Laboratory of Computational Proteomics
Proteomics Informatics Spring 2015
Center for Health Informatics and Bioinformatics
High Performance Computing Facility
NYU Langone Medical Center
Proteomics Informatics Spring 2015 (BMSC-GA 4437)

Course Director: David Fenyö, Associate Professor
Contact information:

David Fenyö (
Himanshu Grover (
Kelly Ruggles (
Jessica Chapman (
Beatrix Ueberheide (

Course overview

This course will give an introduction of proteomics and mass spectrometry workflows, experimental design, and data analysis with a focus on algorithms for extracting information from experimental data. The following subjects will be covered in: (1) Protein identification (peptide mass fingerprinting, tandem mass spectrometry, database searching, spectrum library searching, de novo sequencing, significance testing); (2) Protein char¬acterization (protein coverage, top-down proteomics, post-translational modifications, protein processing and degradation, protein complexes); (3) Protein quantitation (metabolic labeling - SILAC, chemical labeling, label-free quantitation, spectrum counting, stoichiometry, biomarker discovery and verification). Examples will be provided throughout the course on how the different approaches can be applied to investigate biological systems. The class will be structured to include hands-on practical techniques for analyzing relevant proteomics datasets.

Learning objectives

At the conclusion of the course, the student will be able to:

  • Understand experimental design for mass spectrometry based proteomics;
  • Demonstrate detailed understanding of the possibilities and limitations of algorithms that are applied to proteomics data; and
  • Analyze a large proteomics data set using available algorithms.

    Course Assessment

    • Readings and participation (30%): Students are required to attend class, to complete reading assignments and to participate in discussions and engage in healthy exchange of ideas. Each student is required to lead at least one reading from the assigned weekly readings. This discussion lead will be graded.
    • Assignments (30%): Programming assignment will be given at the end of each class, and the solutions to these assignments should be e-mailed to within a week.
    • Final project (40%)
    Missed Exams and Grade Appeals

    Make-up examinations (for final only) will be given under special circumstances. Documentation will be required to verify a student’s claim. If a make-up exam is permitted, a different exam will be written for that student and may have a different format than the regular examination.

    The assignments must be turned in on time and no late assignments will be accepted.

    If there is a time that you believe that there is a mistake in grading of an assignment/exam, you will have a chance to appeal your exam grade within a week after you receive your grade. If you think this is the case, you must write a note describing the error, attach it to the original exam, and give it to me within a week of the return of your exam. I will review your argument and my initial grading, and then return your exam with a decision to you in a timely manner.

    General Policies

    • Late/missed work: You must adhere to the due dates for all required submissions. If you miss a deadline, then you will not get credit for that assignment/post. Try to avoid last minute submissions.
    • Incompletes: No “Incompletes” will be assigned for this course unless we are at the very end of the course and you have an emergency.
    • Responding to Messages: I will check e-mails daily during the week, and I will respond to course related questions within 48 hours.
    • Announcements: I will make announcements throughout the semester by e-mail. Make sure that your email address is updated; otherwise you may miss important emails from me.
    • Safeguards: Always back up your work on a safe place (electronic file with a backup is recommended) and make a hard copy. Do not wait for the last minute to do your work. Allow time for deadlines.
    • Plagiarism: Plagiarism, the presentation of someone else's words or ideas as your own, is a serious offense and will not be tolerated in this class. The first time you plagiarize someone else's work, you will receive a zero for that assignment. The second time you plagiarize, you will fail the course with a notation of academic dishonesty on your official record.

    Lecture 1 Overview of proteomics (February 3, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List

  • M.A. Gillette, S.A. Carr, "Quantitative analysis of peptides and proteins in biomedicine by targeted mass spectrometry", Nature Methods 10 (2013) 28–34.
  • A. Bensimon, A.J.R. Heck R. Aebersold, "Mass Spectrometry–Based Proteomics and Network Biology", Annual Review of Biochemistry 81 (2012) 379-405.

    Lecture 2 Overview of mass spectrometry (February 10, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Fenyo
    Homework (due date: February 17)

    Reading List
  • Beavis, R.C. & Chait, B.T. "Matrix-assisted laser desorption ionization mass-spectrometry of proteins" Meth. Enzymol 270, 519-551 (1996).
  • Banks, J.F. & Whitehouse, C.M. "Electrospray ionization mass spectrometry" Meth. Enzymol 270, 486-519 (1996).
  • Chalkley, R. "Instrumentation for LC-MS/MS in proteomics" Methods Mol. Biol 658, 47-60 (2010).

    Lecture 3 Signal processing I: analysis of mass spectra (February 17, 2015 TRB 718 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Fenyo ( )
    Homework (due date: February 24)

    Reading List
  • Zhang, J., Gonzalez, E., Hestilow, T., Haskins, W. & Huang, Y. "Review of peak detection algorithms in liquid-chromatography-mass spectrometry" Curr. Genomics 10, 388-401 (2009).
  • Yang, C., He, Z. & Yu, W. "Comparison of public peak detection algorithms for MALDI mass spectrometry data analysis" BMC Bioinformatics 10, 4 (2009).

    Lecture 4 Protein identification I: searching protein sequence collections and significance testing (February 24, 2015 TRB 718 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover ( ecoli_1.mgf , yeast_1.mgf , human_1.mgf )
    Homework (due date: March 3)

    Reading List
  • Eriksson, J., Chait, B.T. & Fenyö, D. "A statistical basis for testing the significance of mass spectrometric protein identification results" Anal. Chem 72, 999-1005 (2000).
  • Fenyö, D. & Beavis, R.C. "A method for assessing the statistical significance of mass spectrometry-based protein identifications using general scoring schemes" Anal. Chem 75, 768-774 (2003).
  • Elias, J.E. & Gygi, S.P. "Target-decoy search strategy for increased confidence in large-scale protein identifications by mass spectrometry" Nat. Methods 4, 207-214 (2007).

