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Cancer Systems Biology Internship Topics

Browse all focused areas across all internship categories under this field.

Cancer Systems Biology Internships with Accommodation

Choose an internship topic, then explore accommodation-enabled internship options at active NTHRYS branch locations in India.

Showing 1–10 of 10 internship topics
Phosphoproteomics Data Integration and Network Analysis
Interns will analyze phosphorylation site data from mass spectrometry experiments to map kinase-substrate relationships in cancer signaling networks. They will use bioinformatics tools to integrate phosphoproteomics datasets with pathway databases and identify dysregulated phosphorylation events in different cancer types.
Cancer Proteomics Pathway Integration SystemsView internship →
Protein-Protein Interaction Networks in Oncogenic Pathways
Interns will construct and analyze protein-protein interaction (PPI) networks specific to cancer-related pathways using proteomics data and interaction databases. They will identify hub proteins, network modules, and critical nodes that drive cancer progression and drug resistance.
Cancer Proteomics Pathway Integration SystemsView internship →
Proteogenomics Integration for Cancer Mutation Validation
Interns will correlate genomic mutations with proteomics data to validate which genetic alterations result in protein-level changes in cancer cells. This involves analyzing how somatic mutations affect protein abundance, post-translational modifications, and pathway functionality.
Cancer Proteomics Pathway Integration SystemsView internship →
Temporal Proteomics Profiling of Treatment Response Pathways
Interns will perform time-course proteomics analysis to track dynamic changes in protein expression and signaling during cancer drug treatment. They will identify early biomarkers of therapeutic response and characterize pathway adaptations that lead to treatment resistance.
Cancer Proteomics Pathway Integration SystemsView internship →
Spatial Proteomics and Subcellular Localization in Tumor Microenvironments
Interns will analyze spatially-resolved proteomics data to understand how protein distribution and localization changes across different cellular compartments and tumor regions. They will investigate how compartmentalization affects pathway signaling in cancer cells and tumor-stromal interactions.
Cancer Proteomics Pathway Integration SystemsView internship →
Tumor Mutational Burden (TMB) Quantification and Stratification
Interns will learn to calculate and analyze tumor mutational burden from whole-exome or whole-genome sequencing data across different cancer types. They will develop skills in quantifying mutation counts, normalizing by coding sequence length, and stratifying patients into TMB-high and TMB-low categories for immunotherapy prediction and prognosis assessment.
Cancer Genomics Mutation Burden AnalysisView internship →
Somatic Mutation Calling and Quality Control
Interns will work on variant calling pipelines to identify somatic mutations from sequencing data and implement quality control metrics to distinguish true mutations from sequencing artifacts. They will gain hands-on experience with tools like GATK, VarScan, and MuTect to ensure accurate mutation detection across tumor samples.
Cancer Genomics Mutation Burden AnalysisView internship →
Mutational Signature and Etiology Analysis
Interns will analyze mutational signatures to identify underlying mutational processes (e.g., UV radiation, tobacco, APOBEC) in cancer genomes using computational frameworks. They will learn pattern recognition techniques and signature deconvolution methods to associate mutation types with specific carcinogenic exposures.
Cancer Genomics Mutation Burden AnalysisView internship →
Clonal Evolution and Subclonal Architecture in Tumors
Interns will investigate clonal populations within tumors by analyzing variant allele frequencies and estimating clonal composition from mutation burden data. They will study how subclonal mutations accumulate during tumor progression and their implications for treatment resistance and disease heterogeneity.
Cancer Genomics Mutation Burden AnalysisView internship →
Genomic Biomarker Discovery for Immunotherapy Response Prediction
Interns will correlate mutation burden metrics with immune checkpoint inhibitor response outcomes in published cancer cohorts. They will explore how mutational load, neoantigen density, and specific mutational signatures predict immunotherapy efficacy and identify novel genomic predictors of patient treatment response.
Cancer Genomics Mutation Burden AnalysisView internship →
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