Proteomics & Post-Translational Modification Analysis

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Overview

Proteomics measures what transcriptomics only implies. We process quantitative mass spectrometry data — label-free, TMT and DIA — from search and quantification through statistical testing to pathway interpretation, and we handle post-translational modification data including phosphorylation, acetylation, ubiquitination, lactylation, succinylation and palmitoylation. Modification analysis is treated as a distinct problem, with site localisation confidence and occupancy normalisation handled explicitly rather than folded into protein-level results.

Schematic: raw reads become a quantified matrix, then tested differences, then annotated populations — with the statistics matched to the study design.

Key Advantages

Site Localisation Confidence Reported

Modification sites are delivered with localisation probability, so a site placed ambiguously between two adjacent residues is not presented as if it were certain.

Occupancy Separated From Abundance

Modification changes are normalised to protein-level abundance where the data permits, distinguishing genuine regulation from a protein simply being more present.

Missing Values Handled Deliberately

Imputation strategy is chosen for the missingness mechanism and reported, since proteomics conclusions are notoriously sensitive to this choice.

Network-Level Interpretation

Results are mapped onto interaction networks, kinase–substrate relationships and pathways, which converts a protein list into a mechanistic account.

Where This Service Is Used

Comparing protein abundance between treatment conditions or disease states

Mapping signalling changes through phosphoproteomic analysis after perturbation

Identifying interaction partners from pulldown or proximity labelling experiments

Characterising a drug mechanism of action at the protein level

Studying emerging modifications such as lactylation in a metabolic or disease context

Methods and Techniques Applied

Raw data processing, database search and false discovery rate control at peptide and protein level

Quantification for label-free, isobaric labelling and data-independent acquisition workflows

Normalisation, batch correction and missing value assessment with a documented imputation strategy

Differential abundance testing with appropriate models and multiple testing correction

Modification site identification with localisation scoring and occupancy normalisation

Functional interpretation: pathway enrichment, kinase–substrate inference and network mapping

What We Need From You

Raw mass spectrometry files or a search-engine output table, with the acquisition method described

Sample metadata including group, batch, labelling scheme and any technical replication

The organism and, where relevant, a preferred sequence database or custom construct sequences

The biological question and the comparisons that matter

What You Receive

Protein and peptide identification and quantification tables with quality metrics

Differential abundance results with statistics and effect sizes

Modification site tables including localisation probability and occupancy where computable

Pathway, network and kinase activity inference results

Publication-quality figures, methods text and reproducible analysis code

What We Compute and Report

Protein and peptide identifications with false discovery rate control at both levels

Quantitative abundance matrices with normalisation and batch assessment documented

Differential abundance statistics with effect sizes and multiple-testing correction

Modification site tables with localisation probability and occupancy where computable

Pathway, network and kinase activity inference results

Interpretation and Limitations

Computational predictions prioritise hypotheses; they do not independently establish binding, biological activity, therapeutic efficacy, safety or clinical validity. Performance depends on input quality, target class, the structural evidence available and the applicability domain of the selected methods. Scores used for ranking are comparative devices and should not be read as measured quantities. All deliverables are for research use only and are not intended for diagnostic or therapeutic use.

Specifications

Item	Specification	Notes
Workflows	LFQ, TMT/iTRAQ, DIA	Including PRM and MRM targeted data
Modifications	Phospho, acetyl, ubiquitin, lactyl and others	Enrichment strategy affects achievable depth
Typical turnaround	2–5 weeks	Modification analyses at the longer end
Output	Tables, figures, code	With FDR and quality metrics documented

Service Workflow

Step 01

Scientific Consultation

We discuss the objective, the decision it supports and the data you hold. Nothing is quoted before we understand what the result has to answer.

Step 02

Feasibility Review

We check that the data, target class and available structural evidence can support the proposed approach, and say plainly where they cannot.

Step 03

Technical Proposal

Scope, methods, deliverables, timeline and price are confirmed in writing, together with the limitations we expect to report.

Step 04

Computation and QC

The analysis runs on pinned tool versions in a containerised environment, with quality checkpoints and method comparison where that is informative.

Step 05

Report and Follow-Up

You receive the ranked results, the documented methods, the limitations and a proposed validation plan, plus support in interpreting them.

Is This the Right Service for You?

Choose this service when

Protein-level change must be established rather than inferred from transcripts

Signalling changes after perturbation need mapping at modification-site resolution

Interaction partners from pulldown or proximity labelling need rigorous analysis

Consider another service when

Transcript-level change is sufficient and cheaper

Bulk & Single-Cell RNA-Seq Analysis

Small molecule metabolites are the readout

Metabolomics & Mass Spectrometry Analysis

What Goes Wrong, and How We Handle It

The failure modes that produce confident-looking results which do not survive the next experiment. Each one is designed against rather than discovered afterwards.

Occupancy is normalised to protein level where the data allows, separating regulation from a protein simply being more abundant.

Case Studies

The situation

Phosphosite intensities dropped sharply after treatment and the team attributed it to pathway inhibition.

What the work involved

Protein-level abundance was quantified in parallel, occupancy was normalised against it, and kinase activity was inferred from the corrected site-level changes.

What came back

Roughly a third of the apparent signalling changes tracked protein degradation rather than reduced phosphorylation. The corrected set produced a cleaner and different kinase activity profile.

Illustrative of the shape this work takes. Details are generalised, no client or target is identified, and scope and outcome vary with the system in question.

Questions We Are Asked Before Scoping

Note: ICDMO delivers computational (in silico) services. Results prioritise hypotheses for testing; they do not by themselves establish binding, biological activity, efficacy or safety. All deliverables are for research use only and are not intended for diagnostic or therapeutic use. Downstream experimental work is scoped separately and executed through qualified partners.

Get in Touch
about Proteomics & Post-Translational Modification Analysis

Tell us about the target, the data you hold and the decision the result needs to support. A scientist reviews every enquiry and replies within one business day.

Feasibility reviewed before any scope or price is fixed

Methods, parameters, confidence and limitations in every report

Confidentiality agreement available before data is shared