging from molecules to organisms. There is now a crucial need to bring these large amounts of quantitative biological dynamics data together centrally in a coherent and systematic manner. This will facilitate the reuse of this data for further analysis.Results: We have developed the Systems Science of Biological Dynamics database (SSBD) to store and share quantitative biological dynamics data. SSBD currently provides 311 sets of quantitative data for single molecules, nuclei and whole organisms in a wide variety of model organisms from Escherichia coli to Mus musculus. The data are provided in Biological Dynamics Markup Language format and also through a REST API. In addition, SSBD provides 188 sets of time-lapse microscopy images from which the quantitative data were obtained and software tools for data visualization and analysis.Availability and Implementation: SSBD is accessible at http://ssbd.qbic.riken.jp.Contact: sonami@riken.jp

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ECOH is freely available via the Internet at http://www.bioinfo.sk.ritsumei.ac.jp/apps/ecoh/. This program only works on 32-bit Windows.

In many of the chemical reactions in living cells, enzymes act as catalysts in the conversion of certain compounds (substrates) into other compounds (products). Metabolic pathways are formed as the products of these reactions are used as the substrates of other reactions. Comparative analyses of the metabolic pathways among species provide important information on both evolution and potential pharmacological targets. Here, we propose a method to align the metabolic pathways based on similarities between chemical structures. To measure the degree of chemical similarity, we formalized a scoring system using the MACCS keys and the Tanimoto/Jaccard coefficients. To determine the effectiveness of our method, it was applied to analyses of metabolic pathways in Escherichia coli. The results revealed compound similarities between fructose and mannose biosynthesis and galactose biosynthesis pathways.