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23rd Human Proteome Organization
World Congress (HUPO)
October 20 – 24, 2024 | Dresden, Germany

MSAID will showcase the novel MSAID Platform for proteomics and the CHIMERYS 4 launch
at this year's HUPO.

HUPO2024-Folgeseite

Connect with us in Dresden

We're thrilled to share that we'll be showcasing our innovations at HUPO in Dresden, Germany! Come find us at Booth #16 where we'll be unveiling the latest advancements in proteomics, including the groundbreaking MSAID Platform.

Don't miss this opportunity to learn about cutting-edge developments in the field. Stay tuned for further details on our activities at HUPO!

Our Oral Presentation

  • OP-66: A comparison of peptide- and spectrum-centric search engines beyond bar charts

    Date and Time: Tuesday, October 22, 2024 | 17:06 – 17:18 | Conference room 5-6
    Session: AI and Bioinformatics Approaches
    Presenter: Michelle Berger

    Data-independent acquisition (DIA) offers reproducibility and proteome coverage but yields complex spectra. Various algorithms were developed for peptide identification. Peptide-centric engines rely on fragment ion elution curves, while spectrum-centric methods analyze spectra individually. Algorithms aim to separate true from false identifications (IDs) through diverse scores, with q-values controlling false discovery rates (FDR). We compare DIA-NN, Spectronaut, and Chimerys examining their unique statistics and scores.

Our Poster Presentations

  • P-I-0128: Intensity-based site localization of post-translational modifications utilizing predicted peptide fragmentation spectra

    Poster Session 1: Monday, Oct 21 | 13:15 – 15:15

    In the last decade, mass spectrometry-based analysis of post-translational modifications (PTMs) in general and phosphorylation in particular has become a routine application in cell signaling studies, and accurate localization of PTM sites is crucial for differentiation of the underlying biology. So far, localization tools mostly rely on peak m/z matching to calculate site probabilities, which does not leverage fragment ion intensity differences between modified peptide isomers. Here, we exploit the capabilities of our deep-learning framework to accurately predict physicochemical properties of modified peptides. We demonstrate the usefulness of these predictions for the intensity-based localization of modification sites. We evaluate different scoring approaches and compare the performance of our intensity-driven approach to available localization tools.

  • P-II-0459: Faster and more accurate intensity-based PTM localization in CHIMERYS

    Poster Session 2: Tuesday, Oct 22 | 13:00 – 15:15

    Acetylation and ubiquitination are two important post-translational modifications (PTMs) influencing the function and half-life of proteins. Mass spectrometry-based bottom-up proteomics is the method of choice for identifying and quantifying peptides harboring PTMs. Traditionally, data dependent (DDA) data were acquired for PTM analysis because of its simplicity and high precursor specificity due to narrow isolation windows. Nowadays, scientists increasingly use data independent (DIA) data for PTM analysis, sometimes with wider isolation windows, which complicates PTM identification and site localization. Here, we present a major update to Chimerys offering compatibility with more PTMs, a novel module for intensity-based PTM localization in DDA, WWA and DIA data, and a new architecture, yielding a 2-fold reduction in processing time for DIA data.

  • P-II-0488: An infinite well: harmonizing all public proteomics data for machine learning

    Poster Session 2: Tuesday, Oct 22 | 13:00 – 15:15

    Synthetic proteomics datasets, like ProteomeTools, are invaluable for machine learning but finite, especially regarding spectra from post-translational modifications. In contrast, public repositories abound with data, yet harmonizing them poses challenges due to diverse measurement environments, methods, software, and calibrations, lacking shared QC peptides. To address this, we developed a distributed, standardized, and cost-effective workflow for searching and harmonizing public data with minimal manual intervention. Processing over 3000 files containing ubiquitinated, phosphorylated, and acetylated peptides, we used a novel machine learning-based calibration. This resulted in ~1 million modified peptides from >33 million high-quality PSMs, complements synthetic public data such as ProteomeTools.

  • P-III-0852: The sky is the limit: a cloud-based proteomics platform for the masses

    Poster Session 3: Wednesday, Oct 23 | 13:00 – 15:00

    Laboratories working with bottom-up proteomics data are frequently confronted with computational challenges in the workflow from raw data to conclusions. Often, the lack of automated pipelines combined with disconnected local infrastructure for raw data storage, data processing, systematic result storage and data interpretation lead to substantial system administration overhead and manual, error-prone steps in this workflow. Recent developments of fast-scanning instruments further exacerbate the issue, as the number of files and raw file size quickly exceed the capacity of local infrastructure. Here, we present a highly scalable, fully automatable, cloud-based proteomics platform as a catalyst for the proteomic data workflow, encapsulating raw data storage, processing, systematic result storage, and easy data interpretation.

Past Events


32nd International Conference on Intelligent Systems for Molecular Biology (ISMB)

July 12 – 16, 2024
Montreal, Canada

ASMS-2024-MSAID


ASMS Conference Mass Spectrometry
and Allied Topics Conference 2024

June 2 – 6, 2024
Anaheim, CA, USA

US-HUPO-2024-MSAID


US HUPO 2024
Bridging ‘Omics To Function

March 9 – 13, 2024
Portland, OR, USA