Printer Friendly Printed from http://www.researchandmarkets.com/reports/571326 Computational Methods for Mass Spectrometry Proteomics Description: This book uniquely provides basic knowledge and principles of proteomic bioinformatics and mass spectrometry. Computational Methods for Mass Spectrometry Proteomics covers the bioinformatics problems and how they are solved, which types of programs are used and the different principles / algorithms underlying these programs. A description of the instruments used is also given. The book includes many examples to help make the subject practical and accessible, and is an invaluable resource for all bioinformaticians, students, proteomic researchers, analytical chemists, and computer scientists. Contents: Contents Preface 1 Protein, Proteome, and Proteomics 1.1 Primary goals for studying proteomes 1.2 Defining the protein 1.2.1 Protein identity 1.2.2 Splice variants 1.2.3 Allelic variants - polymorphisms 1.2.4 Posttranslational modifications 1.2.5 Protein isoforms 1.3 Protein properties - attributes and values 1.3.1 The amino acid sequence 1.3.2 Molecular mass 1.3.3 Isoelectric point 1.3.4 Hydrophobicity 1.3.5 Amino acid composition 1.4 Posttranslational modifications 1.5 Protein sequence databases 1.5.1 UniProt KnowledgeBase (Swiss-Prot/TrEMBL, PIR) 1.5.2 The NCBI non-redundant database 1.5.3 The International Protein Index (IPI) 1.5.4 Time-instability of sequence databases 1.6 Identification and characterization of proteins 1.6.1 Top-down and bottom-up proteomics 1.6.2 Protein digestion into peptides 1.7 Two approaches for bottom-up protein analysis by mass spectrometry 1.7.1 MS - Peptide mass fingerprinting 1.7.2 MS/MS - Tandem MS 1.7.3 Combination approaches 1.7.4 Reducing the search space 1.8 Instrument calibration and measuring errors 1.8.1 Calibration 1.8.2 Accuracy and precision 1.9 Exercises 1.10 Bibliographic notes 2 Protein Separation - 2D Gel Electrophoresis 2.1 Separation on molecular mass - SDS-PAGE 2.1.1 Estimating the protein mass 2.2 Separation on isoelectric point - IEF 2.3 Separation on mass and isoelectric point, 2D 2.3.1 Transferring the proteins from the first to the second dimension 2.3.2 Visualizing the proteins after separation 2.3.3 Problems 2.3.4 Excising the proteins 2.4 2D SDS-PAGE for (complete) proteomics 2.4.1 Identifying the proteins 2.4.2 Quantification 2.4.3 Programs for treating and comparing gels 2.4.4 Comparing results from different experiments - DIGE 2.5 Exercises 2.6 Bibliographic notes 3 Protein Digestion 3.1 Experimental digestion 3.1.1 Cleavage specificity 3.1.2 Trypsin 3.1.3 Chymotrypsin 3.1.4 Other considerations for the choice of a protease 3.1.5 Random cleavage 3.1.6 Chemical cleavage 3.1.7 In-gel digestion 3.2 In silico digestion 3.3 Exercises 3.4 Bibliographic notes 4 Peptide Separation - HPLC 4.1 High Pressure Liquid Chromatography - HPLC 4.2 Stationary phases and separation modes 4.2.1 Reverse phase chromatography, RP 4.2.2 Strong cation exchange chromatography, SCX 4.2.3 Other types of chromatography for proteomics 4.2.4 Tandem HPLC 4.3 Component migration and retention time 4.4 The shape of the peaks 4.4.1 The width 4.4.2 Asymmetry 4.4.3 Resolution 4.5 Chromatography used for protein identification 4.5.1 Theoretical calculation of the retention time for reverse phase chromatography 4.6 Chromatography used for quantification 4.7 Exercises 4.8 Bibliographic notes 5 Fundamentals of Mass Spectrometry 5.1 The principle of mass spectrometry 5.2 Ionization sources 5.2.1 MALDI - Matrix Assisted Laser Desorption Ionization 5.2.2 ESI - Electrospray Ionization 5.2.3 Other ionization sources 5.3 Mass analyzers 5.4 Isotopic composition of peptides 5.4.1 Estimating the charge 5.5 Fractional masses 5.5.1 Estimating one or two peptides in a peak complex 5.6 The raw data 5.7 Mass resolution and resolving power 5.7.1 Isotopic resolution 5.8 Exercises 5.9 Bibliographic notes 6 Mass Spectrometry - MALDI-TOF 6.1 Time-of-flight analyzers and their resolution 6.1.1 Time-to-mass converter 6.1.2 Producing spectra 6.1.3 Ionization statistics 6.2 Constructing the peak list 6.2.1 Noise 6.2.2 Baseline correction 6.2.3 Smoothing and noise reduction 6.2.4 Peak detection 6.2.5 Example 6.2.6 Intensity normalization 6.2.7 Calibration 6.3 Peak list preprocessing 6.3.1 Monoisotoping and deisotoping 6.3.2 Removing spurious peaks 6.4 Peak list format 6.5 Automation of MALDI-TOF-MS 6.6 Exercises 