High-Performance Algorithms for Mass Spectrometry-Based Omics

High-Performance Algorithms for Mass Spectrometry-Based Omics
Author: Fahad Saeed
Publisher: Springer Nature
Total Pages: 146
Release: 2022-09-02
Genre: Science
ISBN: 3031019601
GET BOOK

To date, processing of high-throughput Mass Spectrometry (MS) data is accomplished using serial algorithms. Developing new methods to process MS data is an active area of research but there is no single strategy that focuses on scalability of MS based methods. Mass spectrometry is a diverse and versatile technology for high-throughput functional characterization of proteins, small molecules and metabolites in complex biological mixtures. In the recent years the technology has rapidly evolved and is now capable of generating increasingly large (multiple tera-bytes per experiment) and complex (multiple species/microbiome/high-dimensional) data sets. This rapid advance in MS instrumentation must be matched by equally fast and rapid evolution of scalable methods developed for analysis of these complex data sets. Ideally, the new methods should leverage the rich heterogeneous computational resources available in a ubiquitous fashion in the form of multicore, manycore, CPU-GPU, CPU-FPGA, and IntelPhi architectures. The absence of these high-performance computing algorithms now hinders scientific advancements for mass spectrometry research. In this book we illustrate the need for high-performance computing algorithms for MS based proteomics, and proteogenomics and showcase our progress in developing these high-performance algorithms.

Application Of Omics, Ai And Blockchain In Bioinformatics Research

Application Of Omics, Ai And Blockchain In Bioinformatics Research
Author: Jeffrey J P Tsai
Publisher: World Scientific
Total Pages: 207
Release: 2019-10-14
Genre: Computers
ISBN: 9811203598
GET BOOK

With the increasing availability of omics data and mounting evidence of the usefulness of computational approaches to tackle multi-level data problems in bioinformatics and biomedical research in this post-genomics era, computational biology has been playing an increasingly important role in paving the way as basis for patient-centric healthcare.Two such areas are: (i) implementing AI algorithms supported by biomedical data would deliver significant benefits/improvements towards the goals of precision medicine (ii) blockchain technology will enable medical doctors to securely and privately build personal healthcare records, and identify the right therapeutic treatments and predict the progression of the diseases.A follow-up in the publication of our book Computation Methods with Applications in Bioinformatics Analysis (2017), topics in this volume include: clinical bioinformatics, omics-based data analysis, Artificial Intelligence (AI), blockchain, big data analytics, drug discovery, RNA-seq analysis, tensor decomposition and Boolean network.

Lipidomics and Bioactive Lipids: Mass Spectrometry Based Lipid Analysis

Lipidomics and Bioactive Lipids: Mass Spectrometry Based Lipid Analysis
Author:
Publisher: Elsevier
Total Pages: 432
Release: 2007-11-26
Genre: Science
ISBN: 0080554881
GET BOOK

This volume in the well-established Methods in Enzymology series features methods for the study of lipids using mass spectrometry techniques. Articles in this volume cover topics such as Qualitative Analysis and Quantitative Assessment of Changes in Neutral Glycerol Lipid Molecular Species within Cells; Glycerophospholipid identification and quantitation by electrospray ionization mass spectrometry; Detection and Quantitation of Eicosanoids via High Performance Liquid Chromatography/Electrospray Ionization Mass Spectrometry; Structure-specific, quantitative methods for "lipidomic" analysis of sphingolipids by tandem mass spectrometry; Analysis of Ubiquinones, Dolichols and Dolichol Diphosphate-Oligosaccharides by Liquid Chromatography Electrospray Ionization Mass Spectrometry; Extraction and Analysis of Sterols in Biological Matrices by High-Performance Liquid Chromatography Electrospray Ionization Mass Spectrometry; The Lipid Maps Initiative in Lipidomics; Basic analytical systems for lipidomics by mass spectrometry in Japan; The European Lipidomics Initiative Enabling technologies; Lipidomic analysis of Signaling Pathways; Bioinformatics for Lipidomics; Mediator Lipidomics: Search Algorithms for Eicosanoids, Resolvins and Protectins; A guide to biochemical systems modeling of sphingolipids for the biochemist; and Quantitation and Standardization of Lipid Internal Standards for Mass Spectroscopy.

