A5041284510- Advanced Proteomics Techniques and Applications
- Mass Spectrometry Techniques and Applications
- Metabolomics and Mass Spectrometry Studies
- Machine Learning in Bioinformatics
- Ion-surface interactions and analysis
- vaccines and immunoinformatics approaches
- Electron and X-Ray Spectroscopy Techniques
- Blood properties and coagulation
- Biosensors and Analytical Detection
- Antimicrobial Peptides and Activities
- Genomics and Phylogenetic Studies
- Advanced Electron Microscopy Techniques and Applications
- Bioinformatics and Genomic Networks
Max Planck Institute of Biochemistry
2018-2024
Max Planck Society
2019
Report30 September 2019Open Access Transparent process Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies Philipp E Geyer orcid.org/0000-0001-7980-4826 Department of Proteomics Signal Transduction, Max Planck Institute Biochemistry, Martinsried, Germany NNF Center for Protein Research, Faculty Health Sciences, University Copenhagen, Denmark Search more papers by this author Eugenia Voytik Peter V Treit Sophia Doll Alisa Kleinhempel Laboratory Medicine,...
The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate nature utility collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests five organisms with trapped ion mobility spectrometry (TIMS) parallel accumulation-serial fragmentation (PASEF). scale precision (CV < 1%) our is sufficient to train deep recurrent neural network that accurately predicts CCS values...
Machine learning and in particular deep (DL) are increasingly important mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention time, ion mobility fragment intensities of a peptide just from amino acid sequence with good accuracy. However, is very rapidly developing field new neural network architectures frequently appearing, which challenging to incorporate for proteomics researchers. Here we introduce AlphaPeptDeep, modular Python framework built on PyTorch...
Abstract In common with other omics technologies, mass spectrometry (MS)-based proteomics produces ever-increasing amounts of raw data, making efficient analysis a principal challenge. A plethora different computational tools can process the MS data to derive peptide and protein identification quantification. However, during last years there has been dramatic progress in computer science, including collaboration that have transformed research industry. To leverage these advances, we develop...
High-resolution MS-based proteomics generates large amounts of data, even in the standard LC–tandem MS configuration. Adding an ion mobility dimension vastly increases acquired data volume, challenging both analytical processing pipelines and especially exploration by scientists. This has necessitated aggregation, effectively discarding much information present these rich datasets. Taking trapped spectrometry (TIMS) on a quadrupole TOF (Q-TOF) platform as example, we developed efficient...
ABSTRACT In common with other omics technologies, mass spectrometry (MS)-based proteomics produces ever-increasing amounts of raw data, making their efficient analysis a principal challenge. There is plethora different computational tools that process the MS data and derive peptide protein identification quantification. During last decade, there has been dramatic progress in computer science software engineering, including collaboration have transformed research industry. To leverage these...
ABSTRACT Data independent acquisition (DIA) modes isolate and concurrently fragment populations of different precursors by cycling through segments a predefined precursor m/z range. Although these selection windows collectively cover the entire range, overall only few percent all incoming ions are sampled. Making use correlation molecular weight ion mobility in trapped device (timsTOF Pro), we here devise novel scan mode that samples up to 100% peptide current. We extend an established...
ABSTRACT Data-independent acquisition (DIA) methods have become increasingly attractive in mass spectrometry (MS)-based proteomics, because they enable high data completeness and a wide dynamic range. Recently, we combined DIA with parallel accumulation – serial fragmentation (dia-PASEF) on Bruker trapped ion mobility separated (TIMS) quadrupole time-of-flight (TOF) spectrometer. This requires alignment of the separation downstream selective quadrupole, leading to more complex scheme for...
Abstract Summary Integrating experimental information across proteomic datasets with the wealth of publicly available sequence annotations is a crucial part in many studies that currently lacks an automated analysis platform. Here, we present AlphaMap, Python package facilitates visual exploration peptide-level proteomics data. Identified peptides and post-translational modifications are mapped to their corresponding protein visualized together prior knowledge from UniProt expected...
ABSTRACT Although current mass spectrometry (MS)-based proteomics identifies and quantifies thousands of proteins (modified) peptides, only a minority them are subjected to in-depth downstream analysis. With the advent automated processing workflows, biologically or clinically important results within study rarely validated by visualization underlying raw information. Current tools often not integrated into overall analysis nor readily extendable with new approaches. To remedy this, we...
Abstract Machine learning and in particular deep (DL) are increasingly important mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention time, ion mobility fragment intensities of a peptide just from amino acid sequence with good accuracy. However, is very rapidly developing field new neural network architectures frequently appearing, which challenging to incorporate for proteomics researchers. Here we introduce AlphaPeptDeep, modular Python framework built on...
Abstract Plasma and serum are rich sources of information regarding an individual’s health state protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)-based proteomics now allows highly specific quantitative read-out plasma proteome. Here we employ Proteome Profiling to define contamination marker panels assess samples likelihood that suggested instead artifacts related sample handling processing. We...
ABSTRACT The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To explore nature utility entire collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests five organisms with trapped ion mobility spectrometry (TIMS) parallel accumulation – serial fragmentation (PASEF). scale precision (CV <1%) our is sufficient to train deep recurrent neural network that accurately...
Abstract High resolution mass spectrometry-based proteomics generates large amounts of data, even in the standard liquid chromatography (LC) – tandem spectrometry configuration. Adding an ion mobility dimension vastly increases acquired data volume, challenging both analytical processing pipelines and especially exploration by scientists. This has necessitated aggregation, effectively discarding much information present these rich sets. Taking trapped (TIMS) on a quadrupole time-of-flight...
Abstract Summary Integrating experimental information across proteomic datasets with the wealth of publicly available sequence annotations is a crucial part in many studies that currently lacks an automated analysis platform. Here we present AlphaMap, Python package facilitates visual exploration peptide-level proteomics data. Identified peptides and post-translational modifications are mapped to their corresponding protein visualized together prior knowledge from UniProt expected...
Identification and quantification of disease-associated proteins in human biofluids is much needed for monitoring disease progression HD gene expression carriers as well providing means therapeutic intervention. We believe studying with cutting-edge proteomics tools will help these unmet needs provide novel leads further validation use the clinic. To this end, cerebrospinal fluid (CSF) an accessible source enriched brain derived peptides proteins, which allows us to investigate changes CNS...