6.7 Bibliographic notes 7 Protein Identification and Characterization by MS 7.1 The main search procedure 7.1.1 The experimental data 7.1.2 The database - the theoretical data 7.1.3 Other search parameters 7.1.4 Organization of the database 7.2 The peptide mass comparison 7.2.1 Reasons why experimental masses may not match 7.3 Database search and recalibration 7.3.1 The search program MSA (Mass Spectra Analyzer) 7.3.2 Aldente 7.4 Score calculation 7.4.1 Score components 7.4.2 Scoring scheme examples 7.4.3 Identification from a protein mixture 7.5 Statistical significance - the P-value 7.5.1 A priori probability for k matches 7.5.2 Simulation for determining the P-value 7.5.3 A simple Mascot search 7.6 Characterization 7.7 Exercises 7.8 Bibliographic notes 8 Tandem MS or MS/MS Analysis 8.1 Peptide fragments 8.2 Fragmentation techniques 8.3 MS/MS spectrometers 8.3.1 Analyzers for MS/MS 8.4 Different types of analyzers 8.4.1 TOF/TOF 8.4.2 Triple quadrupole (Triple quad) 8.4.3 Ion trap (IT) 8.4.4 Fourier Transform Ion Cyclotron Resonance (FT-ICR) 8.4.5 Combining quadrupole and Time of flight - Q-TOF 8.4.6 Combining quadrupole and ion trap - Q-TRAP 8.4.7 Combining TOF and Ion trap 8.4.8 Combining Linear ion trap with Orbitrap 8.4.9 Characteristics and performances of some type of analyzers 8.5 Overview of the process for MS/MS analysis 8.6 Fragment ion masses and residue masses 8.7 Deisotoping and charge state deconvolution 8.8 Precursor treatment 8.8.1 Precursor mass correction 8.8.2 Estimating the charge state of the precursor 8.9 MS3 spectra 8.10 Exercises 8.11 Bibliographic notes 9 Fragmentation Models 9.1 Chemical approach 9.1.1 The mobile proton model, MPM 9.2 Statistical approach 9.2.1 Constructing the training set(s) 9.2.2 Spectral subsets 9.3 Learning (collecting statistics) 9.3.1 Fragmentation Intensity Ratio (FIR) 9.3.2 Linear models 9.3.3 Use of decision trees 9.4 The effect of amino acids on the fragmentation 9.4.1 Selective fragmentation 9.5 Exercises 9.6 Bibliographic notes 10 Identification and Characterization by MS/MS 10.1 Effect of operations (modifications - mutations) on spectra 10.1.1 Comparison including modifications 10.2 Filtering and organization of the database 10.3 Scoring and statistical significance 10.4 Exercises 11 Spectral Comparisons 11.1 Constructing a theoretical spectrum 11.2 Non-probabilistic scoring 11.2.1 Number and intensities of matching peaks or intervals 11.2.2 Spectral contrast angle 11.2.3 Cross-correlation 11.2.4 Rank based scoring 11.2.5 SEQUEST scoring 11.3 Probabilistic scoring 11.3.1 Bayesian method - SCOPE 11.3.2 Use of log-odds - OLAV 11.3.3 Log-odds decision trees 11.4 Comparison with modifications 11.4.1 Zone modification searching 11.4.2 Spectral convolution and spectral alignment 11.5 Exercises 11.6 Bibliographic notes 12 Sequencial Comparison - de novo Sequencing 12.1 Spectrum graphs 12.1.1 A general spectrum graph 12.2 Preprocessing 12.3 Node scores 12.4 Constructing the spectrum graph 12.5 The sequencing procedure using spectrum graphs 12.5.1 Searching the graph 12.5.2 Scoring the derived sequences against the spectrum 12.6 Combined spectra to improve de novo sequencing 12.6.1 Use of two fragmentation techniques 12.7 Exercises 12.8 Bibliographic and additional notes 13 Database Searching for De Novo Sequences 13.1 Using general sequence search programs 13.1.1 The main principle of FASTA and BLAST 13.1.2 Changing the operation of FASTA/BLAST 13.1.3 Scoring and statistical significance 13.2 Specialized search programs 13.2.1 OpenSea 13.2.2 SPIDER 13.3 Peptide sequence tags 13.3.1 A general model for peptide sequence tag search programs 13.3.2 Automatic extraction and scoring of sequence tags 13.3.3 Database search 13.3.4 Extending the sequence tag hits with flanking amino acids 13.3.5 Scoring the PST matches 13.3.6 Statistical significance 13.4 Comparison by threading 13.4.1 Use of suffix tree 13.4.2 Use of deterministic finite automata 13.5 Exercises 13.6 Bibliographic notes 14 Large-Scale Proteomics 14.1 Coverage and complexity 14.2 Selecting a representative peptide sample - COFRADIC 14.3 Separating peptides into fractions 14.4 Producing MS/MS spectra 14.5 Spectra filtering 14.5.1 Classifying good and bad spectra 14.5.2 Use of the classifier 14.6 Spectrum clustering 14.6.1 Recognizing sibling spectra 14.6.2 Clustering of sibling spectra 14.6.3 Representative spectra for the groups 14.6.4 De novo