Introduction to Parallel Algorithms

Introduction to Parallel Algorithms
Author: C. Xavier
Publisher: John Wiley & Sons
Total Pages: 388
Release: 1998-08-05
Genre: Computers
ISBN: 9780471251828
GET BOOK

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering.

Computational Approaches for Improved Identification, Quantitation, and Interpretation of Mass Spectrometry-based "omics" Data

Computational Approaches for Improved Identification, Quantitation, and Interpretation of Mass Spectrometry-based
Author: Nicholas William Kwiecien
Publisher:
Total Pages: 270
Release: 2016
Genre:
ISBN:
GET BOOK

The research described in this dissertation presents novel computational algorithms and strategies for (1) improving the assignment of molecular identities to analytes profiled by high-resolution gas chromatography-mass spectrometry (GC/MS), (2) performing relative quantitation of large sets of metabolites across expansive sets of mass spectrometry data files, (3) disseminating processed mass spectrometry data and post hoc statistical results in web-based platforms, and (4) monitoring mass spectrometer performance via a web-based data processing and analysis tool. An overview of the aforementioned computational strategies and developed software tools is presented in Chapter 1. A novel algorithm for leveraging accurate mass--afforded by high-resolution GC/MS systems--to discriminate between putative identifications assigned to profiled small molecules is described in Chapter 2. In Chapter 3, an algorithm and accompanying software suite designed to enable untargeted quantitation of small molecules across expansive sets of raw GC/MS data files is described. In Chapter 4, these algorithms are employed as part of a larger study wherein 174 single gene deletion strains of yeast were comprehensively profiled at the proteomic, metabolomic, and lipidomic levels. These multi-omic data were then integrated through various analysis planes in order to define functions of uncharacterized mitochondrial proteins. Chapter 5 details numerous web-based data visualization utilities developed for various projects designed to enable researchers to more rapidly interrogate MS data sets at depth. In Chapter 6, the development of a web-based mass spectrometry data deposition, processing, and visualization tool for automated quality control analysis is described.

High-performance Reductive Strategies for Big Data from LC-MS/MS Proteomics

High-performance Reductive Strategies for Big Data from LC-MS/MS Proteomics
Author: Muaaz Gul Awan
Publisher:
Total Pages: 98
Release: 2019
Genre: Data reduction
ISBN:
GET BOOK

Mass Spectrometry (MS)-based proteomics utilizes high performance liquid chromatography in tandem with high-throughput mass spectrometers. These experiments can produce MS data sets with astonishing speed and volume that can easily reach peta-scale level, creating storage and computational problems for large-scale systems biology studies. Each spectrum output by a mass spectrometer may consist of thousands of peaks, which must all be processed to deduce the corresponding peptide. However, only a small percentage of peaks in a spectrum are useful for further processing, as most of the peaks are either noise or are not useful. Our experiments have shown that 90 to 95% of the peaks are not required for reliable results. This leads to a lot of redundant processing and causes a hindrance to high-throughput processing of big MS data. The existing pre-processing algorithms for noise-removal or spectra-denoising are limited in their data-reduction capability and are compute intensive; in most cases these pre-processing stages create an additional compute bottleneck in the software pipeline for proteomics. One method of attacking this problem would be by developing data-aware algorithms capable of minimizing the amount of redundant computations. Besides, owing to the continuous increase in the speed and size of proteomics data, high-performance computing solutions need to be introduced. In this study we propose a new data reduction algorithm, which exploits the high noise content of MS/MS data to its advantage and uses a weighted-random- sampling technique to reduce the number of computations drastically. Our results have shown a speed gain of over 100x with respect to the existing tools, while giving comparable accuracy on experimental data. To support rapid adoption and development of high-performance computing solutions in proteomics and big data studies in general, we introduce a template-based strategy for development of optimized GPU-based algorithms for omics data. Our proposed template outlines generic methods to tackle critical GPU-centric bottlenecks and provides details of implementing optimized and scalable GPU algorithms for a given big data problem. We demonstrate the application of this template by implementing a GPU version of our proposed data-reduction algorithm as a case-study. This study also explores the methods of benchmarking novel proteomics algorithms and introduces a highly configurable data simulator to generate user-controlled ground-truth data for assessing new algorithms.

