A Comprehensive Survey of Recent Approaches on Microarray Image Data

Microarray image processing techniques are used to study gene expressions in the form of images. This helps in genomic study without sequencing to extract useful information from gene expressions. Microarray images have greater scope of study in the field of Bioinformatics. This helps in processing the information embedded in these gene expressions which is laying a foundation to biological interpretation. Microarray image analysis is needed for applications like gene discovery, disease diagnosis and treatment, taxonomic research, drug discovery. This review paper discusses various types of microarray data and stages pertaining to processing of microarray images. Substantial literature describes comparative study on various microarray image processing techniques to formulate effective results in extracting gene expressions. This paper describes the latest approaches on microarray image processing tools, datasets, experimentation, results with comparative study on computational methods applied in literature. The literature also highlights challenges faced in the phase of pre-processing, gridding, spot segmentation and recognition techniques which can be helpful for a researcher to identify effective methods for classifying gene expressions. Further, the paper gives an overview of standard datasets used by research authors and details on creation of microarray data independently which can be helpful for experimentations. The gene expression extracted from microarray image processing techniques representing biological data helps in integrating computation techniques with the bioinformatics field leading to an open area of research for additional development.