In silico prediction of peptide-MHC binding affinity using SVRMHC

The binding between peptide epitopes and major histocompatibility complex (MHC) proteins is a major event in the cellular immune response. Accurate prediction of the binding between short peptides and class I or class II MHC molecules is an important task in immunoinformatics. SVRMHC which is a novel method to model peptide-MHC binding affinities based on support rector machine regression (SVR) is described in this chapter. SVRMHC is among a small handful of quantitative modeling methods that make predictions about precise binding affinities between a peptide and an MHC molecule. As a kernel-based learning method, SVRMHC has rendered models with demonstrated appealing performance in the practice of modeling peptide-MHC binding.

On plagiarism, patchwriting and the problems of overseas students in British universities

Although according to Angélil-Carter (2002: 2) ‘plagiarism is a modern Western concept which arose with the introduction of copyright laws in the Eighteenth century’, its avoidance is now a basic plank of respectable academic scholarship. Student plagiarism is currently a hot topic, at least for those who teach and study in British and American universities. There are companies selling both off-the-shelf and written-to-order term papers and others, like Turnitin.com, offering an electronic detection service. Recently an Australian Rector was dismissed for persistent plagiarism earlier in his career and most Anglo-American universities have warnings against and definitions of plagiarism on their websites – indeed Pennycook notes that in the mid-90s Stanford University's documents about plagiarism were reproduced by the University of Oregon apparently without attribution, and suggests, whimsically, that there is 'one set of standards for the guardians of truth and knowledge and another for those seeking entry' (1996: 213), (example and quote taken from Pecorari, 2002, p 29).