NovoGlycoX v2.0.1 (Beta) — Executable version (expanded 29/05/2026)

0. Overview

NovoGlycoX is a fully untargeted glycoproteomics platform for identifying and characterizing prokaryotic protein glycosylation directly from shotgun proteomics data. NovoGlycoX integrates de novo discovery of oxonium ions, sequence tag database matching, and mass offset binning to extract glycan masses, compositions, and attachment types. Results are provided with an interactive visualization framework that supports exploration of glycan features and glycoproteins. NovoGlycoX combines ultra-fast database searching, de novo identification of sugar oxonium ions, sequence tag generation and matching for fully untargeted, glycan database-independent glycopeptide identification. Additional offset binning of glycopeptide spectra provides insights into glycan composition and linking sugars. Results are visualized in a user-friendly interactive dashboard interface. NovoGlycoX works in tandem with Oxonium Browser to provide a complete solution for untargeted prokaryotic glycopeptide analysis. The platform processes all SAGE-unmatched MS2 spectra through a glycan database-independent search pipeline and annotates oxonium ion presence. Note: This is a beta version. Detailed documentation is available in the SourceForge Wiki section, including a comprehensive parameter guide, analytical metrics explanation, and system architecture.

┌───────────────┐     ┌───────────────┐     ┌───────────────┐     ┌───────────────┐
│  Input Files  │───▶│ SAGE Database │────▶│   Spectral    │────▶│  Oxonium Ion  │
│  Processing   │     │    Search     │     │  Processing   │     │  Annotation   │
└───────────────┘     └───────────────┘     └───────────────┘     └───────────────┘
                                                                          │
                                                                          ▼
┌───────────────┐     ┌───────────────┐     ┌───────────────┐     ┌───────────────┐
│  Interactive  │◀────│ Glycopeptide  │◀───│ Sequence Tag  │◀────│ DirecTag De  │
│   Dashboard   │     │  Validation   │     │   Matching    │     │Novo Sequencing│
└───────────────┘     └───────────────┘     └───────────────┘     └───────────────┘

Pipeline OUTLINE

NovoGlycoX executes the following steps:

Step 1–2: Database Search

The SAGE search engine performs ultra-fast peptide identification with trypsin specificity (KR, not before P), fixed carbamidomethylation (C), variable oxidation (M), and target-decoy competition at the user-defined FDR threshold. Identified peptide-spectrum matches (PSMs) and their scan numbers are extracted for downstream filtering.

Step 3: mzML Import

MS2 spectra are extracted from the mzML file using pyteomics. Spectra already identified by SAGE are excluded, retaining only unmatched spectra as potential glycopeptide candidates. HCD/ETD scan pairs are identified for complementary fragmentation analysis.

Step 4: Focused Database Creation

The reference FASTA is digested in silico (trypsin, user-defined missed cleavages), retaining only proteins previously identified by SAGE. This focused database dramatically reduces the search space for tag matching. Peptides are filtered to those containing potential glycosylation sites (S, T, or N by default). Decoy peptides are generated by shuffling protein sequences prior to digestion. Leucine/isoleucine equivalence (L→I) is applied.

Step 5: De Novo Sequencing

DirecTag generates sequence tags of defined length (default 5 amino acids) from all MS2 spectra, producing up to 10 tags per spectrum ranked by scoring metrics.

Step 6: Spectral Processing

All unmatched MS2 spectra are processed without any filtering:

• Parent ion masses are calculated from precursor m/z and charge state
• Multiply charged fragment ions are deconvoluted to singly charged equivalents
• Precursor offsets are calculated as the mass difference between the singly charged precursor and each decharged fragment above 750 Da Both original (pre-decharge) and decharged arrays are retained per spectrum.

Step 7: Oxonium Ion Annotation

Each processed spectrum is annotated for the presence of diagnostic oxonium ion pairs from the input list. For each oxonium ion, both the intact ion and its water loss fragment must be present within the mass tolerance and above the intensity threshold. Detection uses the original (non-decharged) arrays with TIC-normalised intensities. A boolean flag column (ox_<n>) is added per oxonium ion.

