Applications of Clinical Bioinformatics

Clinical BioinformaticsThe term, “Clinical Bioinformatics” is defined as the clinical application of bioinformatics – associated sciences and technologies to understand molecular mechanisms and potential therapies for human diseases. It is considered to be a new and important concept for the development of disease specific biomarkers and individualized medicine.

Clinical Bioinformatics domain is encompassed with combination of Medical Informatics and Bioinformatics to develop new methodologies in bioinformatics that can assist in the conduct of clinical research and to develop universal human database. It is the product of combination of clinical informatics, bioinformatics, medical informatics, information technology, mathematics and omics sciences together.

In 1998, a study was conducted on expressed sequence tags (EST) in human stem cells using bioinformatics techniques. 10,000 sequences were analyzed using bioinformatics methodologies and it was found that 48% of sequences showed the identity to already known genes in the GenBank Database, 26.4% matched the previously deposited sequences in a public domain database, 14% were previously undescribed sequences, and the remaining 12% were mitochondrial DNA, ribosomal RNA, or repetitive sequences. In a drug discovery screening performed in early years of the 21st century, gene expression profiles were evaluated in 60 human cancer cell lines by cDNA microarray technique and corrected with drug activity patterns by combining cheminformatics and bioinformatics.

The knowledge of clinical bioinformatics would be useful in providing medical and biological information in individualized healthcare. It also enables researchers to search biological databases available online and make use of bioinformatics in their regular medical practice. It also helps in selecting the appropriate tool to analyse the data obtained from microarray techniques for clinical validation.

Clinical bioinformatics plays an important role in a number of clinical applications, including omics technology, metabolic and signaling pathways, biomarker discovery and development, computational biology, genomics, proteomics, metaboliomics, pharmacomics, transcriptomics, high-throughput image analysis, human molecular genetics, human tissue bank, mathematical medicine and biology, protein expression and profiling and systems biology. Simultaneous evaluation of clinical research and basic research can improve medical care, care provision data, and data exploitation methods in disease therapy and analysis of heterogeneous data sets.

Due to the lack of integrated analysis and digitalised informatics of clinical measurements, clinical bioinformatics couldn’t emphasize the significance and relationships between the underlying molecular mechanisms and the clinical observations.

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