New Technology: AI and Bioinformatics in Mass Spectrometry

Programm

• • Poster presentation
  • P-II-0445

  Extending PSM rescoring for timsTOF data to MSFragger with Oktoberfest

  • Charlotte Adams (Antwerp / BE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0446

  Tree-based quantification retrieves proteoforms from bottom-up proteomics data

  • Constantin Ammar (Planegg / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0447

  Zero-shot retention time prediction for unseen post-translational modifications with molecular structure encodings

  • Wout Bittremieux (Antwerp / BE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0448

  Mixed-species based computational simulation of proteoform groups

  • Isabell Bludau (Munich / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0449

  Towards open modification search with MS Andrea

  • Louise Marie Buur (Hagenberg / AT)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0450

  DIAgui a shiny app to process the output from DIA-NN

  • Luc Camoin (Marseille / FR)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0451

  Evaluation of different rescoring platforms to increase peptide identifications

  • Jesus Castano (Saint-Hyacinthe / CA)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0452

  pi-SPECFormer: pretraining improves spectrum embedding through contrastive learning with transformer

  • Tianze Ling (Beijing / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0453

  MassDash: a web-based dashboard for data-independent acquisition mass spectrometry visualization

  • Joshua Charkow (Toronto / CA)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0454

  imputomics 2.0: bridging data gaps in proteomics with missing value imputation algorithms and their benchmark

  • Jarosław Chilimoniuk (Białystok / PL)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0455

  Phosphorylation site prediction model using structural context

  • Yujin Choo (Seoul / KR)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0456

  Tesorai Search: Large pretrained model boosts peptide identifications without the need for Percolator

  • Peter Cimermancic (San Diego, CA / US)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0457

  DIA-NN: enabling peptidoform confidence in DIA proteomics

  • Vadim Demichev (Berlin / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0458

  IM2Deep predicts collisional cross-sections of modified and multiconformational peptide ions

  • Robbe Devreese (Ghent / BE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0459

  Faster and more accurate intensity-based PTM localization in Chimerys

  • Martin Frejno (Garching / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0460

  Altimeter and pioneer: fast and open-source software for analyzing narrow-window data-independent acquisition proteomics experiments

  • Dennis Goldfarb (Saint Louis, MO / US)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0461

  Effect of sample size on statistical accessibility of proteins and enrichment analysis in proteomics experiments

  • Francesco Greco (Pisa / IT)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0462

  Feature screening and model regularization for k-mer representations of biological sequences

  • Krystyna Grzesiak (Wrocław / PL)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0463

  NA deconvolution analysis(NADA) promotes excavation of unique proteins and protein-protein interactions from proteomics datasets

  • Weiheng Guo (Hong Kong / HK)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0464

  Deep learning for MALDI-MSI: towards a common framework for transferable tissue diagnostics

  • Patrick Jensen (Lyngby / DK)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0465

  FLASHTagger: an open-source web application for ion type- and precursor mass-free protein identification in top-down mass spectrometry

  • Kyowon Jeong (Tuebingen / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0466

  Inferring dynamic interaction network landscape with deep graph contrastive representation learning

  • Wenyi Jin (Hong Kong / HK)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0467

  XL-Prosit: accurate fragment intensity prediction and enhanced cross-linked peptide identification for protein structural and interaction studies

  • Mostafa Kalhor (Freising / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0468

  TIMSrescore: timsTOF-optimized PSM rescoring boosts identification rates for immunopeptidomics

  • Michele Genangeli (Leiderdorp / NL)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0469

  MHC validator boosts unbiased discovery of conserved T-Cell epitope vaccine candidates through improved immunopeptidomics sensitivity

  • Peter Kubiniok (Montreal / CA)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0470

  midiaID: a flexible pipeline for the analysis of midiaPASEF data

  • Mateusz Lacki (Mainz / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0471

  A novel supervised learning algorithm for real-time collision energy selection to optimize peptide fragmentation in mass spectrometry

  • Mathieu Lavallée-Adam (Ottawa / CA)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0472

  GPMelt: a versatile and interpretable Gaussian process-based statistical framework for analyzing thermal proteome profiling datasets

  • Cecile Le Sueur (Heidelberg / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0473

  A Shrinkage-based statistical method for testing group mean differences in quantitative bottom-up proteomics

  • Namgil Lee (Seoul / KR)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0474

  Transforming de novo peptide sequencing by explainable AI

  • Zhendong Liang (Shenzhen / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0475

