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High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing b

Semantic relation extraction is one of the frontiers of biomedical natural language processing research. Gold standards are key tools for advancing this research. It is challenging to generate these standards because of the high cost of expert time and the difficulty in establishing agreement between annotators. We implemented and evaluated a microtask crowdsourcing approach that can produce a gold standard for extracting drug-disease relations. The aggregated crowd judgment agreed with expert annotations from a pre-existing corpus on 43 of 60 sentences tested. The levels of crowd agreement varied in a similar manner to the levels of agreement among the original expert annotators. This work rein-forces the power of crowdsourcing in the process of assembling gold standards for relation extraction. Further, it high-lights the importance of exposing the levels of agreement between human annotators, expert or crowd, in gold standard corpora as these are reproducible signals indicating ambiguities in the data or in the annotation guidelines., Comment: 4 pages, 3 figures In: Bio-Ontologies SIG, ISMB: 10 July 2015, Dublin

The EU Directive 2010/75/EU, Industrial Emissions Directive (IED), limited the NOx emission level < 200 mg/m3n at 6% O2 content from combustion plants into the air at 2016. For achieving NOx emission limitation, Fortum is developing a new combustion technology which includes new third generation Low-NOx burners and advanced OFA system combining with rich reagent injection (RRI) in to the boiler. The aim of the thesis was to study NOx reduction capability of RRI and the effect of reagent on the combustion system at PC firing Power Plants. Two experiments were performed at Inkoo and Suomenoja Power Plants, in which Inkoo has a single wall firing boiler and Suomenoja has tangentially firing boiler. During the test runs, the urea concentration was 32.5 wt. % and three types' urea spray nozzles were prepared to both Power Plants. Coal samples and fly ash samples were collected and analysed in laboratory to determine the coal quality and UBC content and ammonia content in fly ash. Gypsum samples and waste water samples were collected after FGD unit and analysed in laboratory in order to examine the ammonia content. NOx emission was measured by NOx-analyser before the flue gas fan and FTIR was used to measure the gases concentration after the flue gas fan. According to RRI test results, the NOx reduction was achieved 52 mg/m3n (13.5%) at Inkoo and 98 mg/m3n (21%) at Suomenoja with using C-type urea nozzle. The results indicated that urea injection had no remarkable effect on increasing N2O emission, CO emission and UBC content in fly ash. No ammonia slip was found in fly ash and FGD unit. Urea injection had no negative effect on increasing water spray amount to superheater or reheater and steam temperature. In addition, the tendency of NOx reduction was same for the CFD calculation and tests at Power Plants. Based on the tests results and CFD modelling, optimizing existed combustion systems combined with RRI would achi