Synthetic microarray data generation with RANGE and NEMO

cDNA Microarray Data Normalization

A Synthetic Kinome Microarray Data Generator

Cellular pathways involve the phosphorylation and dephosphorylation of proteins. Peptide microarrays called kinome arrays facilitate the measurement of the phosphorylation activity of hundreds of proteins in a single experiment. Analyzing the data from kinome microarrays is a multi-step process. Typically, various techniques are possible for a particular step, and it is necessary to compare and...

On Long-range-dependence Synthetic Data Generation through Heavy-tailed Distributions

Comprehensive analysis of the Internet traffic conducted over the last decade revealed the concept of longrange dependence (LRD) in the collected data traces. Some of this analysis work proved that this property is a result of the heavy tailed distribution of the packet inter-arrival time, which is a result of the heavy tailed distribution of packet size of the traffic sources. In this paper, w...

Head Motion Generation with Synthetic Speech: A Data Driven Approach

To have believable head movements for conversational agents (CAs), the natural coupling between speech and head movements needs to be preserved, even when the CA uses synthetic speech. To incorporate the relation between speech head movements, studies have learned these couplings from real recordings, where speech is used to derive head movements. However, relying on recorded speech for every s...

Synthetic generation of social network data with endorsements

In many simulation studies involving networks there is the need to rely on a sample network to perform the simulation experiments. In many cases, real network data is not available due to privacy concerns. In that case we can recourse to synthetic data sets with similar properties to the real data. In this paper we discuss the problem of generating synthetic data sets for a certain kind of onli...