    Lecture 5 Protein quantitation I: overview (March 3, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • Domon, B. & Aebersold, R. "Options and considerations when selecting a quantitative proteomics strategy", Nat. Biotechnol 28, 710-721 (2010).
  • Zhang, G. et al. "Protein quantitation using mass spectrometry" Methods Mol. Biol 673, 211-222 (2010).

    Lecture 6 Databases, data repositories and standardization (March 10, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover & Chapman

    Reading List
  • Craig R, Cortens JP, Beavis RC, "Open source system for analyzing, validating, and storing protein identification data", J Proteome Res. 3 (2004) 1234-42.
  • D. Fenyö, J. Eriksson, R. Beavis, "Mass spectrometric protein identification using the global proteome machine", Methods Mol Biol 673 (2010) 189-202.
  • CF Taylor, NW Paton, KS Lilley, P-A Binz, RK Julian Jr, AR Jones, W Zhu, R Apweiler, R Aebersold, EW Deutsch, MJ Dunn, AJR Heck, A Leitner, M Macht, M Mann, L Martens, TA Neubert, SD Patterson, P Ping, SL Seymour, P Souda, A Tsugita, J Vandekerckhove, TM Vondriska, JP Whitelegge, MR Wilkins, I Xenarios, JR Yates III, H Hermjakob, "The minimum information about a proteomics experiment (MIAPE)", Nat Biotechnol. 25 (2007) 887-93.

    Lecture 7 Protein quantitation II: multiple meaction monitoring (March 17, 2015 TRB 717 4pm)
    Lecturer: Ruggles ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • D.R. Mani, S.E. Abbatiello, S.A. Carr, "Statistical characterization of multiple-reaction monitoring mass spectrometry (MRM-MS) assays for quantitative proteomics", BMC Bioinformatics 13 (2012) S9.
  • A. Maiolica, M.A. Jünger, I. Ezkurdi, R. Aebersold, "Targeted proteome investigation via selected reaction monitoring mass spectrometry", Journal of Proteomics 75 (2012) 3495-3513.
  • MacLean, B. et al. "Skyline: an open source document editor for creating and analyzing targeted proteomics experiments", Bioinformatics 26, 966-968 (2010).

    Lecture 8 Proteogenomics (March 31, 2015 TRB 619 4pm)
    Lecturer: Ruggles ( Video , Slides )
    Tutorial Instructor: Grover & Chapman

    Lecture 9 Protein identification II: de novo sequencing (April 7, 2015 TRB 717 4pm)
    Lecturer: Ueberheide
    Tutorial Instructor: Grover

    Reading List
  • Seidler J, Zinn N, Boehm ME, Lehmann WD, "De novo sequencing of peptides by MS/MS, Proteomics 10 (2010) 634-49.
  • Standing KG, "Peptide and protein de novo sequencing by mass spectrometry, Curr Opin Struct Biol. 13 (2003) 595-601.

    Lecture 10 Protein characterization I: post-translational modifications (April 21, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • Trost, M., Bridon, G., Desjardins, M. & Thibault, P. "Subcellular phosphoproteomics", Mass Spectrom. Rev. 29, 962-990 (2010).

    Lecture 11 Signal processing II: image analysis (April 28, 2015 TRB 619 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • Introduction to the Quantitative Analysis of Two-Dimensional Fluorescence Microscopy Images for Cell-Based Screening

    Lecture 12 Protein characterization II: protein interactions (May 5, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • Z Hakhverdyan, M Domanski, LE Hough, AA Oroskar, AR Oroskar, S Keegan, DJ Dilworth, KR Molloy, V Sherman, JD Aitchison, D Fenyö, BT Chait, TH Jensen, MP Rout, J LaCava, "Rapid, optimized interactomic screening", Nature Methods 2015
  • A Leitner, R Reischl, T Walzthoeni, F Herzog, S Bohn, F Förster, and R Aebersold, "Expanding the Chemical Cross-Linking Toolbox by the Use of Multiple Proteases and Enrichment by Size Exclusion Chromatography", Mol Cell Proteomics 11 (2012)

    Lecture 13 Data analysis and visualization (May 12, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • Think Stats by Allen B. Downey
  • Data Analysis with Open Source Tools by Philipp K. Janert
  • Data visualization: A view of every Points of View column

    Lecture 14 Molecular signatures (May 21, 2015 TRB 717 4pm)
    Lecturer: Fenyo ( Video , Slides )
    Tutorial Instructor: Grover

    Reading List
  • EF Petricoin III, AM Ardekani, BA Hitt, PJ Levine, VA Fusaro, SM Steinberg, GB Mills, C Simone, DA Fishman, EC Kohn, LA Liotta, "Use of proteomic patterns in serum to identify ovarian cancer", Lancet 359 (2002) 572–77
  • DF Ransohoff, "Bias as a threat to the validity of cancer molecular-marker research", Nat Rev Cancer 5 (2005) 142-9.
  • TA Addona, X Shi, H Keshishian, DR Mani, M Burgess, MA Gillette, KR Clauser, D Shen, GD Lewis, LA Farrell, MA Fifer, MS Sabatine, RE Gerszten & SA Carr, "A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease", Nature Biotechnology 29 (2011) 635

    Lecture 15 Presentations of projects (May 26, 2015 TRB 717 4pm)