PROTEOMICS
Functional Proteome Profiling
At Nucleome, we decode the functional landscape of biological systems through high-resolution proteomic analysis. Our solutions enable protein-level insights into cellular
processes, revealing not just what is encoded in the genome, but what is actively
expressed, modified, and functionally executed within complex biological environments.
From comprehensive mass spectrometry-based proteome profiling to targeted protein
analysis, we transform complex proteomic data into functional, mechanistic, and
clinically relevant insights.
Partner with Nucleome to explore the proteome with precision, depth, and impact—
from fundamental biology to clinical and translational applications..
Why Proteomics Matters
While the genome defines biological potential, the proteome reflects functional reality, capturing the proteins that are actively expressed, modified, and interacting within cells.
Proteomics enables:
- Quantification of protein expression levels and dynamic changes across conditions.
- Identification of post-translational modifications (PTMs) such as phosphorylation, acetylation, and ubiquitination.
- Characterization of protein–protein interactions and signaling pathways.
- Discovery of functional biomarkers for disease diagnosis, prognosis, and therapeutic response.
- Insights into cellular mechanisms, pathway regulation, and phenotype manifestation.
At Nucleome, we go beyond protein identification to deliver functional, systems-level insights that bridge molecular biology with clinical and translational applications.
Next-Generation Proteomics Ecosystem
At Nucleome, our proteomics ecosystem integrates advanced mass spectrometry–based workflows and quantitative proteomic strategies to comprehensively profile the functional protein landscape. We enable high-resolution analysis of protein abundance, post-translational modifications (PTMs), and protein–protein interactions, capturing the dynamic state of cellular systems beyond the genome and transcriptome.
Our workflows combine data-dependent and data-independent acquisition (DDA/DIA) approaches for unbiased proteome coverage, along with targeted proteomics for precise quantification of selected proteins and biomarkers. These strategies support both label-free and isobaric labeling methods, enabling robust comparative analysis across conditions and large sample cohorts.
This integrated framework allows precise characterization of protein expression dynamics, signaling pathways, and regulatory networks, linking molecular function to phenotype, disease mechanisms, and therapeutic response. By integrating proteomics with other omics layers, we deliver systems-level, functionally actionable insights for research, clinical, and translational applications.
Bioinformatics & Data Analysis
At Nucleome, we implement advanced computational pipelines to transform raw proteomics data into quantitative, high-resolution insights into protein expression and function. Our workflows begin with data preprocessing, spectral processing, and peptide-spectrum matching, followed by accurate
protein identification and quantification
across samples and conditions.We perform comprehensive downstream analyses including differential protein expression analysis, post-translational modification (PTM) mapping, and protein–protein interaction (PPI) network analysis, enabling deeper understanding of cellular signaling and functional pathways. Quantitative strategies support both label-free and labeled approaches for robust comparative studies.
Functional interpretation is driven through pathway enrichment (KEGG, Reactome), gene ontology (GO) analysis, and systems-level network modeling, linking proteomic changes to biological processes and disease mechanisms.
By integrating proteomics with genomics, transcriptomics, and clinical data, we deliver multi-omics, systems-level insights for biomarker discovery, disease stratification, and precision medicine applications.
Our Key Solutions
Global (Discovery) Proteomics
Unbiased, large-scale profiling of the entire proteome to identify and quantify thousands of proteins across biological samples. Enables comprehensive coverage of protein expression and functional states.
Why it should be done: Provides a global view of protein dynamics, essential for understanding biological systems, disease mechanisms, and discovering novel protein signatures.
Quantitative Proteomics
Accurate quantification of protein abundance changes across conditions using label-free or multiplexed strategies, enabling high-throughput comparative analysis
Why it should be done: Critical for identifying differentially expressed proteins, supporting biomarker discovery and pathway-level insights in complex biological systems.
Post-Translational Modification (PTM) Analysis
Comprehensive identification and mapping of protein modifications such as phosphorylation, acetylation, and ubiquitination that regulate protein function.
Why it should be done: Essential for understanding cell signaling pathways and regulatory mechanisms, particularly in diseases like cancer and metabolic disorders.
Protein–Protein Interaction (PPI) Analysis
Characterization of protein interaction networks and complexes to understand functional relationships within the cell.
Why it should be done: Reveals pathway connectivity and molecular mechanisms, enabling deeper insights into cellular processes and disease biology.
Biomarker Discovery & Validation
Identification and validation of protein biomarkers associated with disease states, progression, or therapeutic response.
Why it should be done: Supports early diagnosis, prognosis, and precision medicine, improving clinical decision-making and treatment outcomes.