Making sense of microarray data distributions

Making sense of microarray data distributions

MOTIVATION Typical analysis of microarray data has focused on spot by spot comparisons within a single organism. Less analysis has been done on the comparison of the entire distribution of spot intensities between experiments and between organisms. RESULTS Here we show that mRNA transcription data from a wide range of organisms and measured with a range of experimental platforms show close ag...

Making Sense of Big Data.

Hadoop is currently the large-scale data analysis “hammer” of choice, but there exist classes of algorithms thataren’t “nails” in the sense that they are not particularly amenable to the MapReduce programming model. Toaddress this, researchers have proposed MapReduce extensions or alternative programming models in which thesealgorithms can be elegantly expressed. This article es...

Making sense of big data.

As scientists, each of us faces the question of how best to summarize and display data. This question has become increasingly vexatious, because we now find ourselves in an age of “big data,” where technology has enabled us to measure an ever-increasing volume and variety of variables. Even so, modern attempts to answer this question began as early as the turn of the last century, with the intr...

cDNA Microarray Data Normalization

Data assimilation: making sense of Earth Observation

*Correspondence: William A. Lahoz, INBY, NILU – Norwegian Institute for Air Research, Instituttveien 18, PO Box 100, Kjeller 2027, Norway e-mail: [email protected] Climate change, air quality, and environmental degradation are important societal challenges for the Twenty-first Century. These challenges require an intelligent response from society, which in turn requires access to information about th...