sequencing from representative PRM spectra 14.7 Searching the database 14.8 LIMS 14.9 Exercises 14.10 Bibliograpic notes 15 Quantitative Mass Spectrometry-Based Proteomics 15.1 Defining the quantification task 15.2 mRNA and protein quantification 15.3 Quantification of peaks 15.4 Normalization 15.5 Different methods for quantification 15.6 Label-free quantification 15.6.1 Comparing spectra 15.6.2 MALDI-TOF based methods 15.6.3 SELDI-TOF based methods 15.6.4 LC-MS quantification 15.7 Label-based quantification 15.7.1 MS-based labelled quantification 15.7.2 MS/MS-based quantification 15.8 Variance stabilizing transformations 15.9 Dynamic range 15.10 Inferring relative quantity from peptide identification scores 15.11 Absolute quantification methods 15.12 Bibliographic notes 16 Peptides to Proteins 16.1 Peptides and proteins 16.2 Protein identification using peptide masses: an example revisited 16.2.1 Extension to MS/MS derived peptide sequences instead of masses 16.3 Minimal and maximal explanatory sets 16.3.1 Minimal and maximal sets in peptide-centric proteomics 16.3.2 Determining maximal explanatory sets 16.3.3 Determining minimal explanatory sets 16.4 Bibliographic notes 17 Top-Down Proteomics 17.1 Separation of intact proteins 17.2 Ionization of intact proteins 17.3 Resolution and accuracy requirements for charge state determination and mass calculation 17.4 Fragmentation of intact proteins 17.5 Charges of the fragments 17.6 Protein identification 17.7 Protein characterization - detecting modifications 17.8 Problems with top-down approach 17.9 Exercises 17.10 Bibliographic notes 18 Standards 18.1 Standard creation 18.1.1 Types of standards 18.2 Standards from a proteomics perspective 18.2.1 Creation of test samples 18.2.2 Data standards in proteomics 18.2.3 Requirements for data standards 18.2.4 Problems with data standards 18.3 The Proteomics Standards Initiative (PSI) 18.3.1 Minimal reporting requirements 18.4 Mass spectrometry standards 18.5 Modification standards 18.6 Identification standards 18.7 Bibliographic notes Bibliography Index Ordering: Order Online - visit http://www.researchandmarkets.com/reports/571326 Order by Fax - using the order form below Order By Post - print the order form below and send to Research and Markets, Guinness Centre, Taylors Lane, Dublin 8, Ireland. Page 1 of 2 Printed 29/08/2008 06:32:36 Fax Order Form To place an order via fax simply print this form, fill in the information below and fax the completed form to the number at the bottom of this page. If you have any questions please email help@researchandmarkets.com Order information Please verify that the product information is correct and select the format you require. Product Name: Computational Methods for Mass Spectrometry Proteomics Web Address: http://www.researchandmarkets.com/reports/571326 Office Code: OCHGLLOMNVS Report formats Please enter the quantity of the report format you require. Format Quantity Price Hard Copy (Hard Back) €75.00 + EUR€ 50.00 Shipping/Handling * * Shipping/Handling is only charged once per order. Contact information Please enter all the information below in BLOCK CAPITALS. First Name:   Last Name:   Email Address: Job Title: Organisation: Address: City: Postal/Zip Code: Country: Phone Number: Fax Number: Please fax this form to: (646)607-1907 or (646)964-6609 - From USA +353-1-481-1716 or +353-1-653-1571 - From Rest of World Page 2 of 2 Printed 29/08/2008 06:32:36 Payment information Please indicate the payment method you would like to use by selecting the appropriate box.  Pay by Credit Card: American Express Diners Club Master Card Visa Cardholder Name: Expiry Date: / Card Number: CVV Security Code: Issue Date: /   (Diners Club only)  Pay by Check: Please post the check, accompanied by this form, to: Research and Markets, Guinness Centre, Taylors Lane, Dublin 8, Ireland.  Pay by Wire Transfer: Please transfer funds to: Account number: 83313083 Sort code: 98-53-30 Swift code: ULSBIE2D IBAN number: IE78ULSB98533083313083 Bank Address: Ulster Bank, 27-35 Main St, Blackrock, Co. Dublin, Ireland. If you have a Marketing Code please enter it below: Marketing Code: Please note that by ordering from Research and Markets you are agreeing to our Terms and Conditions at http://www.researchandmarkets.com/info/terms.asp Please fax this form to: (646)607-1907 or (646)964-6609 - From USA +353-1-481-1716 or +353-1-653-1571 - From Rest of World