Proteomics is the large-scale study of proteins, their expression levels, modifications, interactions, and functional roles across biological systems. As the key effectors of cellular activity, proteins provide dynamic insight into phenotype regulation, signaling networks, and disease mechanisms. Compared to genomics or transcriptomics, proteomics directly reflects the current physiological state of cells, tissues, or organisms.
Creative Proteomics delivers end-to-end proteomics solutions tailored for research in drug discovery, biomarker development, pathway elucidation, and more. Our platform integrates high-resolution mass spectrometry, advanced fractionation strategies, and AI-assisted bioinformatics, enabling quantitative and qualitative profiling across nearly all proteoforms.
Flexible solutions for deep discovery, high-throughput screening, organelle mapping, and targeted validation.
Platform: Orbitrap Exploris 480 + nanoLC
This is our go-to platform for in-depth, unbiased proteome profiling. Equipped with high-resolution MS and low-femtomole detection sensitivity, it captures >10,000 proteins per sample and is ideal for:
With advanced label-free or TMT-based workflows, this platform supports comprehensive proteomic exploration from whole-cell lysates, tissues, or biofluids.
Platform: timsTOF Pro + Evosep One
Optimized for large sample cohorts, this configuration combines fast chromatographic gradients with trapped ion mobility separation (TIMS) for high-resolution, rapid quantitation. Perfect for:
Our pipeline ensures inter-batch consistency and minimal instrument downtime, making it ideal for large-scale comparative studies.
Platform: Q Exactive HF-X + proprietary fractionation kits
When spatial context matters, this platform enables precise localization of proteins within specific organelles. Using differential centrifugation, affinity purification, and contamination-reducing workflows, we can cleanly isolate:
This approach is critical for studying compartmentalized signaling, organelle-specific PTMs, or protein trafficking. Coupled with subcellular annotation algorithms, it delivers a spatially resolved proteomic landscape.
Platform: QTRAP 6500+ / TripleTOF 6600
For clients requiring precise quantification of predefined protein panels, our targeted proteomics platform offers absolute quantitation using:
Ideal for:
With custom assay development and high dynamic range detection, this platform provides robust, reproducible measurements that integrate seamlessly with previous discovery datasets.
No matter which platform you choose, all services include:
💡 Not sure which platform fits your study?
Let our scientists match your biological question with the right technology. Whether you're profiling 5 samples or 500, we help you get from protein to insight—efficiently and accurately.
Solution:
Label-Free or TMT-Based Global Proteomics
Capture global protein expression and quantify differential changes across conditions using high-depth Orbitrap workflows. Ideal for phenotypic screening and biomarker discovery.
Solution:
Subcellular Fractionation + LC-MS/MS
Isolate nucleus, mitochondria, or lysosomes and identify spatially resolved protein patterns using organelle-targeted proteomics with GO-based localization prediction.
Solution:
Serum-Free Culture + EV Isolation + Proteomics
Characterize cytokines, extracellular matrix proteins, or exosome cargo with specialized workflows to reduce serum background and enhance secretome depth.
Solution:
Enrichment of Phospho-, Acetyl-, Ubiquitin-, or Methyl-Proteins
Use targeted LC-MS/MS to detect regulatory modifications and signaling shifts, supported by site-level annotation and pathway integration.
Solution:
TMT 10/16plex Quantitative Proteomics
Simultaneously analyze 6–16 samples with precise batch correction and replicate normalization for robust time-course or dose-response profiling.
Solution:
Co-IP/MS, Cross-Linking, or Proximity Labeling (BioID/APEX)
Reveal physical interactions or co-complex assembly using structure-aware proteomics strategies and confidence scoring of interactome maps.
Solution:
Integrated Proteomics + Machine Learning
Use statistical and AI-driven ranking models to identify high-confidence protein biomarkers from large datasets, accelerating preclinical-to-clinical transitions and enhancing candidate reproducibility.
Solution:
Ultra-Low Input Proteomics with NanoLC-MS/MS
Analyze limited samples such as fine-needle biopsies, sorted cell subtypes, or isolated organelles with as little as 1–5 µg total protein, without compromising depth or data quality.
