Kyoto Encyclopedia of Genes and Genomes (KEGG) is a knowledge base for systematic analysis of gene functions in terms of the networks of genes and molecules. The major component of KEGG is the PATHWAY database that consists of graphical diagrams of biochemical pathways including most of the known metabolic pathways and some of the known regulatory pathways. The pathway information is also repre...

MOTIVATION The incidence of ageing-related diseases has been constantly increasing in the last decades, raising the need for creating effective methods to analyze ageing-related protein data. These methods should have high predictive accuracy and be easily interpretable by ageing experts. To enable this, one needs interpretable classification models (supervised machine learning) and features wi...

Functional characterization of genes is of great importance, e.g. in microarray studies. Valueable information for this purpose can be obtained from pathway databases, like KEGG. However, only a small fraction of genes is annotated with pathway information up to now. In contrast, information on contained protein domains can be obtained for a significantly higher number of genes, e.g. from the I...

Pancreatic cancer is a serious disease that results in more than thirty thousand deaths around the world per year. To design effective treatments, many investigators have devoted themselves to the study of biological processes and mechanisms underlying this disease. However, it is far from complete. In this study, we tried to extract important gene ontology (GO) terms and KEGG pathways for panc...

KEGG, Kyoto Encyclopedia of Genes and Genomes, project consists of three types of data, pathways, hierarchies, and binary relations, that are used to represent biological knowledge. We present here a C++ library for e cient calculation of possible pathways from binary relations. In practice, the library is used to calculate metabolic pathways from the substrate-product relations of enzymes stor...

A grand challenge in the post-genomic era is a complete computer representation of the cell and the organism, which will enable computational prediction of higher-level complexity of cellular processes and organism behavior from genomic information. Toward this end we have been developing a knowledge-based approach for network prediction, which is to predict, given a complete set of genes in th...

For recent decades, the EC (Enzyme Commission) number has been used to research various biological reactions and metabolic pathways. However, the EC classification is unsuitable for bioinformatics analyses because of the, at least, following two problems. One is inconsistent criteria for classification, utilizing reaction patterns, substrates, transfered groups, and acceptor groups in different...