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 Input:
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 Output:
AMS 3.0: prediction of post-translational modifications


Ex Input:
Compared to classical epidemiologic methods, genomics can be used to precisely monitor virus evolution and transmission in real time across large, diverse populations. Integration of pathogen genomics with data about host genetics and global transcriptional responses to infection allows for comprehensive studies of population-level responses to infection and provides novel methods for predicting clinical outcomes. As genomic technologies become more accessible, these methods will redefine how emerging viruses are studied and outbreaks are contained. Here we review the existing and emerging genomic technologies that are enabling systems epidemiology and systems virology and making it possible to respond rapidly to emerging viruses such as Zika.

Ex Output:
Genomic Signatures of Emerging Viruses: A New Era of Systems Epidemiology


Ex Input:
Objective To introduce the emergency management of nursing human resources and material resources of a large general hospitals when facing the outbreak of the coronavirus disease 2019(COVID-19). The Nursing Department of the hospital fully executed its functional authority to establish a three-level echelon of sustainable support, allocate human recourses dynamically, organize pre-service training, supervise the key working steps, formulate positive incentive methods, and deploy medical supplies scientifically. Result By taking these strategies, the hospital effectively improved the coping capacity of the nursing team and played a positive role in the prevention and treatment of COVID-19. The emergency management of nursing human resources and material resources for COVID-19 of the hospital is successful. But several deficiencies were identified as well, which indicated that the hospital needs to establish an efficient emergency management system, and pay attention to the practice of nursing emergency plans to enhance coping capacities in public health emergencies.

Ex Output:

Journal Pre-proof Emergency management of nursing human resources and supplies to respond to coronavirus disease 2019 epidemic Author statement Emergency management of nursing human resources and supplies to respond to coronavirus disease 2019 epidemic