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.

[EX Q]: 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.
[EX A]: AMS 3.0: prediction of post-translational modifications

[EX Q]: The size and diversity of ribosome display libraries depends upon stability of the complex formed between the ribosome, mRNA and translated protein. To investigate if mRNA secondary structure improves stability of the complex, we tested a pseudoknot, originating from the genomic RNA of infectious bronchitis virus (IBV), a member of the positive-stranded coronavirus group. We used the previously-isolated anti-DNA scFv, 3D8, as a target protein. During in vitro translation in rabbit reticulocyte lysate, we observed that incorporation of the pseudoknot into the mRNA resulted in production of a translational intermediate that corresponded to the expected size for ribosomal arrest at the pseudoknot. Complexes containing the mRNA pseudoknot exhibited a higher efficiency of affinity selection than that those without, indicating that the pseudoknot improves stability of the mRNA-ribosome-antibody complex in a eukaryotic translation system. Thus, in order to improve the efficiency of selection, this relatively short pseudoknot sequence could be incorporated into ribosome display.
[EX A]: A pseudoknot improves selection efficiency in ribosome display

[EX Q]: The transfer of scientific data has emerged as a significant challenge, as datasets continue to grow in size and demand for open access sharing increases. Current methods for file transfer do not scale well for large files and can cause long transfer times. In this study we present BioTorrents, a website that allows open access sharing of scientific data and uses the popular BitTorrent peer-to-peer file sharing technology. BioTorrents allows files to be transferred rapidly due to the sharing of bandwidth across multiple institutions and provides more reliable file transfers due to the built-in error checking of the file sharing technology. BioTorrents contains multiple features, including keyword searching, category browsing, RSS feeds, torrent comments, and a discussion forum. BioTorrents is available at http://www.biotorrents.net.
[EX A]:
BioTorrents: A File Sharing Service for Scientific Data