Step 8: Sequence Tag Filtering

De novo tags are filtered to retain only those belonging to processed spectra and matching the specified tag length.

Step 9: Tag Matching and Validation

Sequence tags are matched against the focused database. For each match, the following validation is applied: - The matched peptide mass must be at least 100 Da smaller than the precursor (room for glycan) - Y0 ion validation when enabled, the unmodified peptide ion (peptide mass + proton) must be present. Disabling this check increases sensitivity at the cost of specificity. - Mass delta (glycan mass) is calculated as precursor mass − peptide mass - Peptide offsets are calculated as the mass differences between fragment ions above the Y0 and the Y0 mass itself Results are grouped per scan: the peptide-protein combination with the highest number of independently matched tags is reported as the confident identification. Tag count redundancy (tag_counts) serves as the primary confidence metric.

Step 10: Cross-Referencing

Identified glycopeptides are cross-referenced against SAGE results to flag cases where the unmodified peptide was also identified, providing additional confidence. Source code, documentation and releases are available at: https://sourceforge.net/projects/novoglycox/

1. System requirements

NovoGlycoX was tested on 64-bit versions of Windows 10 and Windows 11. This is a standalone executable with graphical user interface, no separate Python installation required. The source Python code (NovoGlyco_python_2.0.1.zip) and Docker version (NovoGlyco_docker_2.0.1.zip) are available separately via SourceForge for advanced users. The software runs locally through an embedded Dash framework and is accessed through a local web browser interface. The software was validated on standard desktop and laptop systems equipped with Intel Core i7 and Intel Xeon processors with 16–64 GB RAM. No dedicated GPU or specialized hardware is required. NovoGlycoX Python was tested on 64-bit versions of Windows 10 and Windows 11. Recommended minimum requirements: 4 GB RAM (higher recommended for Astral datasets) 10 GB free disk space (approximately 50 GB recommended for multiple analyses and intermediate files) Both HDD- and SSD-based storage systems were tested successfully. The interactive dashboard was tested with: Microsoft Edge 148.0.3967.83 (64-bit) Google Chrome 148.0.7778.179 (64-bit) NovoGlycoX was primarily developed and validated using Thermo Scientific Orbitrap-based instruments, including Q Exactive, Orbitrap Exploris, Orbitrap Eclipse, and Orbitrap Astral systems. The software is expected to work with any LC-MS/MS platform capable of exporting centroided mzML files with HCD and/or ETD fragmentation data. However, extensive testing on non-Thermo platforms has not yet been performed. For Astral datasets, larger mzML files and increased memory consumption may slow down the browswer-based user interface. Consider using the Python pipeline for larger datasets.

2. Installation guide

Download the executable and extract

# Navigate to https://sourceforge.net/projects/novoglycox/files/
# Download NovoGlyco_executable_2.0.1.zip
# Unzip and navigate to the directory where the ".exe" file is stored.

Install Python dependencies

This is a standalone executable, no separate installation of Python or other dependencies required.

Navigate to https://sourceforge.net/projects/novoglycox/files/

Download "TEST_SAMPLE.zip" and unzip

The folder contains the example mzML, fasta and .xlsx file with selected oxoniums

Typical installation time

Setup typically requires 5 minutes on a standard desktop computer, depending on internet speed.

3. and 4. Demo, Instructions for use and run on data

After downloading and unpacking NovoGlyco_executable_2.0.1.zip and TEST_SAMPLE.zip, click on NovoGlycoX_v2_0_1.exe. Before running, a desktop shortcut can be created. A few minutes after start, the interactive NovoGlyco-X dashboard-browser window opens. Default parameters are suitable for the provided demo dataset, but these can be adjusted in the browser window as needed before execution. The demo dataset, MP_14022020_Kust_Nm_120min_gps_DDA01.mzML, is a highly glycosylated control sample, from Ca. Kuenenia stuttgartiensis, showing two distinct glycan types, one containing HexNAc-based complex glycans, and another based on oligo-heptosidic glycans. The fasta file contains the Ca. Kuenenia stuttgartiensis reference proteome, and selected_oxoniums.xlsx contains a set of earlier identified oxonium ions. Please also check the NovoGlycoX wiki at https://sourceforge.net/p/novoglycox/wiki/Home/.

