The Primary Role of Bioinformatics in Modern Diagnostics and Laboratory Medicine
Bioinformatics primarily functions to manage and analyze large datasets generated through high-throughput technologies in modern diagnostics and laboratory medicine. 1
Core Function: Data Management and Analysis
The fundamental role of bioinformatics centers on handling the massive volumes of data produced by next-generation sequencing (NGS) and other high-throughput platforms. 1 This includes:
- Storing and analyzing huge amounts of data generated by sequencing and high-throughput technologies, requiring e-infrastructure with high-performance computing and large-scale storage resources 1
- Processing data through multiple analytical stages: primary analysis (converting instrument signals to base calls), secondary analysis (quality assessment, trimming, filtering, and sequence alignment), and tertiary analysis (interpretation and clinical reporting) 1
- Providing computational tools for finding disease fingerprints in proteomic and microarray datasets through improved data visualization technologies and multivariate statistical algorithms 1
Integration Across Multiple Biological Levels
Bioinformatics serves as the critical bridge for integrating diverse data types:
- Combining complementary genetic, gene-expression, and clinical data to support discovery and evaluation of candidate disease patterns in large clinical datasets 1
- Organizing information gathered from both high-throughput experimental technologies and traditional biology and medicine 2, 3
- Enabling effective integration of multiple biological levels including genomic, transcriptomic, and proteomic data 1
Supporting High-Throughput Technologies
The infrastructure demands are substantial:
- NGS applications require automated informatics components, computational servers, and databases that were not previously routine in clinical and public health laboratories 1
- Bioinformatics tasks typically require extensive cluster-attached storage and random-access memory (RAM), with some tasks like genome assembly requiring up to several terabytes of RAM 1
- High-throughput marker validation relies on bioinformatics to process data from widely used immunoassay platforms and other clinical laboratory technologies 1
Critical Distinction from Other Laboratory Functions
While bioinformatics does not primarily focus on developing new diagnostic tests (that's the role of technology development centers), training personnel on testing procedures (that's laboratory education), or ensuring safety (that's quality assurance and regulatory compliance), it is essential for making high-throughput diagnostic technologies clinically useful 1
Important Caveats
- Workforce education in bioinformatics is critical for successful NGS adoption, as most clinical and public health laboratorians lack routine bioinformatics skills 1
- Expansion of information technology infrastructure and training efforts among clinicians and scientists is required to support effective progress 1
- Professional service units should handle e-infrastructure development and maintenance due to increasingly demanding technical requirements, with emphasis on collaboration between researchers and IT professionals 1