Machine Learning algorithms are being increasingly used for knowledge discovery tasks. Approaches can be broadly divided by distinguishing discovery of procedural from that of declarative knowledge. Client requirements determine which of these is appropriate. This paper discusses an experimental application of machine learning in an area related to drug design. The bottleneck here is in finding appropriate constraints to reduce the large number of candidate molecules to be synthesisedand tested. Such constraints canbe viewed as declarative specifications of the structural elements necessary for high medicinal activity and low toxicity. The first-order representation used within Inductive Logic Programming (ILP) provides an appropriate description language for such constraints. Within this application area knowledge accreditation requires not only a demonstration of predictive accuracy but also, and crucially, a certification of novel insight into the structural chemistry. Thi...

Industry is increasingly overwhelmed by large-volume-data. For example, the pharmaceutical industry generates vast quantities of data both internally as a side-effect of screening tests and combinatorial chemistry, as well as externally from sources such as the human genome project. Industry is also becoming predominantly knowledgedriven. Increased understanding not only improves products, but is also central in market assessment and strategic decision making. From a computer science point of view, the knowledge requirements within industry often give higher emphasis to "knowing that" (declarative or descriptive knowledge) rather than "knowing how" (procedural or prescriptive knowledge). Mathematical logic has always been the preferred representation for declarative knowledge and thus knowledge discovery techniques are required which generate logical formulae from data. Inductive Logic Programming (ILP) is such a technique. Logic programs provide a powerful and flexible representation ...

Interleukin 4 (IL-4) and IL-13 share many biological functions. Both rtokines promote growth of activated human B cells and induce naive human surface immunoglobulin D+ (sIgD+) B cells to produce IgG4 and IgE. Here we show that a mutant form of human IL-4, in which the tyrosine residue at position 124 is replaced by aspartic acid (hIL-4Y124D), specifically blocks IL-4 and IL-13-induced proliferation ofB cells costimulated by anti-CD40 mAbs in a dose-dependent fashion. A mouse mutant IL-4 protein (mIL-4Y119D), which antagonizes the biological activity of mouse IL-4, was ineffective. In addition, hIL-4Y124D, at concentrations of up to 40 nM, did not affect IL-2-induced B cell proliferation. hIL-4Y124D did not have detectable agonistic activity in these B cell proliferation assays. Interestingly, hIL-4Y124D also strongly inhibited both IL-4 or IL-13-induced IgG4 and IgE synthesis in cultures of peripheral blood mononuclear cells, or highly purified sIgD ` B cells cultured in the presence of anti-CD40 mAbs. IL-4 and IL-13-induced IgE responses were inhibited>95 % at a N50- or-20-fold excess ofhIL-4Y124D, respectively, despite the fact that the IL-4 mutant protein had a weak agonistic activity. This agonistic activity was 1.6 ± 1.9 % (n = 4) of the maximal IgE responses induced by saturating concentrations of IL-4. Taken together, these data indicate that there are commonalities between