Short Courses

Saturday, February 22

9:00 AM - 4:00 PM - Short Course

Quantitative Data Analysis for Proteomics - Part 1

This course will cover both theory and practice for analyzing quantitative proteomics data. The course will be a mixture of both "lecture" and "lab" portions. The "lectures" will discuss best practices, considerations, and pitfalls for interpreting label-free and labeled measurements, including those produced by DDA, DIA, PRM, TMT/iTRAQ, and SILAC methods. The "labs" will give students a chance to explore and analyze raw data from different instrument platforms with Skyline and other open-source tools using Windows laptops that they either bring with them or have remote access to. While participants are highly recommended to bring their own computers to get the full experience, participants without Windows laptops will be able to join up as teams to analyze datasets. The goal of this course is to give students a foundation for how data analysis tools work and to build an intuition for what data analysis challenges lurk in their datasets. A portion of the class will be devoted to "office hours" where students will get a chance to discuss their specific quantitative proteomics challenges. Audience: proteomics researchers at all levels that want to learn what common proteomics data analysis tools/methods are doing, how they work, and where they break down.

Presented By:

Brian Searle, United States
(Bio)

Machine Learning for Mass Spectrometry Data Analysis - Part 1

Over the past decade, machine learning has become a dominant technology for data-intensive discovery in nearly all scientific domains. Today, almost all biomedical research employs machine learning techniques to derive new knowledge from complex biological data. This course will introduce the fundamentals of common machine learning techniques used for the analysis of mass spectrometry data. The main goal of the course is to promote basic data literacy for people new to machine learning. This will help researchers to perform basic machine learning analyses, recognize common pitfalls, know when and how to consult a machine learning expert, and better understand machine learning applications in the scientific literature. Each session will include hands-on exercises to illustrate the covered material. Prerequisites: All participants will need to bring a laptop to perform example exercises during the course. Basic knowledge of mass spectrometry and data analysis is recommended. Basic knowledge of Python is recommended. No extensive machine learning experience is needed.

Presented By:

Wout Bittremieux, University of Antwerp
(Bio)

Justin Sanders, University of Washington, WA, WA, United States

Sunday, February 23

9:00 AM - 12:00 PM - Short Course

Applications for Tissues, Cells and Biofluids by Multiomic Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is an innovative platform for spatial biology of human health and disease with a broad range of applications from tissue histopathology to visual analysis of cells and biofluids as arrays. The current state of the field is the use of novel combinations of cell markers with de novo multiomics: proteomics, glycomics, drugs, and metabolites. This 4-hour short course is a combination of lectures and expert discussion on translational and clinical applications of the MSI platform. The short course will start with a brief tutorial discussion on mass spectrometry imaging and state-of-the-art instrumentation. This will be followed by a lecture and discussion on the application of MSI in multiomic glycomics and proteomics in studies of clinical relevance, including therapeutics and survival. Next, the course will cover applications of the MSI platform applied to glycomics of tissues, cells, and fluids. Finally, we will conclude with a lecture and discussion on multiomic studies of drugs and metabolomics. Lectures will be 45 minutes long with 15 minutes of discussion for a high level of attendee interaction. Resources and protocols used in mass spectrometry imaging will be shared with attendees. The goal of this course is to provide attendees with an interactive forum for expert information and discussion on applications of state-of-the-art spatial biology that incorporate mass spectrometry imaging.

Presented By:

Peggi Angel

Richard Drake, Medical University of South Carolina

Elizabeth Neumann, University of California at Davis, CA, CA, United States

Proteomics in (Bio)Pharma Industry: Bridging the Gap

This short course aims to bridge the experience gap between proteomics research in academic and industrial settings, with a specific focus on the (bio)pharma industry. The course will highlight the unique features, challenges, and opportunities of conducting proteomics work in an industrial setting, where the focus is on delivering medicines for patients in need - while balancing risk, impact, timelines, and profit. The course will start with a brief introduction to the drug discovery process, highlighting the three different stages - discovery, pre-clinical, and clinical phases - and how proteomics can play a role in each of them. The main part of the course will consist of facilitated discussions on two key topics. Firstly, we will explore opportunities for students to understand scientific work in industrial settings. Secondly, strategies for demonstrating the impact of proteomics in the (bio)pharma industry will be discussed. The focus of the discussion can shift based on the final structure of the audience. The discussions will be summarized into actionable bullet points, providing participants with tangible takeaways. The course will conclude with a short informal networking session, allowing participants to connect and exchange ideas.

Presented By:

Jan Schejbal, Senior Scientist I, Abbvie

Dorothy Ahlf Wheatcraft, Senior Scientist, AstraZeneca

9:00 AM - 4:00 PM - Short Course

Machine Learning for Mass Spectrometry Data Analysis - Part 2

Presented By:

Wout Bittremieux, University of Antwerp
(Bio)

Justin Sanders, University of Washington, WA, WA, United States

Quantitative Data Analysis for Proteomics - Part 2

Presented By:

Brian Searle, United States
(Bio)

1:00 PM - 4:00 PM - Short Course

Chemoproteomics 101: Introduction and Applications

Chemoproteomics = chemical biology + proteomics. If that doesn't clear things up, this course is for you! Chemoproteomics leverages mass spectrometry-based proteomics to study the action of chemical probes (typically, small molecules) in biological systems, with the aim of identifying and developing chemical tools to explore biology and expand the "druggable proteome". This course will provide an introductory overview of chemoproteomics, exploring its methodologies, applications, and challenges. Participants will learn about the use of chemoproteomics in drug discovery, proteome-wide target identification, and emerging techniques for mass spectrometry-based phenotypic assays. By the end of the course, participants will have a solid understanding of the principles and applications of chemoproteomics.

Presented By:

Michael Lazear, Belharra Therapuetics

Crafting and Marketing Proteomics: Strategies for Promoting Your Research

***This short course requires pre-registration and an additional fee. Click here for more details.***

This session will guide participants through the process of designing educational materials that effectively communicate complex proteomics concepts to a wide range of audiences. Attendees will work on creating engaging content such as tutorials, infographics, and videos while learning marketing strategies to promote these materials. The session will cover essential marketing strategies, including branding, outreach, and the use of digital platforms to reach and influence both scientific and public audiences. By the end of the course, attendees will have developed a toolkit for creating engaging content and a strategic plan for marketing it to both scientific and non-scientific audiences.

Presented By:

Dragana Noe, Discovery Life Sciences