DNA-SDM 2012 - 1st SDM Workshop on Dynamic Network Analysis

In the recent years, rapid advances in technology have led to an exponential growth in data, with billions and trillions of observations being generated constantly in numerous domains such as astronomy, sociology, computer science, biology, chemistry, metabolism and nutrition. It has been observed that real world data from these diverse domains can be modeled as complex networks where nodes represent entities of interest and edges mimic the interactions or relationships among them. Specific examples include, but are not limited to, social networks, co-authorship networks, World Wide Web, metabolic networks, and peer-to-peer networks.

These networks, while diverse in their applications and use, share some common challenges --- community discovery, dynamic nature, modeling for spread and diffusion, link prediction, etc. In the case of large online networks such as Facebook, MySpace and Twitter, Wikipedia, weblogs and community photo and video sharing applications, researchers have recognized the need for community mining, i.e, analysis of linked groups of entities, to identify interesting structural and behavioral properties. In biological networks communities can be mapped to informative structures, such as functional groups of proteins and genes, regulatory modules, and protein complexes. Also, since these networks are typically dynamic in nature, it is crucial to consider the evolutionary aspect of these networks to identify and model key structural and behavioral changes occurring in these networks over time. For biological networks, network dynamics might reveal cellular level responses to changing conditions, including drug treatment, stress, and disease progression. Therefore, studying the dynamics of these networks provides great potential for knowledge discovery.

The 1st SDM Workshop on Dynamic Network Analysis is designed to be a common-themed interdisciplinary workshop that bridges social networks, communication networks, and biological networks. The aim is to attract researchers/practitioners from multiple scientific disciplines into a fruitful discussion about the the state-of-the-art techniques and applications of network analysis in diverse domains. To this end, we expect participation from computational areas such as Data Mining, Machine Learning, Statistics, Applied Mathematics, as well as life sciences and inter-disciplinary fields such as Computational Biology, Biostatistics and Biophysics. It is our expectation that this workshop would present an attractive venue to bring together researchers and practitioners from diverse backgrounds and provide a forum to foster a new cross-disciplinary research community.

Topics of Interest

We solicit high quality papers in the general areas of network analysis including novel computational techniques for network construction, mining and analysis as well as novel applications of these computational tools in diverse disciplines such as Social Sciences, Computer Science, Life Sciences and Biology.
Topics of interest include but are not limited to:

1. Constructing useful information networks from raw datasets

2. Analysis and inferences of structure, behavior and causality from information networks

3. Evolution of patterns and communities in networks

4. Link and trend prediction

5. Time-series Analysis

6. Content-based analysis

7. Analysis of temporal dynamics in networks

8. Data mining and machine learning algorithms for networks

9. Qualitative and quantitative models and metrics

10. Applications of network analysis in Web, social, biological, clinical and computer science

All submitted papers will be peer reviewed. If accepted, at least one of the authors must attend the workshop to present the work. Selected accepted papers will be recommended for submission to special issues of journals.