Running NovoGlycoX on your own data

1. Convert RAW files to mzML (not needed for test dataset)
2. Place mzML, FASTA and oxonium .xlsx files into an Input folder
3. Adjust parameters in browser window if needed
4. Select the correct file paths for mzML, fasta and selected oxonium ion excel file
5. Click Run NovoGlyco X to start analysis
5. The results appear in the same browser window, below the input window. A separate excel summary is provided in the Output folder

Input file summary

Place the following files in the Input directory: 1. Mass Spectrometry Data: - .mzML file - Note: Vendor-specific RAW files must be converted to mzML format before using this tool 2. Protein Database: - .fasta file containing protein sequences 3. Sugar Oxonium Ion List: - .xlsx file containing sugar oxonium ions to be searched for (Output of Oxonium Browser - see Oxonium Ion Excel File Format below)

Converting RAW Files to mzML

NovoGlycoX requires mzML format input. Use ProteoWizard MSConvert (recommended): 1. Open MSConvert GUI and select your RAW file(s) 2. Set output format to mzML 3. Recommended settings: - Peak Picking: checked (MS levels 1–2; for Astral data, MS level 2 only to reduce size) - Binary encoding precision: 64-bit (default); 32-bit acceptable for Astral data to reduce file size - zlib compression: checked - Write index: checked - TPP compatibility: checked 4. Place the resulting .mzML file in the Input directory Note: For Astral data, ensure sufficient available memory — the required memory is approximately equal to the mzML file size. For detailed conversion instructions, see the MSConvert documentation.

Configurations

Customize parameters via the dashboard browser input window. Defaults are:

Available Parameters

Glycopeptide Detection Parameters

Glycosites (allowed amino acids)=[STNY]         # Filter for peptides containing S, T, N or Y
AMINO_ACID_MARKER=false (unchecked/checked)     # Set to true to enable amino acid marker detection
Intensity threshold=0.1                                         # Intensity threshold for oxonium ion detection (% of TIC)
MASS_ERROR=0.005                                # Mass error tolerance (Da) for oxonium ion detection
MIN_OFFSET=750                                  # Minimum fragment m/z for precursor offset calculation
VALIDATE_PEPTIDE_MASS=(unchecked/checked)       # Validate peptide mass by Y0 ion presence (can be set to false for maximum sensitivity)
Exclude frag type=ETD (select)                              # Activation method to exclude: ETD, HCD or NONE

Peptide Database Parameters

MIN_LENGTH=6                # Minimum peptide length
MAX_MISSED_CLEAVAGES=0      # Maximum allowed missed cleavages for focused database

SAGE Database Search Parameters

SAGE_MIN_PEPTIDE_LENGTH=6   # Minimum peptide length for SAGE search
SAGE_MISSED_CLEAVAGES=2     # Maximum missed cleavages for SAGE search
SAGE_GENERATE_DECOYS=true   # Generate decoy database for FDR estimation
SAGE_PREC_TOL=20            # Precursor mass tolerance in ppm
SAGE_FRAG_TOL=20            # Fragment ion mass tolerance in ppm
SAGE_FDR=1                  # FDR threshold as percentage

De Novo Sequencing Parameters

TAG_LENGTH=5                # Length of sequence tags for de novo sequencing

Visualization Parameters

BIN_WIDTH=1                                     # Bin width (Da) for histograms NOTE: smaller bin widths (<0.5) slow down the browser interface (if small bin widths (<0.25) are needed run from python source code directly)
SAVE_PLOTS_LOCALLY=unchecked (or checked)       # Save static histogram plots as PNG files
PORT=automatic (default 8050)                   # Port for the interactive dashboard

Common Parameter Combinations

Example prokaryotic O-Glycosylation Analysis

TAG_LENGTH=5
MIN_OFFSET=750
Intensity threshold=0.25
Glycosites (allowed amino acids)=[STY]
VALIDATE_PEPTIDE_MASS=checked
Exclude frag type=ETD
Max missed cleavages=1
SAGE_FDR=1

