Elementary approach towards Biological Data Mining
In this paper we provide an overview on interactive and integrative knowledge discovery and data mining. The most important challenges, includes the need to develop and apply novel methods, algorithms and tools for the integration, fusion, pre processing, mapping, analysis and interpretation of complex biomedical data with the aim to identify testable hypotheses, and build realistic models. The HCI KDD approach, which is a synergistic combination of methodologies and approaches of two areas, Human–Computer Interaction HCI and Knowledge Discovery and Data Mining KDD , offer ideal conditions towards solving these challenges with the goal of supporting human intelligence with machine intelligence. There is an urgent need for integrative and interactive machine learning solutions, because no medical doctor or biomedical researcher can keep pace today with the increasingly large and complex data sets – often called “Big Data”. The application of data mining in the domain of bioinformatics is explained. It also highlights some of the current challenges and opportunities of data mining in bioinformatics.
Data Mining, HCI and KDD Human Computer Interaction, Knowledge Discovery and Data Mining , Big Data, Interactive Knowledge discovery.