Paul D. Dobson

TL;DR: Recon 2, a community-driven, consensus 'metabolic reconstruction', is described, which is the most comprehensive representation of human metabolism that is applicable to computational modeling and has improved topological and functional features.

TL;DR: This work describes how it has produced a consensus metabolic network reconstruction for S. cerevisiae, and places special emphasis on referencing molecules to persistent databases or using database-independent forms, such as SMILES or InChI strings, as this permits their chemical structure to be represented unambiguously and in a manner that permits automated reasoning.

TL;DR: It is shown that protein function can be predicted as enzymatic or not without resorting to alignments, and the method is compared to sequence-based methods that also avoid calculating alignments and predict a recently released set of unrelated proteins.

TL;DR: Evidence is discussed supporting the idea that rather than being an exception, carrier-mediated and active uptake of drugs may be more common than is usually assumed and the implications for drug discovery and development are considered.

TL;DR: The combination of accurate mass data for a large collection of metabolites, theoretical isotope abundance data and knowledge of the different ion types detected provided a greater number of electrospray mass spectrometric signals which were putatively identified and with greater confidence in the samples studied.