Grammatical inference methods are expected to find grammatical structures hidden in biological sequences. One hopes that studies of grammar serve as an appropriate tool for theory formation. Thus, we have developed JSequitur for automatically generating the grammatical structure of biological sequences in an inference framework of string compression algorithms. Our original motivation was to find any grammatical traits of several cancer genes that can be detected by string compression algorithms. Through this research, we could not find any meaningful unique traits of the cancer genes yet, but we could observe some interesting traits in regards to the relationship among gene length, similarity of sequences, the patterns of the generated grammar, and compression rate.
Genes, Neoplasm ; Motivation ; Natural Language Processing

Treating genomes just as languages raises the possibility of producing concise generalizations about information in biological sequences. Grammars used in this way would constitute a model of underlying biological processes or structures, and that grammars may, in fact, serve as an appropriate tool for theory formation. The increasing number of biological sequences that have been yielded further highlights a growing need for developing grammatical systems in bioinformatics. The intent of this review is therefore to list some bibliographic references regarding the recent progresses in the field of grammatical modeling of biological sequences. This review will also contain some sections to briefly introduce basic knowledge about formal language theory, such as the Chomsky hierarchy, for non-experts in computational linguistics, and to provide some helpful pointers to start a deeper investigation into this field.
Biological Processes ; Computational Biology ; Generalization (Psychology) ; Genome ; Linguistics ; Natural Language Processing

The characteristics of metabolic pathways make them particularly amenable to layered graph drawing methods. This paper presents a visual Java-based tool for drawing and annotating biological pathways in twoand- a-half dimensions (2.5D) as an alternative to three dimensional (3D) visualizations. Such visualization allows user to display different groups of clustered nodes, in different parallel planes, and to see a detailed view of a group of objects in focus and its place in the context of the whole system. This tool is an extended version of J2dPathway.
Hypogonadism ; Metabolic Networks and Pathways ; Mitochondrial Diseases ; Ophthalmoplegia