Addressing the unmet need for visualizing conditional random fields in biological data.

BACKGROUND: The biological world is replete with phenomena that appear to be ideally modeled and analyzed by one archetypal statistical framework - the Graphical Probabilistic Model (GPM). The structure of GPMs is a uniquely good match for biological problems that range from aligning sequences to modeling the genome-to-phenome relationship. The fundamental questions that GPMs address involve making decisions based on a complex web of interacting factors. Unfortunately, while GPMs ideally fit many questions in biology, they are not an easy solution to apply. Building a GPM is not a simple task for an end user. Moreover, applying GPMs is also impeded by the insidious fact that the "complex web of interacting factors" inherent to a problem might be easy to define and also intractable to compute upon. DISCUSSION: We propose that the visualization sciences can contribute to many domains of the bio-sciences, by developing tools to address archetypal representation and user interaction issues in GPMs, and in particular a variety of GPM called a Conditional Random Field(CRF). CRFs bring additional power, and additional complexity, because the CRF dependency network can be conditioned on the query data. CONCLUSIONS: In this manuscript we examine the shared features of several biological problems that are amenable to modeling with CRFs, highlight the challenges that existing visualization and visual analytics paradigms induce for these data, and document an experimental solution called StickWRLD which, while leaving room for improvement, has been successfully applied in several biological research projects. Software and tutorials are available at http://www.stickwrld.org/.

Calmodulin interacts with and regulates the RNA-binding activity of an Arabidopsis polyadenylation factor subunit.

The Arabidopsis (Arabidopsis thaliana) gene that encodes the probable ortholog of the 30-kD subunit of the mammalian cleavage and polyadenylation specificity factor (CPSF) is a complex one, encoding small (approximately 28 kD) and large (approximately 68 kD) polypeptides. The small polypeptide (AtCPSF30) corresponds to CPSF30 and is the focus of this study. Recombinant AtCPSF30 was purified from Escherichia coli and found to possess RNA-binding activity. Mutational analysis indicated that an evolutionarily conserved central core of AtCPSF30 is involved in RNA binding, but that RNA binding also requires a short sequence adjacent to the N terminus of the central core. AtCPSF30 was found to bind calmodulin, and calmodulin inhibited the RNA-binding activity of the protein in a calcium-dependent manner. Mutational analysis showed that a small part of the protein, again adjacent to the N terminus of the conserved core, is responsible for calmodulin binding; point mutations in this region abolished both binding to and inhibition of RNA binding by calmodulin. Interestingly, AtCPSF30 was capable of self-interactions. This property also mapped to the central conserved core of the protein. However, calmodulin had no discernible effect on the self-association. These results show that the central portion of AtCPSF30 is involved in a number of important functions, and they raise interesting possibilities for both the interplay between splicing and polyadenylation and the regulation of these processes by stimuli that act through calmodulin.