Deep (Transfer) Learning for Peptide Retention Time Prediction

RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis

Python code to identify and calculate decomposition of materials using Raman spectroscopy

Targeted pipeline to quantify metabolomics datasets produced by QExactive and Triple Quadrupole Mass Specs.

Awesome papers and codes list of analytical chemistry-related deep learning methods

A Python utility for the processing and quantification of chromatography data

Data hub and data tool repository related to the NIST PFAS Program.

Deep Learning for Mass Spectra Quality Assessment

A Python package to plot fractional composition diagrams and pH-log c diagrams

Topino: A graphical tool for assessment of molecular-stream separations

Perform titration curves of any acid-base pair.

A capillary electrophoresis data extraction utility for Karat32 data files

Helper Functions For Dealing With GCMS and LCMS data from IonAnalytics

Direct Analysis in Real Time (DART) Mass Spectrometry Data Analysis

UHPLC-QqQ-MS/MS method development and validation with statistical analysis: Determination of raspberry ketone metabolites in mice plasma and brain

Decompose Thermo Gravimetrical Analysis (TGA) curves into simpler logistic curves representing mass-change events with a chemical interpretation. All of the analysis is performed with the TensorFlow library for the creation of a NN-analogous model and optimization.

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A Shiny R project to ease the statistical validation of analytical methods

Quantitative analysis of chemicals

This case serves as an illustration how data science can help analytical chemistry, in-field analysis and ecology. An additional point to be stressed is the reality of the subject case. The best practice for data scientists always consists in facing difficulties present in real cases – data cleaning, preparation, analysis of the data logic, stra…