R3 Terms from literature C Joint term A Rare term R1 R1 Rare term R2 Rare term R3 A R2 Figure 1: Principle behind RaJoLink. Our examination of autism phenomena began with the identiﬁcation of its main concepts and a review of what is already known about autism. We identiﬁed such information by ontology construction, which we found to be a very fast and eﬀective way of describing the contents of large datasets. We used OntoGen [13], the interactive tool for semiautomatic ontology construction. OntoGen is based on machine learning and text mining techniques that automatically extract topics covered within the input documents. Thus, they support the user of the system to organise those documents into a topic ontology. Given that a biological basis to autism is nowadays broadly accepted, we began our autism research by focusing on very basic biochemical and neurological mechanisms. Using the RaJoLink system, approximately 2000 terms were automatically detected in the ﬁrst step, Ra. Each of the terms appeared in only one of the publications from our set of 214. This long list of terms can be time consuming and confusing for further analysis. The RaJoLink ability to ﬁlter by MeSH (medical subject headings) classiﬁcation (by 4 Terms from literature R2 Terms from literature R3 Terms from literature R1 Autism Research and Treatment choosing one or more top- or second-level MeSH categories) turned out to be very beneﬁcial. In our experiments, we considered only the D12 second-level category from the 2008 MeSH tree structure, that is, amino acids, peptides, and proteins because, as mentioned, our research approach has been driven by biochemical mechanisms. Thus, we choose meaningful rare terms belonging to amino acids, peptides, and proteins, which in our experimental case included the terms lactoylglutathione, synaptophysin, and calcium channels. In the next step, Jo, we investigated whether the chosen terms, though rare in autism literature, pointed towards any interesting connections with autism in an indirect, yet logical way. We collated the PubMed abstracts of articles about lactoylglutathione, synaptophysin, and calcium channels into three separate text ﬁles and searched for terms that the three groups had in common. In this way, we singled out joint terms in the literature on the three rare terms. From several joint terms that were found automatically, calcineurin, a protein phosphatase that is widely present in mammalian brains, was chosen for further investigation. 3. Results 3.1. Autism and Calcineurin Relationship. We began the ﬁnal step of our method by retrieving the abstracts of articles on autism as well as articles on calcineurin from the PubMed database. In this step, we found several pairs of PubMed articles that, when put together, could connect the two categories, as shown in Table 1. It should be mentioned that all of the identiﬁed pairs of related publications, displayed in Table 1, proved to be very useful in guiding the discussion towards new ideas for further investigation. Finally, we looked more closely at the signiﬁcance of the fragile X protein loss in autism [14], due to the fact that fragile X syndrome has been found as one of the most recognisable causes for the disorder [15]. This evaluation helped us signiﬁcantly in narrowing down our hypothesis. It encouraged us to further select data on autism and its relation to the fragile X. We found 41 full text articles in PubMed Central, which served as our input ﬁle of data on autism and fragile X. As in the case of our literature mining on pure autism articles, we used this new set of documents from PubMed in the open discovery stage for identiﬁcation of rare terms. In a process similar to the one described previously, we found three interesting rare terms: BDNF (brain-derived neurotrophic factor), bicuculline, and c-Fos. In the next step, we found several promising joint terms in the intersection of the respective three sets of literature. One of these was the term NF-kappaB. 3.2. The Relationship between Autism and NF-kappaB. To test our hypothesis on the connection between autism and NF-kappaB we analysed the combined set of abstracts of 9,365 publications on autism and 30,893 publications on NF- kappaB. We found Bcl-2, cytokines, MCP-1, oxidative stress,