The Computational Techniques Developed to Analyze DNA Gel Images

The analysis of gel electrophoresis images is very crucial for molecular biologists to comprehend and interpret their experimental results. Thus, enhancing current mathematical methods and developing new accurate ones is very important and challenging task for bioinformaticians. For example, enhancing the commonly used mathematical method in gel analysis known as "Fitting method estimation" and proposing a new efficient method entitled "Ruler estimation" for preprocessing a given image and detecting lanes and bands automatically. Both mathematical methods implemented in our newly developed software. Three mathematical models namely, linear, quadratic and cubic fitting are tested for the accuracy of detecting the bands and lanes in the gel image to determine the best fitting model. A friendly user interface is developed for this new program using MATLB GUI to extract useful bimolecular information accurately and automatically. The new software has the ability to manually add or delete any band(s) and estimate the size of any unknown band(s) on the gel. Moreover, the similarity and (dis)similarity between lanes "samples" are estimated based on comparing the numbers and sizes of bands to generate a phylogram tree