Blockchain in Bioinformatics Data Security: Systematic Evidence, Research Gaps and Pathways Forward

Background: The growth of high-throughput sequencing and multi-omics research has intensified the need for secure, interoperable and transparent data management infrastructures. Blockchain technology has been widely proposed as a potential solution; however, its feasibility, empirical maturity and comparative performance in bioinformatics remain unclear.Objective: This systematic review analyses blockchain applications in bioinformatics, highlighting claimed security and governance benefits, comparing them with traditional data security approaches, discussing implementation challenges and assessing the empirical rigor of existing studies using a structured quality assessment framework.Methods: This overview was conducted using Scopus, ScienceDirect, IEEE Xplore, ACM Digital Library and SpringerLink for publications from 2014 to 2024. Search strings combined blockchain, bioinformatics and security-related terms. Sixty-five studies met the inclusion criteria. Each study was evaluated using five equally weighted quality dimensions: application specificity, clarity of benefits, empirical evaluation, challenge articulation and reproducibility.Results: Most studies focused on blockchain use cases in genomic data sharing, provenance tracking and access control, with a strong emphasis on conceptual benefits such as immutability and auditability. Fewer studies provided empirical evaluations or direct comparisons with traditional security mechanisms. Quality assessment results revealed a predominance of conceptual and prototype-level contributions; over half of the studies lacked empirical benchmarking and reproducibility was frequently limited. Heterogeneity in blockchain architectures and the absence of standardized genomic benchmarking environments hindered cross-study comparison. No study demonstrated deployment within a production-scale genomic pipeline.Conclusion: Blockchain demonstrates conceptual potential for enhancing provenance, decentralized governance and tamper-resistant auditing in bioinformatics data management. However, empirical validation remains limited and significant technical, regulatory and organizational challenges persist. The current evidence base is insufficient to support large-scale adoption. Future research should prioritize benchmarking using realistic genomic workloads, hybrid architectures that integrate off-chain storage, consent-aware governance models and alignment with regulatory frameworks such as GDPR and HIPAA.