Ultra-High Proteome Coverage
Subcellular & Organelle-Specific Resolution
High Analytical Sensitivity
Advanced Bioinformatics & Subcellular Annotation
Sample Reception & Quality Assessment
Incoming samples are logged, photographed, and assessed for concentration, integrity, and suitability. Optional buffer exchange or concentration performed as needed.
QC: Protein quantification (BCA), SDS-PAGE validation
High-Resolution LC-MS/MS Acquisition
Peptides are separated using nanoLC and analyzed on Orbitrap, timsTOF, or QTRAP systems depending on the platform selected.
QC: MS performance calibration, internal standards, spike-ins
Subcellular Fractionation (Optional)
If organelle-specific analysis is requested, samples are processed via density centrifugation or affinity purification to isolate nuclei, mitochondria, ER, or exosomes.
QC: Organelle marker western blot, cross-contamination check
Data Processing & Bioinformatics
Spectral files are searched with appropriate database algorithms (e.g., MaxQuant, DIA-NN), filtered by FDR, and processed through our custom bioinformatics suite.
QC: ID confidence (FDR <1%), replicate correlation (R² ≥ 0.98)
Protein Extraction, Digestion & Labeling
Proteins are extracted, denatured, reduced, alkylated, and digested (trypsin or LysC). TMT/SILAC labeling is applied if multiplexed analysis is required.
QC: Digestion efficiency, labeling yield validation
Result Interpretation & Reporting
Clients receive a detailed report including quantitative protein matrices, pathway enrichment, subcellular localization, PTM annotation, and optional visual dashboards.
Deliverables: Raw MS files, processed data, annotations, plots, and custom visuals
| Sample Type | Minimum Input | Recommended Conditions & Notes |
|---|---|---|
| Cultured Cells | ≥ 5 × 10⁶ cells | Use fresh or snap-frozen pellets. For secretome analysis, culture in serum-free medium. |
| Animal or Plant Tissues | ≥ 50 mg | Snap-frozen preferred. Avoid freeze-thaw cycles. Homogenization performed prior to protein extraction. |
| Organelle Fractions | ≥ 10 µg total protein | Provide details on isolation method or request Creative Proteomics to perform fractionation. |
| Conditioned Media | ≥ 500 µL (serum-free) | Suitable for secretome or exosome proteomics. Media should be free of serum proteins. |
| Exosome Pellets | ≥ 5 µg total protein | Isolated using ultracentrifugation or kit-based methods. DNase/RNase pre-treatment optional. |
| Biofluids (e.g., plasma) | ≥ 50 µL | Plasma/serum samples should be EDTA- or heparin-treated. For deep coverage, depletion may be advised. |
| FFPE Tissue Sections | ≥ 5 sections (10 µm thick) | Must be freshly cut. Provide H&E reference if spatial localization is needed. |
Additional Notes:
All deliverables are tailored to your experimental design and output preferences, ensuring clarity, traceability, and scientific usability.
Representative demo results from subcellular proteomics analysis, including differential expression matrix, subcellular localization profiling, phosphorylation motif enrichment, and pathway-level biological interpretation.
Case 1: Diurnal Nuclear Proteome Remodeling in Mouse Liver
Case 2: Hypoxia-Driven Remodeling of the Mitochondrial Proteome
How do you ensure organelle purity during subcellular proteomics?
We use optimized differential centrifugation, gradient ultracentrifugation, and affinity purification combined with western blot validation of organelle-specific markers. Cross-contamination is evaluated using quantitative enrichment scoring and GO-based localization analysis.
Can you distinguish between cytosolic contaminants and truly secreted proteins in secretome studies?
Yes. We employ serum-free culture, EV depletion, and use tools like SignalP, SecretomeP, and WoLF PSORT for secretion pathway annotation. Additionally, contamination is flagged via intracellular marker abundance and excluded during downstream analysis.
How do you deal with batch effects in large-scale TMT or label-free projects?
