Suggested Pre-Meeting Reading Spring 2014

Suggested Pre-Meeting Reading

If you’d like to learn more about the topics under discussion at the Spring Meeting, the following literature may be of interest:

Patel, H.; Bodkin, M. J.; Chen, B.; Gillet, V. J., Knowledge-Based Approach to de Novo Design Using Reaction Vectors. J. Chem. Inf. Model. 2009, 49 (5), 1163-1184.

Soh, S.; Wei, Y.; Kowalczyk, B.; Gothard, C. M.; Baytekin, B.; Gothard, N.; Grzybowski, B. A., Estimating Chemical Reactivity and Cross-influence from Collective Chemical Knowledge. Chem. Sci. 2012, 3 (5), 1497-1502.

Berthold, M.; Cebron, N.; Dill, F.; Gabriel, T.; Kötter, T.; Meinl, T.; Ohl, P.; Sieb, C.; Thiel, K.; Wiswedel, B., KNIME: The Konstanz Information Miner. In Data Analysis, Machine Learning and Applications, Preisach, C.; Burkhardt, H.; Schmidt-Thieme, L.; Decker, R., Eds. Springer Berlin Heidelberg: 2008; pp 319-326

Herrgård, M. J. et mult al. (2008). A consensus yeast metabolic network obtained from a community approach to systems biology. Nature Biotechnol. 26, 1155-1160.

Thiele I et mult. al.: A community-driven global reconstruction of human metabolism. Nature Biotechnol 2013; 31:419-425.

Swainston N, Mendes P, Kell DB: An analysis of a ‘community-driven’ reconstruction of the human metabolic network. Metabolomics 2013; 9:757-764.

Kell DB (2013) Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening, and knowledge of transporters: where drug discovery went wrong and how to fix it. FEBS J 280, 5957-5980.

Kell DB & Goodacre R (2014) Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery. Drug Disc Today, online.

Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease, Cell, 153, Issue 3, , Pages 707–720 (2013) http://dx.doi.org/10.1016/j.cell.2013.03.030

The Psychiatric GWAS Consortium: Big Science Comes to Psychiatry – Neuron. Oct 21, 2010; 68(2): 182–186. http://dx.doi.org/10.1016%2Fj.neuron.2010.10.003

In Silico Target Predictions: Comparing Multiclass Naïve Bayes and Parzen-Rosenblatt Window and the Definition of a Benchmarking Dataset for Target Prediction. J Chem Inf Model 2013, 53, 1957–1966.

Cronin MTD, Madden JC, Richarz A-N (2012) The COSMOS Project: A Foundation for the Future of Computational Modelling of Repeat Dose Toxicity. http://alttox.org/ttrc/toxicity-tests/repeated-dose/way-forward/cronin/