Bioinformatics Bioinformatics Analysis Clinical Bioinformatics

Role of Bioinformatics in Clinical Research

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Clinical bioinformatics is a new way to focus on the combination of clinical measurements and signs with human tissue-generated bioinformatics, understand clinical symptoms and signs, disease development and progress, and therapeutic strategy, and map relationships that integrate discrete elements that collectively.

The term “Clinical bioinformatics” is as “clinical application of bioinformatics-associated sciences and technologies to understand molecular mechanisms and potential therapies for human diseases”, a new and important concept for the development of disease-specific biomarkers, mechanism-oriented understanding and individualized medicine. 

Clinical bioinformatics is a new emerging science combining clinical informatics, bioinformatics, medical informatics, information technology, mathematics, and omics science together. 

At the starting of the 20th century, clinical physicians needed to be informed and open to advances in omics technology despite the barriers which existed for physicians applying genetic tests, for example the low tolerance for uncertainty, negative attitudes about their responsibility for genetic counseling and testing, and unfamiliarity with ethical issues raised by testing. Since the middle of the 20th century, bioinformatics has been suggested to be applied for clinical toxicology and cancer. One of the early studies on expressed sequence tags in human stem cells by bioinformatics was performed in 1998, where near 10000 sequences were analyzed. Clinical bioinformatics was initially proposed to provide biological and medical information for individualized healthcare, enable researchers to search online biological databases and use bioinformatics in medical practice, select appropriate software to analyze the microarray data for medical decision-making, optimize the development of disease-specific biomarkers, and supervise drug target identification and clinical validation.


  • omics technology
  • metabolic and signaling pathways
  • biomarker discovery and development
  • computational biology
  • genomics
  • proteomics
  • metabolomics
  • pharmacomics
  • transcriptomics
  • high-throughput image analysis
  • human molecular genetics
  • human tissue bank
  • mathematical medicine and biology
  • protein expression and profiling and systems biology

Understanding the interaction between clinical informatics and bioinformatics is the first and critical step to discover and develop the new diagnostics and therapies for diseases. Clinical bioinformatics was suggested to be associated with the analysis and visualization of complex medical datasets. Different from other informatics, clinical bioinformatics should focus more on clinical informatics, including patient complaints, history, therapies, clinical symptoms and signs, physician’s examinations, biochemical analyses, imaging profiles, pathologies and other measurements. It was emphasized that the simultaneous evaluation of clinical and basic research could improve medical care, care provision data, and data exploitation methods in disease therapy and algorithms for the analysis of such heterogeneous data sets. 

Biostatistics and bioinformatics concern the acquisition and interpretation of quantitative information in medical research. Both disciplines involve data analysis and experimental design. Both disciplines are concerned with conducting inferences and measuring evidence on the basis of observed data, and thus use similar tools and methodology. 


  • Molecular epidemiology
  • Pharmacogenetics and biomarkers
  • Clinical molecular genetics
  • Clinical forensic medicine.
  • Patterns of drug utilization
  • The effect of drug overdoses.
  • The economic implications of drug use.
  • Discovery undetected adverse and beneficial effects
  • Reassurance about drug safety

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