Recent trends in knowledge and data integration for the life sciences

Abstract

Abstract:The bioscience field has seen some spectacular advances in genomic and proteomic technologies that are able to deliver vast quantities of information on cellular activity. Such technologies are of critical importance to biology, medical science and in drug discovery. However, living systems are highly complex and to fully exploit these technologies requires knowledge at many different levels. Information such as genome sequence data, gene expression data, protein-to-protein interactions and metabolic pathways is required to understand the complexity of biological processes. The challenge for bioinformatics is to tackle the problem of fragmentation of knowledge by integrating the many sources of heterogeneous information into a coherent entity. Another problem is that the high level of biological complexity and the fragmented nature of biological research has meant that it is difficult to keep fully conversant with the latest research and discoveries. Progress in one area of biology may have implications for other areas but the dissemination of this knowledge is not straightforward; difficulties such as differences in naming conventions for genes and biological processes has led to confusion and the lack of productivity. This paper reviews the most recent research to overcome the fragmentation problem where technologies such as text mining and ontologies are used within the knowledge discovery process and the specific technical challenges they address.

Auto-Extraction, Representation and Integration of a Diabetes Ontology Using Bayesian Networks

“…Ontologies are experiencing increased interest as they are perceived by many as a mechanism for the unification of biology [7]. Within this framework the Bayesian approach can be seen as both a learning mechanism and as a knowledge representation technique [8].…”

“…The use of ontologies in biology for the semantic integration of heterogeneous data is receiving increased attention, however problems occur because of the dynamic, changing nature of biological knowledge [7]. These difficulties arise from the highly complex structures that are expensive and problematic to update and maintain [3].…”

Techniques for integrating -omics data

“…Such information resources are of censorious importance to modern biology, medical science and in drug discovery [1]. Data obtained from completed and ongoing projects of ’omes‘ is now widely available over the internet.…”

Identifying Emerging Trends of Financial Business Method Patents

“…Text mining is a knowledge discovery technology that enables researchers to discern patterns and trends based on unstructured text. It is possible to extract hidden knowledge using approaches such as natural language analysis, information retrieval, information extraction, and data mining [17,[39][40][41][42][43][44][45][46]. Patent documents contain lengthy and rich explanations in technical and legal terminologies [47,48].…”