Proteome Informatics

Proteome Informatics
Author: Conrad Bessant
Publisher: Royal Society of Chemistry
Total Pages: 429
Release: 2016-11-15
Genre: Science
ISBN: 1782626735
GET BOOK

The field of proteomics has developed rapidly over the past decade nurturing the need for a detailed introduction to the various informatics topics that underpin the main liquid chromatography tandem mass spectrometry (LC-MS/MS) protocols used for protein identification and quantitation. Proteins are a key component of any biological system, and monitoring proteins using LC-MS/MS proteomics is becoming commonplace in a wide range of biological research areas. However, many researchers treat proteomics software tools as a black box, drawing conclusions from the output of such tools without considering the nuances and limitations of the algorithms on which such software is based. This book seeks to address this situation by bringing together world experts to provide clear explanations of the key algorithms, workflows and analysis frameworks, so that users of proteomics data can be confident that they are using appropriate tools in suitable ways.

Comprehensive Foodomics

Comprehensive Foodomics
Author:
Publisher: Elsevier
Total Pages: 2444
Release: 2020-11-12
Genre: Science
ISBN: 0128163968
GET BOOK

Comprehensive Foodomics, Three Volume Set offers a definitive collection of over 150 articles that provide researchers with innovative answers to crucial questions relating to food quality, safety and its vital and complex links to our health. Topics covered include transcriptomics, proteomics, metabolomics, genomics, green foodomics, epigenetics and noncoding RNA, food safety, food bioactivity and health, food quality and traceability, data treatment and systems biology. Logically structured into 10 focused sections, each article is authored by world leading scientists who cover the whole breadth of Omics and related technologies, including the latest advances and applications. By bringing all this information together in an easily navigable reference, food scientists and nutritionists in both academia and industry will find it the perfect, modern day compendium for frequent reference. List of sections and Section Editors: Genomics - Olivia McAuliffe, Dept of Food Biosciences, Moorepark, Fermoy, Co. Cork, Ireland Epigenetics & Noncoding RNA - Juan Cui, Department of Computer Science & Engineering, University of Nebraska-Lincoln, Lincoln, NE Transcriptomics - Robert Henry, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, Australia Proteomics - Jens Brockmeyer, Institute of Biochemistry and Technical Biochemistry, University Stuttgart, Germany Metabolomics - Philippe Schmitt-Kopplin, Research Unit Analytical BioGeoChemistry, Neuherberg, Germany Omics data treatment, System Biology and Foodomics - Carlos Leon Canseco, Visiting Professor, Biomedical Engineering, Universidad Carlos III de Madrid Green Foodomics - Elena Ibanez, Foodomics Lab, CIAL, CSIC, Madrid, Spain Food safety and Foodomics - Djuro Josic, Professor Medicine (Research) Warren Alpert Medical School, Brown University, Providence, RI, USA & Sandra Kraljevic Pavelic, University of Rijeka, Department of Biotechnology, Rijeka, Croatia Food Quality, Traceability and Foodomics - Daniel Cozzolino, Centre for Nutrition and Food Sciences, The University of Queensland, Queensland, Australia Food Bioactivity, Health and Foodomics - Miguel Herrero, Department of Bioactivity and Food Analysis, Foodomics Lab, CIAL, CSIC, Madrid, Spain Brings all relevant foodomics information together in one place, offering readers a ‘one-stop,’ comprehensive resource for access to a wealth of information Includes articles written by academics and practitioners from various fields and regions Provides an ideal resource for students, researchers and professionals who need to find relevant information quickly and easily Includes content from high quality authors from across the globe

Foodomics

Foodomics
Author: Jorge Barros-Velázquez
Publisher: Royal Society of Chemistry
Total Pages: 515
Release: 2021-03-31
Genre: Science
ISBN: 1788018842
GET BOOK

Presents the most updated information on the main methodologies and technological platforms involved in foodomics.