Computational Identification of Biomarkers
Archana N. Mahajan1, Maulika S. Patel2

1Archana N. Mahajan, Ph.D Scholar, Gujarat Technological University, Ahmedabad (Gujarat), India.

2Dr. Maulika S. Patel, Professor & Head, Department of Computer Engineering, G H Patel College of Engineering & Technology, Vallabh Vidyanagar (Gujarat), India.

Manuscript received on 25 April 2020 | Revised Manuscript received on 07 May 2020 | Manuscript Published on 22 May 2020 | PP: 1-5 | Volume-9 Issue-7S July 2020 | Retrieval Number: 100.1/ijitee.G10010597S20 | DOI: 10.35940/ijitee.G1001.0597S20

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Abstract: Early detection of diseases and personalized medicine are gaining huge attention as a result of the advancements in the fields of bioinformatics and computational biology. Computational Biology is an interdisciplinary area involving Biomolecular data understanding and analysis by using and development of various tools, algorithms and methods. Disease detection and prediction is mostly carried out through the symptoms reported by patient and clinical test performed on the basis of it. There is a need to detect disease before the symptoms progress. Biomarkers are biological markers which are implicitly available in biomolecular data. There are different types of biomarkers which can help in early disease detection and finding correlation of the disease with other changes at the cellular level. The biomolecular data exploration is the key to identify various biomarkers. This paper presents a summary of types of biomarkers and biomarker identification techniques.

Keywords: Biomarker, Computational Biology, Decision Trees, Genomics, k-means Clustering, Proteomics, Support Vector Machines, Transcriptomics.
Scope of the Article: Computational Economics