MOTIVATION: Understanding life cannot be accomplished without making full use of biological data, which are scattered across databases of diverse categories in life sciences. To connect such data seamlessly, identifier (ID) conversion plays a key role. However, existing ID conversion services have disadvantages, such as covering only a limited range of biological categories of databases, not keeping up with the updates of the original databases and outputs being hard to interpret in the context of biological relations, especially when converting IDs in multiple steps. RESULTS: TogoID is an ID conversion service implementing unique features with an intuitive web interface and an application programming interface (API) for programmatic access. TogoID currently supports 65 datasets covering various biological categories. TogoID users can perform exploratory multistep conversions to find a path among IDs. To guide the interpretation of biological meanings in the conversions, we crafted an ontology that defines the semantics of the dataset relations. AVAILABILITY AND IMPLEMENTATION: The TogoID service is freely available on the TogoID website (https://togoid.dbcls.jp/) and the API is also provided to allow programmatic access. To encourage developers to add new dataset pairs, the system stores the configurations of pairs at the GitHub repository (https://github.com/togoid/togoid-config) and accepts the request of additional pairs. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Science computing platforms are changing from traditional on-premises computing platforms to clouds. The style of research publications is also changing with the movement of open science. For example, it is common that researchers in the bioscience research community publish their research papers with the associated research data on the Internet. Furthermore, demands for reproducibility of computational experiments are increasing. A conventional method, or sharing source codes of application programs, is not enough to guarantee the reproducibility of computational experiments. In this paper, we propose overlay cloud architecture for building virtual clouds on cloud platforms. In the proposed architecture, the middleware, Virtual Cloud Provider (VCP), automatically configures computing environments (application programs, operating systems, libraries and binaries) that is required to reproduce computing results by using the Linux container technology. VCP also deploys containers of computing environments on clouds and configures overlay network connecting the deployed containers. A case study which considers DNA sequencing software shows how the VCP can be deployed, and used to reproduce results.

This paper proposes an intercloud brokerage method for system infrastructure deployments of genomic big data analytics workflows. The proposed method utilizes a conjunction of universally quantified atomic formula to describe requirements given by users, and selects combinations of cloud services based on logical reasoning by the replacement of definite clause sets created from conjunction of the atomic formulas, while preserving the declarative meaning of the system infrastructures' constraint conditions. We also define algorithms for the replacement of definite clause sets, and present an example of the use of the proposed intercloud brokerage method.