Visual Analytics for Biological Data

Final submissions due: 21 July 2013
Publication date: March/April 2014

The emergence of pre-eminent systems approaches in biological and life-sciences creates enormous challenges for computational visualization techniques to enable researchers to gain insight from their large, highly complex, and multiple data sets.

The special issue of IEEE Computer Graphics & Applications on Visual Analytics for Biological Data seeks contributions that describe applications of visual analytics techniques to yield viable results that are biologically relevant and significant. We welcome case studies that were greatly facilitated or could not have been completed in the absence of visual analytics techniques. Existing, modified, or new analytical and visualization techniques can be applied to verify prevailing or novel hypotheses or to allow for discovery of new facts and hypotheses as manifest in the data. Ideally, the submitted case studies should be conducted by teams of researchers from the visualization and bioinformatics or biology communities.

We are looking for contributions ranging from data on organization, form, and function of phenotypes that may come from a multitude of scales ranging from molecular and subcellular, to cell, tissue, organism and populations thereof. Similarly, contributions that visualize and analyze genomic alterations and explain associations between genotypes and phenotypes (for example, eQTL studies, GWAS) are welcome. It is important that the submissions have a narrative that highlights utility in terms of successful, biologically-relevant results. Suggested case studies include, but are not limited to:

- genome and sequence data, including genomic variation data,
- multivariate omics data (transcriptomics, proteomics, metabolomics, and so on),
- biological networks (protein-protein interactions, co-expression, and so on) and pathways,
- structures (for example, protein or RNA structures) and their relationship to function,
- association studies in the clinic and the laboratory (eQTL, GWAS),
- visualization in neurobiology and developmental biology,
- integration of visualization in biological workflows or collaborative processes,
- visualization and visual analytics of integrated biological data sets (for example, image and omics data) for purposes of biomarkers, and subtyping, and so on,
- creative visual-analysis of publicly available datasets (for example, The Cancer Genome Atlas, Allen Brain Atlas, and son on) and privately curated datasets, and
- creation and visualization of ontologies, biological atlases and metadata.

Questions?
Please direct any correspondence before submission to the guest editors:

Carsten Görg, University of Colorado, Carsten.Goerg@ucdenver.edu
Raghu Machiraju, The Ohio State University, machiraju.1@osu.edu
Arthur Olson, Scripps Institute, olson@scripps.edu

Submission Guidelines
Articles should be no more than eight magazine pages, where a page is 800 words and a quarter-page image counts as 200 words. Please cite only the 12 most relevant references, and consider providing (technical) background information in sidebars for nonexpert readers. Color images are preferable and should be limited to a total of 10. Visit the CG&A style and length guidelines at www.computer.org/portal/web/peerreviewmagazines/cga.

We also strongly encourage you to submit multimedia (videos etc.) to enhance your article. Visit CG&A supplemental guidelines at www.computer.org/portal/web/peerreviewmagazines/accga#supplemental

Please submit your paper using the online manuscript submission service at https://mc.manuscriptcentral.com/cs-ieee. When uploading your paper, select the appropriate special-issue title under the category "Manuscript Type." Also, include complete contact information for all authors. If you have any questions about submitting your article, contact the peer review coordinator at cga-ma@computer.org.