A REVIEW: CONCEPTUAL DATA MODELS FOR BIOLOGICAL DOMAIN

ABSTRACT This paper demonstrates the survey and review of conceptual data models and the novel data modeling techniques of biological data. The term conceptual data modeling is used in broad categories in this sense. The biological data, its concepts and frameworks have diversity of expressiveness under the umbrella of bioinformatics. If we consider the biological data a single field of research, it is not possible to handle all these things efficiently and completely. For provision of highly maintainable and efficient solutions, which will have less cost and complexity, we must reduce its scope by making its sub domains in bioinformatics. Keep in mind the aforementioned reasons, we considered only the concept of central dogma of molecular biology; produces sequence biological data (DNA, RNA and protein structures); to describe this reviewed study of conceptual modeling. Our objectives are to provide a current state of art study of conceptual data models for a sequence biological data. Based on this research, we will propose a uniform data model for biological data for unification purposes. In this review paper, we provide the analysis and post-mortems of existing conceptual biological data models, and present their comparison, provided on the basis of conceptually proposed methodologies, Meta data, modeling methods and other critical aspects, necessary for sequence data. This study provides us the cutting edge for the integration of biological data

Transforming semi-structured life science diagrams into meaningful domain ontologies with DiDOn

AbstractBio-ontology development is a resource-consuming task despite the many open source ontologies available for reuse. Various strategies and tools for bottom-up ontology development have been proposed from a computing angle, yet the most obvious one from a domain expert perspective is unexplored: the abundant diagrams in the sciences. To speed up and simplify bio-ontology development, we propose a detailed, micro-level, procedure, DiDOn, to formalise such semi-structured biological diagrams availing also of a foundational ontology for more precise and interoperable subject domain semantics. The approach is illustrated using Pathway Studio as case study