Example prokaryotic N-Glycosylation Analysis

TAG_LENGTH=5
MIN_OFFSET=750
Intensity threshold=0.25
Glycosites (allowed amino acids)=[N]
VALIDATE_PEPTIDE_MASS=checked
Exclude frag type=ETD
Max missed cleavages=1
SAGE_FDR=1

Example low-Abundance Glycopeptide Discovery

TAG_LENGTH=4
MIN_OFFSET=500
Intensity threshold=0.1 (or 0.05)
Glycosites (allowed amino acids)=[NSTY]
VALIDATE_PEPTIDE_MASS=unchecked
Max missed cleavages=2
SAGE_FDR=5
Exclude frag type=EDT

Expected runtime

For the provided demo dataset, the expected runtime on a standard desktop computer is approximately 5-15 minutes.

Expected outputs

NovoGlycoX provides an interactive dashboard-browser output which appears below the input interface, and Excel and table reports.

Interactive Dashboard

The browser-based dashboard at http://localhost:8050 provides an interactive view of the results. The dashboard is built with Plotly Dash and provides real-time interactive exploration of results.

Oxonium Ion Co-occurrence Heatmap

Displays the fraction of one oxonium ion's spectra that also contain another oxonium ion. The matrix is asymmetric — "HexNAc in Hex" may differ from "Hex in HexNAc" because their total spectrum counts differ. Rows and columns are ordered by Jaccard similarity-based hierarchical clustering (average linkage), with a dendrogram shown on the left, grouping oxonium ions that tend to co-occur in the same spectra. The colour intensity (0–100%) indicates the degree of co-occurrence. Oxonium ions with no detected spectra are marked in grey.

Main Histogram — Mass Delta

Shows the distribution of glycan masses (precursor mass − peptide mass) across all identified glycopeptide spectra, binned at 0.1 Da resolution. The height of each bar represents the number of PSMs with that mass delta. Recurring mass deltas across different peptide sequences indicate genuine glycan modifications. Overlapping traces from different oxonium ions (and the untargeted search) can be toggled via checkboxes to compare which mass deltas are confirmed by diagnostic sugar fragments. Decoy traces can be shown for empirical false positive assessment.

Main Histogram — Precursor Offsets

Shows the distribution of mass differences between the intact precursor and high-mass fragment ions (>750 Da) in the decharged MS2 spectrum. Displayed as paired frequency histogram and summed intensity bar plot. These offsets represent sequential losses of monosaccharide units from the intact glycopeptide. Recurring offset values indicate specific monosaccharide masses. This analysis is independent of peptide identification and includes all oxonium-positive spectra, enabling glycan exploration even where sequence matching fails.

Child Plots

Clicking a bin in the main histogram generates three rows of child plots showing complementary data for the spectra in that bin. When mass delta is the main view, the child plots show precursor offsets, peptide offsets, and the raw m/z spectrum. Precursor offsets reveal monosaccharide losses from the intact glycopeptide. Peptide offsets (Y-ions − Y0) show sequential monosaccharide additions from the peptide backbone. The m/z spectrum shows the binned fragment ion distribution. Each is displayed as a frequency histogram paired with a summed intensity bar plot.

