Computational mass spectrometry

In this continuity, the potentiality of D. citrea essential oil was subjected to screening research. The extract yield was obtained experimentally and its chemical characterization was acquired by gas chromatography-mass spectrometry (GC-MS). The determined data was subjected as the input for computational implementations, including density functional theory calculation, molecular docking simulation, and biopharma-potential predicting analyses.

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Ebook "Prokaryotic systems biology (Advances in experimental medicine and biology, Volume 883)" focuses on innovative experimental and computational approaches for charting interaction networks in bacterial species.

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Influenza is one of the oldest and deadliest infectious diseases known to man. Reassorted strains of the virus pose the greatest risk to both human and animal health and have been associated with all pandemics of the past century, with the possible exception of the 1918 pandemic, resulting in tens of millions of deaths.

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This is an editorial report of the supplements to BMC Bioinformatics that includes 6 papers selected from the BIOCOMP’19—The 2019 International Conference on Bioinformatics and Computational Biology. These articles reflect current trend and development in bioinformatics research.

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Tandem mass spectrometry-based database searching is currently the main method for protein identification in shotgun proteomics. The explosive growth of protein and peptide databases, which is a result of genome translations, enzymatic digestions, and post-translational modifications (PTMs), is making computational efficiency in database searching a serious challenge.

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Label-free quantitation of mass spectrometric data is one of the simplest and least expensive methods for differential expression profiling of proteins and metabolites. The need for high accuracy and performance computational label-free quantitation methods is still high in the biomarker and drug discovery research field.

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Metabolomics is one of most recent omics technologies. It has been applied on fields such as food science, nutrition, drug discovery and systems biology. For this, gas chromatography-mass spectrometry (GC-MS) has been largely applied and many computational tools have been developed to support the analysis of metabolomics data. Among them, AMDIS is perhaps the most used tool for identifying and quantifying metabolites.

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Mass spectrometry analyses of complex protein samples yield large amounts of data and specific expertise is needed for data analysis, in addition to a dedicated computer infrastructure. Furthermore, the identification of proteins and their specific properties require the use of multiple independent bioinformatics tools and several database search algorithms to process the same datasets.

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Mass spectrometry (MS) is producing high volumes of data supporting oncological sciences, especially for translational research. Most of related elaborations can be carried out by combining existing tools at different levels, but little is currently available for the automation of the fundamental steps.

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Chemical cross-linking combined with mass spectrometry (CX-MS) is a high-throughput approach to studying protein-protein interactions. The number of peptide-peptide combinations grows quadratically with respect to the number of proteins, resulting in a high computational complexity.

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Tracing stable isotopes, such as 13C using various mass spectrometry (MS) methods provides a valuable information necessary for the study of biochemical processes in cells. However, extracting such information requires special care, such as a correction for naturally occurring isotopes, or overlapping mass spectra of various components of the cell culture medium.

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Non-targeted metabolomics based on mass spectrometry enables high-throughput profiling of the metabolites in a biological sample. The large amount of data generated from mass spectrometry requires intensive computational processing for annotation of mass spectra and identification of metabolites.

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Tandem mass spectrometry (MS/MS)-based database searching is a widely acknowledged and widely used method for peptide identification in shotgun proteomics. However, due to the rapid growth of spectra data produced by advanced mass spectrometry and the greatly increased number of modified and digested peptides identified in recent years.

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In themanagement of privacy, organizations focus on two types of threats: Deliberatemisuse of information or theft of information can range from incidents where employees deliberately remove proprietary information, including trade secrets, customer lists, or financial data, and provide that information to unauthorized parties. The second type of internal threat stems from ignorance or carelessness in how proprietary data and information is used.

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This second edition presents new chapters on (a) the utilization of mutants as highresolution nanosensors of short-living protein structures and protein nanophysics (Chap. 11) and (b) the recently developed method of evolutionary computer programming (Chap. 12), respectively. In the latter method, computer programs evolve themselves towards a higher performance. In contrast to simple selflearning programs, the code of the evolved program differs significantly from that of the original "wild-type" program.

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Nowadays it is difficult to imagine an area of knowledge that can continue developing without the use of computers and informatics. It is not different with biology, that has seen an unpredictable growth in recent decades, with the rise of a new discipline, bioinformatics, bringing together molecular biology, biotechnology and information technology.

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