Prediction and Testing of Biological Networks Underlying Intestinal Cancer

Colorectal cancer progresses through an accumulation of somatic mutations, some of which reside in so-called “driver” genes that provide a growth advantage to the tumor. To identify points of intersection between driver gene pathways, we implemented a network analysis framework using protein interactions to predict likely connections – both precedented and novel – between key driver genes in cancer. We applied the framework to find significant connections between two genes, Apc and Cdkn1a (p21), known to be synergistic in tumorigenesis in mouse models. We then assessed the functional coherence of the resulting Apc-Cdkn1a network by engineering in vivo single node perturbations of the network: mouse models mutated individually at Apc (Apc1638N+/−) or Cdkn1a (Cdkn1a−/−), followed by measurements of protein and gene expression changes in intestinal epithelial tissue. We hypothesized that if the predicted network is biologically coherent (functional), then the predicted nodes should associate more specifically with dysregulated genes and proteins than stochastically selected genes and proteins. The predicted Apc-Cdkn1a network was significantly perturbed at the mRNA-level by both single gene knockouts, and the predictions were also strongly supported based on physical proximity and mRNA coexpression of proteomic targets. These results support the functional coherence of the proposed Apc-Cdkn1a network and also demonstrate how network-based predictions can be statistically tested using high-throughput biological data

P3HT-Based Solar Cells: Structural Properties and Photovoltaic Performance

Each year we are bombarded with B.Sc. and Ph.D. applications from students that want to improve the world. They have learned that their future depends on changing the type of fuel we use and that solar energy is our future. The hope and energy of these young people will transform future energy technologies, but it will not happen quickly. Organic photovoltaic devices are easy to sketch, but the materials, processing steps, and ways of measuring the properties of the materials are very complicated. It is not trivial to make a systematic measurement that will change the way other research groups think or practice. In approaching this chapter, we thought about what a new researcher would need to know about organic photovoltaic devices and materials in order to have a good start in the subject. Then, we simplified that to focus on what a new researcher would need to know about poly-3-hexylthiophene:phenyl-C61-butyric acid methyl ester blends (P3HT: PCBM) to make research progress with these materials. This chapter is by no means authoritative or a compendium of all things on P3HT:PCBM. We have selected to explain how the sample fabrication techniques lead to control of morphology and structural features and how these morphological features have specific optical and electronic consequences for organic photovoltaic device applications