Sunday, October 20, 2024 - 8:30-14:15
To attend our pre-congress training courses, you'll need to book them separately. Your booking includes access to all available courses.
Just click here to sign up for your chosen course.
Session 1
Post-translational modifications: insights into sample preparation, enrichment, detection and computational.
8:30-10:00 | Conference room 5-6
| Chairs |
|
| Short description |
| This session aims to educate and inspire researchers and students interested in measuring and understanding protein post-translational modifications in their biological or clinical samples. The latest methodologies and research from leading experts in the field will be presented and discussed. Attendees will gain knowledge of the latest strategies, challenges, and solutions in PTM sample preparation and enrichment, covering protein phosphorylation, glycosylation, Cys modifications, and other PTMs like malonylation and succinylation. Additionally, the session will provide insights into PTM detection using state-of-the-art mass spectrometry techniques and demonstrate how advanced computational tools can be properly used for identifying, quantifying, and annotating PTMs. |
| Audience of the course |
| This course will be tailored to students, industry professionals, medical researchers, regulatory and quality control personnel, and academic scholars interested in exploring the experimental and computational approaches to characterize post-translational modifications. Moreover, the attendees of this course will explore the role of PTMs in various biological processes, disease states, and therapeutic interventions. |
| Speakers |
|
Session 2
Leveraging repository data to improve study designs
10:15-11:45 | Conference room 5-6
| Chairs |
|
| Short description |
| This Computational Proteomics Pre-Congress Training is intended to help both new and experienced researchers to incorporate existing knowledge into their proteomics study designs. The program will begin by discussing strengths and weaknesses of sequence databases from sources such as UniProt, Ensembl, and the Joint Genome Institute. It will illustrate strategies for building targeted or DIA experiment designs on the basis of biological pathways known to be involved in a phenotype. Finally, it will discuss strategies to include ProteomeXchange raw data in meta-analysis and the reporting of metadata to enable data reuse. |
| Audience of the course |
This course will be tailored to students, industry professionals, medical researchers, regulatory and quality control personnel, and academic scholars interested in exploring the computational tools and resources to design a proteomic experiment. Moreover, the attendees will learn how to interrogate public proteomic data repositories. |
| Speakers |
|
UniProtKB and beyond: creating the right sequence database The “search space” for protein identification is the set of peptide sequences and their post-translational modifications that will be considered in making peptide-spectrum matches by a database search engine. Constructing a sequence database appropriate to your experiment is therefore a necessary skill for proteomics. This talk will start with UniProtKB, often the default place researchers look for protein sequences, discussing the distinction between reviewed and unreviewed sequences and examining the difference between reference and non-reference proteomes. Resources such as Ensembl, RefSeq, and the Joint Genome Institute will also be considered to support a wider variety of species. Network-based priortization of candidates for targeted proteomics While proteomics has been largely dominated by data-dependent shotgun proteomes, the shift toward more quantitative experiments has gained momentum in recent years. Untargeted data-independent acquisition or targeted parallel reaction monitoring experiments have demonstrated excellent sensitivity for measuring the proteins associated with a given molecular function. This talk will evaluate online resources such as STRING for deciding on a set of proteins to be monitored in detail through quantitative experiments. Network embeddings can capture global network structure, facilitating machine learning-based prioritization. Enhancing the reusability of proteomics data through strengthened metadata standards A large proportion of papers in the proteomics literature is now accompanied by raw and identification data in ProteomeXchange repositories such as PRIDE and MassIVE. Researchers in our field, however, are still adapting to the respositories as a tool for experiment planning rather than as a “write-only” place where data go for long time storage. Data re-use from repositories can dramatically improve experiment planning and can contextualize new experiments. Re-use is only possible, however, if sufficient metadata have been included with a study. The SDRF standard, published in 2021, represents a machine-readable text format for describing which biological samples are represented by each LC-MS/MS experiment and records information critical to reproducing data analysis. Including SDRF descriptions with each ProteomeXchange data set will go a long way toward fostering re-use of proteomes. |
Session 3
Principal Investigator School
12:45-14:15 | Conference room 5-6
| Chairs |
|
| Short description |
| Despite all the training researchers get during grad school and in a postdoc, no one teaches you how to run a productive lab. This workshop will present multiple philosophies towards running a proteomics or mass spectrometry lab given by established professors and PIs, including HUPO president, Jenny Van Eyk, TUM Professor Bernhard Kuster, and other guests. Targeting early career professors, principal investigators, and PI-bound postdocs, this workshop will start with statements from each established panelist on how they got their labs established and predominantly focus on an interactive panel session. The discussion topics will include how to establish a lab community, how to mentor students, how to plan funding, how to manage your attention and focus, and how to prevent burnout. In short, the goal is to teach new and future PIs how to build lasting labs. The workshop and panel discussion will be moderated by Brian Searle. |
| Audience of the course |
| This course will be tailored to early career professors, principal investigators, and PI-bound postdocs that want to lead and manage their research groups including mentoring students, planning funds and organize the different research and administrative activities. This course will aim at preparing the attendees for current and future research endeavors or careers as group leaders in academia or industry. |
| Proposed speakers |
|