Find Studio

pFind pLink
pGlyco pNovo

Proteins are vital parts of living organisms, as they are the main components of the physiological metabolic pathways of cells. While proteomics generally refers to the large-scale experimental analysis of proteins, it is often specifically used for protein purification and mass spectrometry which is an analytical technique that measures the mass-to-charge ratio of charged particles.

pFind Studio is a computational solution for such mass spectrometry-based proteomics. It germinated in 2002 in Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China. We call ourselves "pFinders". Our goal is to study bioinformatics algorithms and to develop easy-to-use software tools to help answer biological questions.

What's New

Nov 4, 2023 - Dr. Wen-Feng Zeng introduced his research and life status, and his return to Beijing led to a joyful reunion of pfinders!


Oct 17, 2023 - Professor Hao Chi taught a proteomics data analysis course at the Yanqi Lake Campus of the University of Chinese Academy of Sciences.


Sep 23-27, 2023 - pFinders attended the 12th CNHUPO and learned a lot. Wang Kai-Fei and Peng Ya-Ping won the Poster Award. And during these days, pFinders took the opportunity to visit the Chengdu Giant Panda Breeding& Research Base to see cute pandas together.

Software

pFind is a search engine for peptide and protein identification via tandem mass spectrometry. [download...]




pLink is a tool dedicated for the analysis of chemically cross-linked proteins or protein complexes using mass spectrometry.
[download...]




pNovo+ is a de novo peptide sequencing algorithm using complementary HCD and ETD tandem mass spectra. [download...]

Benchmark

We participated in the ABRF iPRG study with pFind developed by our group in the past few years.



"The mission of the ABRF iPRG (formerly the Bioinformatics Committee) is to educate ABRF members and the scientific community on best application and practice of bioinformatics toward accurate and comprehensive analysis of proteomics data."


We believe it is advantageous to improve our algorithms, software tools and strategies for proteome informatics.
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