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.
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Question: 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.

Answer: AMS 3.0: prediction of post-translational modifications


Question: Background: Drainage systems and its role in sanitation related outbreaks are evident but still occluded once it has been installed. This current review evaluates if drainage systems can cause infections and thus be of clinical concern. Method: A review of the literature was analyzed. Papers, guidelines, and quality management systems have been considered. Results: Adequate sanitation is fundamental and a prerequisite for safe life and productivity. In contrast, malfunctioning sanitation has been reported to cause outbreaks all over the world. In areas with no sanitation, diarrheal mortality is high and has been shown to decrease by 36% after interventions to improve sanitation. Often, infections are faeces associated and when present in wastewater and sewage sludge poses a high risk of infection upon exposure. Hence, there are working safety guidelines and in industries where infection reduction is essential strict quality assurance systems, i.e. HACCP (hazard analysis critical control points) and GMP (Good Manufacturing Practice) must be complied. Healthcare has recently taken interest in the HACCP system in their efforts to reduce healthcare associated infections as a response to increasing number of ineffective antibiotics and the threat of mortality rate like the pre-antibiotic era. The last few years have called for immediate action to contain the emergence of increasing resistant microorganisms. Resistance is obtained as a result of overuse and misuse of antibiotics in both healthcare and agriculture. Also, by the discharge of antibiotics from manufacturers, healthcare and society. One mechanism of development of novel resistant pathogens has been shown to be by effortless sharing of genetic mobile elements coding for resistance from microbes in the environment to human microbes. These pathogens have been sampled from the drainage systems. These were noticed owing to their possession of an unusual antibiotic resistance profile linking them to the outbreak. Often the cause of sanitation related outbreaks is due to inadequate sanitation and maintenance. However, in general these infections probably go unnoticed. Conclusion: Drainage systems and its maintenance, if neglected, could pose a threat in both community and healthcare causing infections as well as emergence of multi-resistant bacteria that could cause unpredictable clinical manifestations.

Answer: Drainage systems, an occluded source of sanitation related outbreaks


Question: Methods: Using surface-enhanced laser desorption/ionization (SELDI) ProteinChip technology, we profiled and compared serum proteins of 39 patients with earlystage SARS infection and 39 non-SARS patients who were suspected cases during the SARS outbreak period. Proteomic patterns associated with SARS were identified by bioinformatic and biostatistical analyses. Features of interest were then purified and identified by tandem mass spectrometry. Results: Twenty proteomic features were significantly different between the 2 groups. Fifteen were increased in the SARS group, and 5 were decreased. Their concentrations were correlated with 2 or more clinical and/or biochemical variables. Two were correlated with the SARS-CoV viral load. Hierarchical clustering analysis showed that a majority of the SARS patients (95%) had similar serum proteomic profiles and identified 2 subgroups with poor prognosis. ROC curve analysis identified individual features as potential biomarkers for SARS diagnosis (areas under ROC curves, 0.733-0.995). ROC curve areas were largest for an N-terminal fragment of complement C3c ␣ chain (m/z 28 119) and an internal fragment of fibrinogen ␣-E chain (m/z 5908). Conclusions: Specific proteomic fingerprints in the sera of adult SARS patients could be used to identify SARS cases early during onset with high specificity and sensitivity.

Answer:
Serum Proteomic Fingerprints of Adult Patients with Severe Acute Respiratory Syndrome