The role of bioinformatics in oncology
Bioinformatics plays an important role in cancer diagnosis and treatment. It can help in identifying common biomarkers and differentially expressed genes in different cancers, as well as monitoring and predicting the efficiency and effectiveness of medicine.
Bioinformatics tools play a crucial role in oncology by facilitating the analysis of large-scale genomic, transcriptomic, epigenomic, and proteomic data generated from cancer studies. These tools aid in identifying driver mutations, understanding tumor heterogeneity, predicting treatment response, and uncovering potential therapeutic targets.
The choice of tools depends on the specific research questions, data types, and analytical needs of the study. Additionally, many of these tools are integrated into bioinformatics pipelines or platforms, providing user-friendly interfaces for data analysis and interpretation in oncology.
One of the most severe and lethal diseases, when diagnosed in early stages cancer can be cured. An important role in discovering and testing new therapies available for cancer treatment, and new drugs is played by advancements in bioinformatics.
For example, genome seq has provided a breakthrough in understanding cancer, its effects, and possible treatment options.
Oncologic bioinformatics can be extremely useful in drug development and disease management.
What can we offer
KonAnBio can offer next-generation sequencing personalised oncology for clinical practice to major cancer centres worldwide.
- Primary analysis of DNA data
- Primary analysis of RNA data
- Variant annotation
- Interpretation of molecular profiles and clinical reporting
- Survival analysis
Drug sensitivity and resistance analysis
KonAnBio can help you with:
- Target and lead identification and validation;
- Identifying biomarkers for measurement of drug efficacy and mechanism of action;
- Predicting biomarkers for stratification/classification of patient response to drug;
- SNP genotype analysis and DNA sequence analysis for the detection of novel SNPs implicated in disease or response to drugs.