We embed internal pooled references and run bridge channels for TMT-based studies. For label-free experiments, we use spike-in standards and global normalization strategies. Downstream correction includes ComBat and variance-stabilizing transformations to remove technical drift.
Can you identify and annotate isoforms or proteoforms?
Yes. When appropriate sequence databases are available, we support isoform-level identification using top-down or bottom-up integration pipelines. We also offer proteoform inference via PTM co-localization and alternative splicing patterns.
How do you handle uncharacterized or novel proteins in non-model species?
For non-model organisms or custom genomes, we support proteogenomics workflows using custom FASTA databases derived from RNA-seq or genome annotation. Novel peptides can be mapped to reference scaffolds and functionally annotated via orthology.
Can you help prioritize biomarker candidates from large datasets?
Yes. We use machine learning–based scoring (e.g., random forest, LASSO, SVM) to rank protein candidates based on expression stability, condition specificity, and functional relevance. This helps streamline validation and clinical translation.
What strategies do you use to increase proteome depth in challenging samples?
We combine multi-dimensional fractionation (Hi-pH reversed-phase, SCX), low-flow nanoLC, and longer gradients to improve peptide separation. For extremely complex matrices, we also support OFFGEL fractionation or organelle pre-enrichment.
Is your platform compatible with single-cell proteomics strategies?
While we do not offer true single-cell proteomics at this stage, we support ultra-low input workflows down to 1 µg total protein, which is suitable for sorted cell populations or rare tissue regions. Please contact us for project-specific feasibility.
| Bioinformatics Data Analysis Components | Description |
|---|---|
| Quantitative Proteomics Analysis | - Protein Abundance: Quantify protein levels within subcellular compartments, enabling relative expression comparisons. - Differential Expression: Identify significantly altered proteins using statistical methods, aiding in biomarker or target discovery. - Hierarchical Clustering: Organize proteins into clusters with similar expression patterns to unveil functional groups. |
| Post-translational Modification (PTM) Analysis | - PTM Identification: Identify and characterize various PTMs (e.g., phosphorylation, glycosylation) to unravel regulatory mechanisms. - Site Localization: Pinpoint the exact amino acid residues modified by PTMs for precise functional insights. |
| Functional Analysis | - Gene Ontology (GO) Enrichment: Categorize proteins based on biological processes, molecular functions, and cellular components, revealing functional roles. - Functional Annotation: Annotate proteins with known functions to explore their involvement in specific cellular processes or diseases. - Pathway Enrichment: Identify enriched biological pathways among subcellular proteins to understand functional context. |
| Interaction Analysis | - Protein-Protein Interaction (PPI) Analysis: Build protein-protein interaction networks to uncover key players and pathways within subcellular structures. |
| Subcellular Localization Prediction | - Subcellular Localization Prediction: Predict the specific subcellular compartments where proteins are likely to reside, enhancing functional understanding. |
| Differential Gene Expression Analysis | - Identification of Differentially Expressed Genes: Analyze gene expression data to identify genes showing significant expression changes within subcellular compartments. |
| Biomarker Discovery | - Identification of Potential Biomarkers: Explore the dataset for proteins that may serve as potential biomarkers for diseases or biological processes. |
| Multi-Omics Integration | - Integration with Other Omics Data: Combine subcellular proteomics data with other omics data types, such as genomics or metabolomics, for a comprehensive systems biology approach. |
| Subcellular Protein Distribution Visualization | - Data Visualization: Utilize visualization tools to create subcellular protein distribution maps, enhancing the understanding of protein spatial localization. |
From System to Subcellular: Your Proteomics Partner
At Creative Proteomics, we bring together cutting-edge instrumentation, proprietary workflows, and experienced bioinformatics teams to offer not just protein lists, but functional, localized, and integrated protein insights. Whether you aim to track stress-induced proteome changes, decode cell signaling, or discover novel subcellular biomarkers, we deliver the resolution and reliability your research demands.
→ Get in touch now to customize your proteomics project. Let's turn your proteins into discoveries.
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