efficion

A program for predicting mass spectrometry relevant analyte ionization efficiency

https://github.com/mitkeng/efficion

Science Score: 57.0%

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Repository

A program for predicting mass spectrometry relevant analyte ionization efficiency

Basic Info

Host: GitHub
Owner: mitkeng
License: mit
Language: Python
Default Branch: main
Homepage:
Size: 2.9 MB

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Stars: 0
Watchers: 1
Forks: 1
Open Issues: 0
Releases: 0

Created almost 2 years ago · Last pushed almost 2 years ago

Metadata Files

Readme License Citation

efficION: ionization efficiency prediction

Introduction

efficION is a python program for predicting mass spectrometry relevant compound ionization efficiency. Two interacting deep neural network models are implemented for log ionization efficiency (logIE) value prediction and error attenuation; one sequential model (i.e., model 1) predicts logIE while a second sequential model (i.e., model 2) attempts to correct for residual logIE prediction error produced by model 1.

Functionality

The program supports single logIE query or batch chemical logIE queries. For single query, either a canonical SMILE or chemical name is applicable, along with a required solution pH value; for batch queries, the following csv file data format is required: || SMILES| pH| |--| ------------- | ------------- | |1| C1=CNC(=O)NC1=O| 7.2| |n| ... | ...|

Upon completion of a task a tabulated result similar to the table below is saved to a csv file.

|| Chemical Name| SMILE| logIE| |---|------|-----|----| |1| 1H-pyrimidine-2,4-dione | C1=CNC(=O)NC1=O |0.49364716| |n| ... | ...|...|

Currently, efficION is only appropriate for predicting logIE relating to the ESI ionization technique.

Performance

focus focus

Requirement

Google account needed to access Google Colab notebook.

Support

To create a small batch queries csv input file ad hoc: ```twig import pandas as pd

try: !touch small_batch.csv except: pass

columnnames=["SMILES","pH"] smallbatch=pd.readcsv("smallbatch.csv", names=column_names)

complist = #list of compounds -> ["C(=O)=O", "O"] pHlist = #list of corresponding pH values -> [2.7, 7.2]

smallbatch['SMILES'] = complist smallbatch['pH'] = pHlist

smallbatch.tocsv("small_batch.csv", index=False) ```

Accessibility

to access the efficION platform. focus

Reference

Liigand, J., Wang, T., Kellogg, J. et al. Quantification for non-targeted LC/MS screening without standard substances. Sci Rep 10, 5808 (2020). https://doi.org/10.1038/s41598-020-62573-z

Owner

Name: Mithony Keng
Login: mitkeng
Kind: user
Company: Michigan State University

Repositories: 1
Profile: https://github.com/mitkeng

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: efficION
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Mithony
    family-names: Keng
    orcid: 'https://orcid.org/0000-0002-9850-0120'
    affiliation: Michigan State University
    email: kengmith@msu.edu
repository-code: >-
  https://https://github.com/mitkeng/efficION/new/main/CITATION.cff
url: 'https://github.com/mitkeng/efficION'
abstract: >-
  A program for predicting ESI ionization efficiency 
keywords:
  - Mass spectrometry
  - ESI
  - Ionization efficiency
  - Machine learning
license: MIT
version: '1.0'
date-released: '2024-07-08'

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