Recent developments in chemoinformatics education

Chemoinformatics techniques are increasingly being used to analyse the huge volumes of chemical and biological data resulting from combinatorial synthesis and high-throughput screening programmes. Scientists with both the chemical and the computing skills required to carry out such analyses are currently in very short supply, this resulting in the establishment of MSc programmes for the training of chemoinformatics specialists

Surface Diffusion and Islanding in Semiconductor Heterostructures

Molecular beam epitaxy (MBE) is an important technique for the creation of new, non-equilibrium semiconductor materials and structures exhibiting novel physical phenomena. Surface diffusion plays an important role in the growth of these structures, influencing such fundamental growth processes and constants as islanding, critical thickness and epitaxial temperatures. Two approaches to the general problem of surface diffusion and islanding, using the SiGe system as a prototypical semiconductor heterostructure, are discussed: The time evolution of patterned deposits, and kinetic studies of nucleation and growth. While disordered laminar growth occurs for deposition at 300 K, elevated temperatures lead to Stranski-Krastanow (SK) growth (uniform coverage SK with excess Ge in islands). Diffusion coefficients for Ge on Si(100) have been determined for coverages below SK and show a significant coverage dependence. They are extremely sensitive to contamination with carbon on the order of ≈0.05 ML, as well as to e-beam irradiation. In situ annealing experiments were performed to study the islanding process in real time. Provided the initial coverage exceeds the thickness of the SK layer, SK ≈3 ML on Si(100)2x1, the initially uniform but disordered layer begins to collapse into a SK-type morphology at about 250 °C. At a ramping rate of 0.1 °C/s this process is completed at ≈400 °C. A temperature dependence of the SK-layer thickness has been discovered for the first time. It is in excellent agreement with theoretical predictions

Spatial chemical distance based on atomic property fields

Similarity of compound chemical structures often leads to close pharmacological profiles, including binding to the same protein targets. The opposite, however, is not always true, as distinct chemical scaffolds can exhibit similar pharmacology as well. Therefore, relying on chemical similarity to known binders in search for novel chemicals targeting the same protein artificially narrows down the results and makes lead hopping impossible. In this study we attempt to design a compound similarity/distance measure that better captures structural aspects of their pharmacology and molecular interactions. The measure is based on our recently published method for compound spatial alignment with atomic property fields as a generalized 3D pharmacophoric potential. We optimized contributions of different atomic properties for better discrimination of compound pairs with the same pharmacology from those with different pharmacology using Partial Least Squares regression. Our proposed similarity measure was then tested for its ability to discriminate pharmacologically similar pairs from decoys on a large diverse dataset of 115 protein–ligand complexes. Compared to 2D Tanimoto and Shape Tanimoto approaches, our new approach led to improvement in the area under the receiver operating characteristic curve values in 66 and 58% of domains respectively. The improvement was particularly high for the previously problematic cases (weak performance of the 2D Tanimoto and Shape Tanimoto measures) with original AUC values below 0.8. In fact for these cases we obtained improvement in 86% of domains compare to 2D Tanimoto measure and 85% compare to Shape Tanimoto measure. The proposed spatial chemical distance measure can be used in virtual ligand screening

Similarity Methods in Chemoinformatics

promoting access to White Rose research paper

Building New Connections to Old Memories: Accessing Northern Appalachian History through Digital Storytelling in the College Writing Classroom

In fall 2013 my honors writing students at California University of Pennsylvania collaborated with the Heinz History Center in Pittsburgh to create digital storytelling projects for five local historical societies. Through the History Center’s Affiliates Program (HCAP), my students set out to document stories that are meaningful to northern Appalachians, specifically southwestern Pennsylvanians. My students began the semester by creating individual digital stories that helped them situate themselves in the Appalachian region. Later, they formed small groups and chose five local historical societies with which to work with the broad goal of creating digital stories from archival material to encourage visitors to the centers. The semester culminated with the premiere of each story at the designated society with local citizens and dignitaries present. My presentation will discuss the theory and methodology behind using digital storytelling in the honors writing classroom. I will also showcase student work and explore the pitfalls and successes of this pilot project. My presentation will conclude with implications for use by others