Web servers and bioinformatics tools for cancer research: A review

The rapid expansion of high-throughput technologies and multi-omics profiling has transformed cancer research by enabling systematic characterization of genomic, transcriptomic, epigenomic, proteomic, immunological, and pharmacological features of tumors. These diverse molecular alterations contribute to tumor initiation, progression, heterogeneity, treatment response, and resistance, creating a need for computational resources capable of integrating and interpreting complex cancer datasets. Consequently, numerous bioinformatics resources have been developed to organize, analyze, and interpret cancer-related molecular and clinical data, encompassing expression profiling, survival analysis, regulatory network reconstruction, epigenetic annotation, immune analysis, and drug-response assessment. In this review, we systematically examine and comparatively evaluate cancer-focused bioinformatics resources according to their data coverage, analytical capabilities, evidence strength, limitations, and appropriate use cases. We further distinguish databases, analytical web servers, prediction tools, and integrated analysis platforms and discuss their respective applications and limitations. Overall, this review provides a practical framework for selecting and interpreting cancer bioinformatics resources while highlighting key challenges in data integration, evidence validation, reproducibility, and clinical translation.