  MS-BERT: a pre-trained model for data-independent acquisition mass spectrometry-based proteomics data analysis

  • Zhiwei Liu (Hangzhou / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0476

  MsBayesImpute: a versatile framework for handling missing values in mass-spectrometry data through a combined Bayesian factorization and probabilistic dropout model

  • Junyan Lu (Heidelberg / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0477

  Identifying and quantifying the unknown. Two workflows combined to search for variant/mutation information and to quantify un-/identified spectra in MS-based proteomics

  • Dominik Lux (Bochum / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0478

  Statistical benchmark of Label-free DIA quantification using the generic integration algorithm with iSanXoT

  • Ana Martinez-Val (Madrid / ES)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0479

  SpectroPipeR – an R package for the downstream analysis of Spectronaut DIA-MS data

  • Stephan Michalik (Greifswald / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0480

  Systems-wide Functional Characterization of Time-resolved Protein Dynamics by Mass Spectrometry

  • Till Möcklinghoff (Heidelberg / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0481

  Enhancing peptide-spectrum match identification: leveraging mokapot with nonlinear machine learning algorithms to increase PSMs, with consideration for false positives

  • Alireza Nameni (Ghent / BE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0482

  Direct spectrum-centric analysis of diaPASEF data using diaTracer and FragPipe computational platform

  • Alexey Nesvizhskii (Ann Arbor, MI / US)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0483

  Artificial Intelligence in mass spectrometry: fascinating past, exciting present and promising future

  • Magnus Palmblad (Leiden / NL)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0484

  Optimization of peptide selection for absolute protein quantification using QconCATs

  • Jorge Peinado-Izaguerri (Manchester / GB)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0485

  Aiproteomics: a Python package to facilitate the use of deep learning for DIA-MS-based phosphoproteomics data processing

  • Thang V. Pham (Amsterdam / NL)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0486

  CURTAIN – a unique web-based tool for exploration and sharing of MS-based proteomics data

  • Toan Phung (Dundee / GB)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0487

  DIGging into the DIGestion

  • Jasmína Mária Portašiková (Prague / CZ)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0488

  An infinite well: harmonizing all public proteomics data for machine learning

  • Tobias Schmidt (Garching / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0489

  AI-powered Onco-Knowledge Graph (OncoKG) for Precision Medicine

  • Dibyendu Seal (Heidelberg / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0490

  Optimizing search engines to detect marginal peptide matches using large-scale matched-matrix "truth" datasets

  • Brian Searle (Columbus, OH / US)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0491

  ProteomicsDB: connecting proteomes across species

  • Armin Soleymaniniya (Freising / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0493

  A CCS-centric HLA-specific trained de novo module for precise and accurate real-time immunopeptide identification on the Bruker ProteoScape platform

  • Angela Paul (Coventry / GB)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0494

  The benefit of in silico predicted spectral libraries in data-independent acquisition data analysis workflows

  • An Staes (Ghent / BE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0495

  TimSim – a simulation framework for PASEF-like timsTOF proteomics mass spectrometry raw data

  • David Teschner (Mainz / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0497

  SWAPS: a joint peptide identification and quantification approach to increase the depth and coverage of LC-MS experiments

  • Zixuan Xiao (Freising / DE)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0498

  Benchmarking deep learning models and classical de novo sequencing tools for immunopeptidomics

  • Liang Xue (Cambridge, MA / US)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0499

  Benchmarking predictions models for improved peptide identification with MSBooster and Koina

  • Kevin Yang (San Jose, CA / US)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0500

  Enhancing metaproteomics analysis with deep learning prediction to uncover new microbial communities in deep-sea hydrothermal vents

  • Xinpei Yi (Shanghai / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0501

  Unleash the power of Hybrid-DIA data analysis with AI-driven software for biomarker discovery and validation in translational research

  • Qing Zhang (Waterloo / CA)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0502

  SPverse: an R package for data analysis of spatial proteomics derived from micro-FFPE tissues

  • Haichao Zhou (Shenzhen / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0503

  Enhancing protein analysis with the confident PTM/Mutation algorithm

  • Wenting Li (Shanghai / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry
• • Poster presentation
  • P-II-0504

  Deep learning prediction of Glycopeptide tandem mass spectra powers Glycoproteomics

  • Yu Zong (Shanghai / CN)

   New Technology: AI and Bioinformatics in Mass Spectrometry