"/>Research area

Computational Proteomics

From spectra to systems — identifying and quantifying proteins and their modifications across conditions.

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Overview

What this area is.

Proteins are where genotype becomes phenotype. We process mass-spectrometry data to identify and quantify proteins and peptides, then test which ones change and what that means biologically.

Differential abundance, post-translational modifications and pathway enrichment turn raw spectra into systems-level understanding of protein expression and signalling.

Tools & technologies

MaxQuantFragPipePerseusSkylinelimmaSTRINGReactome
Abundance volcanoDifferentially abundant proteins.
Protein networkInteraction and complex membership.
Capabilities

What we do.

Core methods we apply in computational proteomics.

Spectra processing

Peak picking, calibration and feature detection.

Identification & quant

Peptide/protein ID and label-free or labelled quantification.

Differential abundance

Robust statistics for changing proteins.

PTM analysis

Phosphorylation and other modification mapping.

Pathway & enrichment

Biological interpretation of protein changes.

Systems integration

Linking proteomics to other omic layers.

Workflow

From data to insight.

How a computational proteomics project flows end to end.

01

MS run

peptide spectra

02

Search

peptide–spectrum match

03

Quantify

protein abundance

04

Test

differential analysis

05

PTMs

modification sites

06

Interpret

pathways & systems

Visual analytics

Publication-grade figures.

Interactive, live-rendered visualisations used in computational proteomics.

Abundance volcanoDifferentially abundant proteins.
Protein networkInteraction and complex membership.
Sample embeddingProteomic similarity across samples.
Feature matrixProtein/PTM events across conditions.
Focus

Where we go deep.

Quantitative proteomics

Accurate, reproducible protein-level quantification.

Post-translational modifications

Mapping the regulatory layer beyond abundance.

Systems & signalling

From protein lists to pathway-level mechanism.

Insights

Questions we answer.

A few of the things people ask about computational proteomics — and our short answers. Ask CGB-AI for more.

Why proteomics if you have RNA?

mRNA and protein levels often diverge; proteins (and their modifications) are closer to function and drug action.

What are PTMs?

Post-translational modifications like phosphorylation switch protein activity — a regulatory layer invisible to the genome alone.

Selected research

Publications in Computational Proteomics.

Drawn from our full record of 173 papers, filtered to this area.

Browse all publications →

Start a computational proteomics project.

Tell us the biological question and the data you have — we will map out an approach.

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