Glycoprotein Candidate Table

Displayed below the histograms when a mass delta or offset bin is selected. Shows all glycoprotein candidates from the untargeted search matching the selected bin, ranked by unique peptide count then PSM count. Each protein row shows: | Column | Description | |--------|-------------| | # | Rank by evidence strength | | Protein | Accession ID and description | | PSMs | Number of peptide-spectrum matches | | Peptides | Number of unique peptide sequences | | Med. tags | Median tag count — the median number of de novo tags that independently matched the same peptide per spectrum. Higher values indicate more confident sequence identification. | | Oxonium evidence | Coloured dots indicating which diagnostic oxonium ions were detected in this protein's spectra, using the same colours as the histogram traces. | Clicking a protein row expands it to reveal a peptide detail table with all individual PSMs: | Column | Description | |--------|-------------| | Peptide | Matched peptide sequence | | Scan # | MS2 scan number | | Δ Mass | Mass delta (glycan mass) | | Prec. mass | Precursor monoisotopic mass | | Pep. mass | Peptide monoisotopic mass (with carbamidomethylated cysteines) | | p-value | DirecTag JointpValue — combined statistical score for the sequence tag. Lower is better. Displayed with a colour-coded bar (green = low/good, red = high/poor). | | MzFidelity | DirecTag MzFidelity score — measures how closely the observed fragment masses match expected values. Lower is better. | | Complement | DirecTag Complement score — evaluates the presence of complementary fragment ion pairs. Higher is better. | | Intensity | DirecTag Intensity score — assesses the relative intensity of matched fragments. Higher is better. | | Tags | Number of de novo tags that matched this peptide for this spectrum. | | Unmod. | Whether SAGE also identified the unmodified version of this peptide (✓ or —). | | Unmod. scans | Scan numbers where the unmodified peptide was identified by SAGE. | | Oxonium | Per-scan oxonium ion presence as coloured dots. |

Oxonium Filter

Above the glycoprotein table, checkboxes allow filtering matches by oxonium ion presence. By default, no filter is applied and all untargeted search results are shown. Selecting one or more oxonium ions restricts the table to only scans where ALL selected ions are present (AND logic). The subtitle indicates the active view — e.g., "showing open search results" or "showing Hex, HexNAc filtered". This allows progressive refinement from the full untargeted search to high-confidence glycopeptide candidates confirmed by specific sugar fragments.

Excel Export

The "Export to Excel" button downloads an Excel file with two sheets:

• Protein summary — one row per protein with PSM count, unique peptides, median tag counts, and oxonium evidence
• Peptide details — all individual PSMs with full scoring metrics Sheet names reflect the active oxonium filter — e.g., "Protein summary (Hex)" or "Protein summary (open search)". Mass-Based Detection Limitations: This approach identifies sugars based on diagnostic oxonium ion masses, but cannot differentiate between isomeric sugars. For example, when a hexose (Hex) is detected, additional biochemical experiments or literature review would be required to determine whether it represents glucose, galactose, mannose, or another hexose isomer. The tool provides evidence of glycosylation and sugar mass, but structural characterization requires complementary techniques.

Other output Files

NovoGlycoX also generates the following outputs files:

Output/
  <mzml_name>/
    <mzml_name>_peptideshaker.sage.tsv       # SAGE results in PeptideShaker format
    <mzml_name>_ALL_GLYCO_peptideshaker.tsv   # Combined SAGE + glycopeptide results
    <mzml_name>_Open_search/
        Open_search_final_report.xlsx          # Open search Excel report
    <mzml_name>_<oxonium>/
        Ox_<oxonium>_final_report.xlsx         # Per-oxonium filtered Excel report

Each Excel report contains three sheets:

• SUMMARY_SHORT — grouped glycopeptide matches (one row per scan, best peptide-protein combination)
• SUMMARY_EXT — all individual tag matches before grouping
• OXONIUM_SCANS — all spectra that passed the filter (metadata only, no raw arrays) When SAVE_PLOTS_LOCALLY=True, static PNG histograms are saved in each output folder:
• *_mass_deltas.png — mass delta distribution
• *_precursor_offsets.png — precursor offset frequency histogram
• *_precursor_offsets_intensity.png — precursor offset summed intensity bar plot
• *_peptide_offsets.png — peptide offset distribution

Key Metrics

Tag Counts (Med. tags)

The number of de novo sequence tags from a single spectrum that independently matched the same database peptide. DirecTag generates up to 10 tags per spectrum; if 5 of those point to the same peptide, the tag count is 5. Higher values indicate more confident peptide identification, as multiple independent sequence fragments converge on the same answer. The median across all PSMs for a protein is reported in the summary table.

Mass Delta

The mass difference between the precursor ion and the identified peptide backbone (precursor mass − Y0 mass). This represents the total mass of the attached glycan modification. Genuine glycan modifications appear as recurring mass deltas across different peptide sequences from the same or different proteins.

