The gene normalization task in BioCreative III

BACKGROUND: We report the Gene Normalization (GN) challenge in BioCreative III where participating teams were asked to return a ranked list of identifiers of the genes detected in full-text articles. For training, 32 fully and 500 partially annotated articles were prepared. A total of 507 articles were selected as the test set. Due to the high annotation cost, it was not feasible to obtain gold-standard human annotations for all test articles. Instead, we developed an Expectation Maximization (EM) algorithm approach for choosing a small number of test articles for manual annotation that were most capable of differentiating team performance. Moreover, the same algorithm was subsequently used for inferring ground truth based solely on team submissions. We report team performance on both gold standard and inferred ground truth using a newly proposed metric called Threshold Average Precision (TAP-k). RESULTS: We received a total of 37 runs from 14 different teams for the task. When evaluated using the gold-standard annotations of the 50 articles, the highest TAP-k scores were 0.3297 (k=5), 0.3538 (k=10), and 0.3535 (k=20), respectively. Higher TAP-k scores of 0.4916 (k=5, 10, 20) were observed when evaluated using the inferred ground truth over the full test set. When combining team results using machine learning, the best composite system achieved TAP-k scores of 0.3707 (k=5), 0.4311 (k=10), and 0.4477 (k=20) on the gold standard, representing improvements of 12.4%, 21.8%, and 26.6% over the best team results, respectively. CONCLUSIONS: By using full text and being species non-specific, the GN task in BioCreative III has moved closer to a real literature curation task than similar tasks in the past and presents additional challenges for the text mining community, as revealed in the overall team results. By evaluating teams using the gold standard, we show that the EM algorithm allows team submissions to be differentiated while keeping the manual annotation effort feasible. Using the inferred ground truth we show measures of comparative performance between teams. Finally, by comparing team rankings on gold standard vs. inferred ground truth, we further demonstrate that the inferred ground truth is as effective as the gold standard for detecting good team performance

The use of robots and computers in the organisation of studies on the circadian variation of beta 2-adrenoceptor sites in peripheral mononuclear leucocytes

We have developed a partially automated method for the performance of equilibrium radioligand binding studies which is applied by our group in investigations on circadian variations and stimulation studies on beta 2-adrenoceptor sites in human peripheral mononuclear leucocytes (pMNL). Using a Tecan Robotic Sample Processor, binding assays with 12 concentrations of 125iodocyanopindolol (1-150 pmol/l, total binding in triplicates, unspecific binding in the presence of 10(-5) mol/l timolol in duplicates) are prepared automatically with all titer tubes per experiment arranged in a microtiterplate-sized rack. After incubation in a waterbath for 2hr at 37 degrees C, the whole rack is centrifuged at 5000g and transferred back to the lab robot. Bound radioactivity is separated from the unbound ligand by removing the supernatant by the machine. The radioactive counts are evaluated using personal computers. The lab robot enhances reproducibility of experimental results and frees lab workers from time-consuming pipetting jobs. Radioactive exposure is minimized to the time preparing the radioligand working solution and transferring the sample tubes from the robot to the waterbath, to the centrifuge and back to the robot. The variability of our software allows easy adaptation to other binding studies with intact cells

Ko-Kultivierung von Osteoblasten und Osteoklasten unter Einfluss mechanischer Stimuli

J. Matthews' Gallopers - G102 - photographed 1932. Photograph numbered 557