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MotifQuest

An Automated Pipeline for Motif Database Creation to Improve Peptidomics Database Searching Programs

MotifQuest, our novel motif database generation algorithm, is designed to work in partnership with EndoGenius, a program optimized for database searching of endogenous peptides and that is powered by a motif database to capitalize on biological context to produce identifications. MotifQuest aims to quickly develop motif databases without any prior knowledge, a laborious task not possible with traditional sequence alignment resources.

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Endogenius
An Open-Source Software for Optimized Neuropeptide Identification from Mass Spectrometry Datasets

EndoGenius, a database searching strategy designed specifically for elucidating neuropeptide identifications from mass spectra by leveraging optimized peptide–spectrum matching approaches, an expansive motif database, and a novel scoring algorithm to achieve broader representation of the neuropeptidome and minimize reidentification.

MSI Parser
An Open-Source Software for Analysis of Single-Cell Mass Spectrometry Imaging Data

MSI-Parser is a program designed to define regions of interest (ROI) for single cell mass spectrometry analysis, followed by average spectra extraction, and machine learning classification of cell types.

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HyPep

An Open-Source Software for Identification and Discovery of Neuropeptides Using Sequence Homology Search

HyPep is an open-source Python based algorithm designed for hybrid analysis of neuropeptide mass spectral data through sequence homology searching and accurate mass matching. HyPep aligns de novo sequenced peptides, generated through PEAKS software, with neuropeptide database sequences and identifies neuropeptides based on the alignment score. Users can upload their data files following the instructions in the manual and the results can be downloaded for use.

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Metandem

A Data Analysis Tool for Isobaric Labeling-based Metabolomics

Metandem is a free online data analysis platform for mass spectrometry-based isobaric labeling metabolomics. It allows users to upload and process MS or hyphenated MS data files for isobaric-labeling-based quantitative and qualitative metabolomics analyses, including feature extraction, metabolite quantification, metabolite identification, batch processing of multiple data files, parameter optimization, median normalization, and statistical analysis. Results can be downloaded or visualized online.

Cite
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PRESnovo

Prescreening prior to de novo sequencing

Prescreening Prior to de novo sequencing tool using peptide motif homology for improved de novo sequencing of peptides.  PRESnovo works by searching tandem mass spectrometry data against a predefined motif database consisting of known peptides from the species of interest or related species. The software assigns the most probable motif to each precursor using a sophisticated scoring function. Results can then be used in conjunction with other de novo sequencing software to improve the accuracy of the de novo sequences.

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Proteome-wide and matrisome-specific alterations during human pancreas development and maturation

In this study, we apply mass spectrometry-based quantitative proteomics strategies using N,N-dimethyl leucine isobaric tags to delineate proteome-wide and ECM-specific alterations in four age groups: fetal (18-20 weeks gestation), juvenile (5-16 years old), young adults (21-29 years old) and older adults (50-61 years old). We identify 3,523 proteins including 185 ECM proteins and quantify 117 of them. The manuscript can be found below and the data may be viewed interactively via our custom webapp.

Crustacean Neuropeptide Database

De Novo Neuropeptide Database

This database contains all known neuropeptides present in several decapod crustacean species. The database consists of sequences obtained in-house via de novo sequencing, publicly-available data, and sequences reported in the literature using in silico prediction.  This database has been used for the identification of neuropeptides in crustacean tissue and circulating fluid.

More coming soon!

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Li Research Group

 University of Wisconsin Madison

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