When Process Mining Meets Bioinformatics

Text mining meets workflow: linking U-Compare with Taverna

UNLABELLED Text mining from the biomedical literature is of increasing importance, yet it is not easy for the bioinformatics community to create and run text mining workflows due to the lack of accessibility and interoperability of the text mining resources. The U-Compare system provides a wide range of bio text mining resources in a highly interoperable workflow environment where workflows can...

Bioinformatics meets data mining: time to dance?

Using Emerging Pattern Based Projected Clustering and Gene Expression Data for Cancer Detection

Using gene expression data for cancer detection is one of the famous research topics in bioinformatics. Theoretically, gene expression data is capable to detect all types of early cancer development in molecular level. Traditional clustering and pattern mining algorithm are either inadequate to handle high dimensional gene expression data effectively or the results obtained are not easy to unde...

Introduction to Domain Driven Data Mining

The mainstream data mining faces critical challenges and lacks of soft power in solving real-world complex problems when deployed. Following the paradigm shift from ‘data mining’ to ‘knowledge discovery’, we believe much more thorough efforts are essential for promoting the wide acceptance and employment of knowledge discovery in real-world smart decision making. To this end, we expect a new pa...

Integrating Biomedical Text Mining Services into a Distributed Workflow Environment

Workflows are useful ways to support scientific researchers in carrying out repetitive analytical tasks on digital information. Web services can provide a useful implementation mechanism for workflows, particularly when they are distributed, i.e., where some of the data or processing resources are remote from the scientist initiating the workflow. While many scientific workflows primarily invol...