TASK DEFINITION: In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.
PROBLEM: Background: We present here the recent update of AMS algorithm for identification of post-translational modification (PTM) sites in proteins based only on sequence information, using artificial neural network (ANN) method. The query protein sequence is dissected into overlapping short sequence segments. Ten different physicochemical features describe each amino acid; therefore nine residues long segment is represented as a point in a 90 dimensional space. The database of sequence segments with confirmed by experiments post-translational modification sites are used for training a set of ANNs. The efficiency of the classification for each type of modification and the prediction power of the method is estimated here using recall (sensitivity), precision values, the area under receiver operating characteristic (ROC) curves and leave-one-out tests (LOOCV). The significant differences in the performance for differently optimized neural networks are observed, yet the AMS 3.0 tool integrates those heterogeneous classification schemes into the single consensus scheme, and it is able to boost the precision and recall values independent of a PTM type in comparison with the currently available state-of-the art methods. The standalone version of AMS 3.0 presents an efficient way to indentify post-translational modifications for whole proteomes. The training datasets, precompiled binaries for AMS 3.0 tool and the source code are available at Additional file 1 Supplementary materials for the publication. Supplementary.xls contains detailed results of training and testing of AMS 3.0 tool in MS Excel file format. Additional file 2 PTM predictor software with training data. PTM_Archive.tar.gz includes the predictor software binaries together with all trained ANNs in tar.gz compressed form.

SOLUTION: AMS 3.0: prediction of post-translational modifications

PROBLEM: Although the majority of cases of Legionnaires' disease (LD) are caused by Legionella pneumophila, an increasing number of other Legionella species have been reported to cause human disease. There are no clinical presentations unique to LD and hence accurate laboratory tests are required for early diagnosis. Therefore, we designed a real-time PCR assay that targets the 23S-5S rRNA intergenic spacer region (23S-5S PCR) and allows for detection of all Legionella species and discrimination of L. pneumophila from other Legionella species. In total, 271 isolates representing 50 Legionella species were tested and the assay was validated using 39 culture-positive and 110 culture-negative patient specimens collected between 1989 and 2006. PCR-positive results were obtained with all 39 culture-positive samples (100% sensitivity). Specimens that tested positive according to 23S-5S PCR, but were culture-negative, were further analysed by DNA sequencing of the amplicon or the macrophage infectivity potentiator (mip) gene. In addition to L. pneumophila, Legionella longbeachae, Legionella cincinnatiensis and Legionella micdadei were identified in the specimens. The assay showed a 7-log dynamic range displaying a sensitivity of 7.5 CFU/mL or three genome equivalents per reaction. Sixty-one specimens containing viruses or bacteria other than Legionellae were negative according to 23S-5S PCR, demonstrating its specificity. Use of this assay should contribute to the earlier detection of respiratory disease caused by Legionella species, as well as to increased rates of detection.

SOLUTION: Dual detection of Legionella pneumophila and Legionella species by real-time PCR targeting the 23S-5S rRNA gene spacer region

PROBLEM: The use of viral-mediated gene transfer in animal behavioral experiments has become very popular over the last decade. Altering gene regulation and assessing subsequent behavior can be a useful tool in unraveling a specifi c gene's contributions to complex behavioral processes such as depressive-like behavior. However, these types of experiments require detailed planning and designs to avoid pitfalls associated with issues such as surgical procedure or the peak of viral expression. This chapter is intended to be a primer on the design of such experiments and aims to discuss factors that must be considered in the early phases of experimental planning.

SOLUTION:
Using Viral-Mediated Gene Transfer to Study Depressive-Like Behavior