Estimation and modelling problems as they arise in many data analysis areas often turn out to be unstable and/or intractable by standard numerical methods. Such problems frequently...
The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high ...
We introduce StarFlow, a script-centric environment for data analysis. StarFlow has four main features: (1) extraction of control and data-flow dependencies through a novel combina...
Applying Cloud computing techniques for analyzing large data sets has shown promise in many data-driven scientific applications. Our approach presented here is to use Cloud comput...
Kalpa Gunaratna, Paul Anderson, Ajith Ranabahu, Am...
Data-driven knowledge discovery is becoming a new trend in various scientific fields. In light of this, the goal of the present paper is to introduce a novel framework to study one...
Chen Yu, Thomas G. Smith, Shohei Hidaka, Matthias ...
This paper describes our research effort to employ Grid technologies to enable the development of geoscience applications by integrating workflow technologies with data mining r...
Gianluigi Folino, Agostino Forestiero, Giuseppe Pa...
The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. A major drawback of the SOM has been the lack of a theoretically justified criterion for model se...
Graphical representation may provide effective means of making sense of the complexity and sheer volume of data produced by DNA microarray experiments that monitor the expression p...
ct 10 The field of gene expression data analysis has grown in the past few years from being purely data-centric to integrative, aiming at 11 complementing microarray analysis with...
Visualization can largely improve biomedical data analysis. It plays a crucial role in explorative data analysis and may support various data mining tasks. The paper presents Free...