Precursor Offsets

Mass differences between the intact precursor and high-mass fragment ions in the decharged spectrum (precursor − Y-ions). These correspond to sequential monosaccharide losses from the intact glycopeptide during fragmentation. Common prokaryotic monosaccharide masses include HexNAc (203.08 Da), Hex (162.05 Da), and dHex (146.06 Da).

Peptide Offsets

Mass differences between fragment ions above the Y0 ion and the Y0 mass itself (Y-ions − Y0). These represent sequential monosaccharide additions to the peptide backbone, providing complementary evidence to precursor offsets. The correlation between precursor and peptide offset patterns enhances confidence in glycan composition assignments.

Y0 Ion

The unmodified peptide ion — the peptide backbone after complete loss of the glycan. Its presence in HCD/CID spectra is characteristic of glycopeptide fragmentation due to preferential cleavage of glycosidic bonds. When VALIDATE_PEPTIDE_MASS=true (the default), NovoGlyco requires Y0 detection within 20 ppm for glycopeptide assignment, increasing confidence. Setting it to false disables this check, which can be useful for low-abundance glycopeptide discovery where Y0 ions may be weak or absent.

Oxonium Ions

Low-mass diagnostic fragment ions produced by monosaccharide fragmentation during HCD. Each monosaccharide generates a characteristic ion pair: the intact oxonium ion and its water loss fragment (−18.01 Da). Detection of these pairs with sufficient intensity provides direct evidence for the presence of specific sugar types, independent of peptide identification.

Troubleshooting

Common Issues "No raw or mzML file found in the selected folder" error

• Ensure you have placed an .mzML file in the Input directory
• RAW files are not supported directly - convert them to mzML format first using MSConvert
• Check file permissions and names (case sensitivity matters) Dashboard not accessible
• Verify that no other application is using port 8050 Interactive browser output appears very slowly, with long delays before interactive graphs and plots update
• Increase the bin size (>0.25 Da, best performance with 1 Da)
• Decrease sensitivity level (sensitivity levels of 0.1 % or lower can create many oxonium hits and slow down the browser based dashboard, use >0.1 % best performance at >0.5 %).
• Too large dataset for browser-based dashboard (e.g. data from Orbitrap Astral). Consider downsampling the data density with msconvert. Use low sensitivity levels (1%) and low bin width (1Da). ** "FileNotFoundError:[Errno 2] No such file or directory" during reporting**
• The max path length was exceeded, move the input and outputfolder at a lower level, closer to C:

5. License, data privacy, no warranty and contacts

NovoGlycoX is released under the Apache License 2.0. Copyright (c) 2026 Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. Please note that some of the functions and libraries used by NovoGlycoX may not share the same license as NovoGlycoX. If you want to use any of these in a different context, ensure that you obtain the appropriate licenses for the dependent libraries and tools. Dependencies and their licenses:

• Python: Python 3.x, open-source, https://www.python.org/
• Dash: MIT License, https://dash.plotly.com/
• Pyteomics: MIT License, https://pyteomics.readthedocs.io/
• pandas: BSD 3-Clause License, https://pandas.pydata.org/
• matplotlib: PSF License, https://matplotlib.org/
• scipy: BSD 3-Clause License, https://scipy.org/
• numpy: BSD 3-Clause License, https://numpy.org/
• Sage: MIT License, https://github.com/lazear/sage — Lazear, Michael R. "Sage: an open-source tool for fast proteomics searching and quantification at scale." Journal of Proteome Research 22.11 (2023): 3652-3659.
• Other Python Libraries: Please review the licenses for any other third-party packages used. Data/Privacy: NovoGlycoX does not collect, store, or transmit any personal data. It operates entirely on the local machine and does not interact with any external servers or services. All data processing and analysis occur locally. By using NovoGlyco, you consent to the software operating on your local machine as described above, and you are responsible for managing your own data and files. No Warranty Disclaimer: THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES, OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Citation

If you use this software in your research, please cite:

Šoić D. and Pabst M. NovoGlyco: mapping protein glycosylation in prokaryotes. bioRxiv. 2026.

Contacts

Dinko Šoić (soic@imsb.biol.ethz.ch) Martin Pabst (m.pabst@tudelft.nl)