To transform undergraduate biology education, faculty need to provide opportunities for students to engage in the process of science. The rise of research approaches using next-generation (NextGen) sequencing has been impressive, but incorporation of such approaches into the undergraduate curriculum remains a major challenge. In this paper, we report proceedings of a National Science Foundation–funded workshop held July 11–14, 2011, at Juniata College. The purpose of the workshop was to develop a regional research coordination network for undergraduate biology education (RCN/UBE). The network is collaborating with a genome-sequencing core facility located at Pennsylvania State University (University Park) to enable undergraduate students and faculty at small colleges to access state-of-the-art sequencing technology. We aim to create a database of references, protocols, and raw data related to NextGen sequencing, and to find innovative ways to reduce costs related to sequencing and bioinformatics analysis. It was agreed that our regional network for NextGen sequencing could operate more effectively if it were partnered with the Genome Consortium for Active Teaching (GCAT) as a new arm of that consortium, entitled GCAT-SEEK(quence). This step would also permit the approach to be replicated elsewhere.

Bacterial type III secretion systems (T3SSs) deliver proteins called effectors into eukaryotic cells. Although N-terminal amino acid sequences are required for translocation, the mechanism of substrate recognition by the T3SS is unknown. Almost all actively deployed T3SS substrates in the plant pathogen Pseudomonas syringae pathovar tomato strain DC3000 possess characteristic patterns, including (i) greater than 10% serine within the first 50 amino acids, (ii) an aliphatic residue or proline at position 3 or 4, and (iii) a lack of acidic amino acids within the first 12 residues. Here, the functional significance of the P. syringae T3SS substrate compositional patterns was tested. A mutant AvrPto effector protein lacking all three patterns was secreted into culture and translocated into plant cells, suggesting that the compositional characteristics are not absolutely required for T3SS targeting and that other recognition mechanisms exist. To further analyze the unique properties of T3SS targeting signals, we developed a computational algorithm called TEREE (Type III Effector Relative Entropy Evaluation) that distinguishes DC3000 T3SS substrates from other proteins with a high sensitivity and specificity. Although TEREE did not efficiently identify T3SS substrates in Salmonella enterica, it was effective in another P. syringae strain and Ralstonia solanacearum. Thus, the TEREE algorithm may be a useful tool for identifying new effector genes in plant pathogens. The nature of T3SS targeting signals was additionally investigated by analyzing the N-terminus of FtsX, a putative membrane protein that was classified as a T3SS substrate by TEREE. Although the first 50 amino acids of FtsX were unable to target a reporter protein to the T3SS, an AvrPto protein substituted with the first 12 amino acids of FtsX was translocated into plant cells. These results show that the T3SS targeting signals are highly mutable and that secretion may be directed by multiple features of substrates.

To analyse primary haemostasis in the zebra-®sh we have identi®ed and characterized the zebra®sh thrombocyte by morphologic, immunologic and functional approaches. Novel methods were developed for harvesting zebra®sh blood with preservation of thrombocytes, and assaying whole blood adhesion/aggregation responses in microtitre plates. Light and electron microscopy of the thrombocyte illustrated morphological characteristics including the formation of aggregates, pseudopodia, and surface-connected vesicles analagous to the platelet canali-cular system. Immunostaining with polyclonal antisera versus human platelet glycoproteins demonstrated the presence of glycoprotein Ib and IIb/IIIa-like complexes on the thrombocyte surface. Whole blood assays for adhesion/ aggregation and ATP release showed ristocetin-induced adhesion without ATP release, and platelet agonist (collagen, arachidonic acid) induced aggregation with ATP release. Blood harvested from zebra®sh treated with aspirin demonstrated inhibition of arachidonic acid induced aggregation and agonist induced ATP release, consistent with at least partial dependence on an intact cyclo oxygenase pathway. The combined morphologic immunologic and functional evidence suggest that the zebra®sh thrombocyte is the haemostatic homologue of the mammalian platelet. Conservation of major haemostatic pathways involved in platelet function and coagulation suggests that the zebra®sh is a relevant model for mammalian haemostasis and thrombosis.

<p>This study compares the forecasting accuracy in stock price prediction of two<br />widely established models - a more traditional autoregressive integrated<br />moving average (ARIMA) model and a deep learning network, the long shortterm memory (LSTM) model. They perform exceptionally well in time series data analysis and are applied to ten different stock tickers, comprising exchange-traded funds (ETFs) from different market sectors for the purpose of this study. The parameters in both models were optimised and this process revealed several differences from existing literature with regards to the optimal combination of parameters in both models. Upon comparing their performances, despite being more accurate when making point predictions, the ARIMA was outperformed significantly by LSTMs in terms of long-term predictions. Point predictions made by ARIMA were found to have similar accuracies as the long-run predictions made by LSTMs.</p>

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