Welcome to ModiFinder’s documentation!

ModiFinder is a powerful Python toolkit for mass spectrometry data analysis, specializing in site localization of structural modifications using MS/MS data.

Beyond Modification Finding

While ModiFinder excels at pinpointing where structural modifications occur in molecules, it’s also a comprehensive toolkit for:

  • Working with Mass Spectra: Parse USIs, fetch data from GNPS, and manipulate spectrum objects

  • Molecular Visualization: Draw molecules, spectra, structural comparisons, and modification heatmaps

  • Data Processing: Read/write MGF files, normalize spectra, and batch process MS data

  • Compound Management: Create and manipulate compound objects from SMILES, InChI, or GNPS identifiers

  • Network Analysis: Retrieve and compare spectra from public repositories

Whether you’re analyzing a single modification site or building a large-scale MS data processing pipeline, ModiFinder’s utilities can help streamline your workflow.

Quick Start

Install ModiFinder:

pip install modifinder

Get started with a simple example:

from modifinder import Compound
from modifinder.utilities import visualizer as viz

# Fetch compound from GNPS
compound = Compound("CCMSLIB00010113829")

# Draw the structure
img = viz.draw_molecule(compound.structure)

# Access spectrum data
print(f"{len(compound.spectrum.mz)} peaks")

Key Features

🎯 Modification Site Prediction

Identify the most likely modification sites in unknown compounds using MS/MS data

🔬 Spectrum Analysis

Parse, normalize, and compare mass spectra from various sources

🎨 Rich Visualization

Create publication-quality figures of molecules, spectra, and structural comparisons

📊 Data Integration

Seamlessly work with GNPS data, MGF files, and USIs

🧪 Flexible Objects

Compound and Spectrum classes that work with your existing data formats

Note

This project is under active development.

Citing

ModiFinder: Tandem Mass Spectral Alignment Enables Structural Modification Site Localization

Mohammad Reza Zare Shahneh, Michael Strobel, Giovanni Andrea Vitale, Christian Geibel, Yasin El Abiead, Neha Garg, Berenike Wagner, Karl Forchhammer, Allegra Aron, Vanessa V Phelan, Daniel Petras, and Mingxun Wang

Journal of the American Society for Mass Spectrometry 2024 35 (11), 2564-2578

DOI: 10.1021/jasms.4c00061

License

Academic Software License: © 2024 UCR (“Institution”). Academic or nonprofit researchers are permitted to use this Software (as defined below) subject to Paragraphs 1-4:

1. Institution hereby grants to you free of charge, so long as you are an academic or nonprofit researcher, a nonexclusive license under Institution’s copyright ownership interest in this software and any derivative works made by you thereof (collectively, the “Software”) to use, copy, and make derivative works of the Software solely for educational or academic research purposes, and to distribute such Software free of charge to other academic or nonprofit researchers for their educational or academic research purposes, in all cases subject to the terms of this Academic Software License. Except as granted herein, all rights are reserved by Institution, including the right to pursue patent protection of the Software.
2. Any distribution of copies of this Software -- including any derivative works made by you thereof -- must include a copy (including the copyright notice above), and be made subject to the terms, of this Academic Software License; failure by you to adhere to the requirements in Paragraphs 1 and 2 will result in immediate termination of the license granted to you pursuant to this Academic Software License effective as of the date you first used the Software.
3. IN NO EVENT WILL INSTITUTION BE LIABLE TO ANY ENTITY OR PERSON FOR DIRECT, INDIRECT, SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS, ARISING OUT OF THE USE OF THIS SOFTWARE, EVEN IF INSTITUTION HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. INSTITUTION SPECIFICALLY DISCLAIMS ANY AND ALL WARRANTIES, EXPRESS AND IMPLIED, INCLUDING, BUT NOT LIMITED TO, ANY IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE SOFTWARE IS PROVIDED “AS IS.” INSTITUTION HAS NO OBLIGATION TO PROVIDE MAINTENANCE, SUPPORT, UPDATES, ENHANCEMENTS, OR MODIFICATIONS OF THIS SOFTWARE.
4. Any academic or scholarly publication arising from the use of this Software or any derivative works thereof will include the following acknowledgment:  The Software used in this research was created by [INSERT AUTHOR NAMES] of UC Riverside. © 2024 UCR.

Commercial entities: please contact mingxun.wang@cs.ucr.edu or tp@ucr.edu for licensing opportunities.

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