Showing papers by "Goutam Saha published in 2014"

An Algorithm for Parallel Assay Operations in a Restricted Sized Chip in Digital Microfluidics

Abstract: Digital Microfluidic Biochips (DMFB) is revolutionizing many areas of Microelectronics, Biochemistry, and Biomedical sciences. It is also known as 'Lab-on-a-Chip' for its popularity as an alternative for laboratory experiments. Pin count reduction and cross contamination avoidance are some of the core design issues for practical applications. Nowadays, due to emergency and cost effectiveness, more than one assay operations are required to be performed simultaneously. So, parallelism is a necessity in DMFB. Having an area of a given chip as a constraint, how efficiently we can use a restricted sized biochip and how much parallelism can be incorporated are the objectives of this paper. The paper presents a design automation flow that augments parallelism in applications considering cross contamination problem as well.

Identification of Genetic Pathway for Cervical Cancer Development Using Rough and Bayesian Theory

Abstract: Suitable analysis of microarray dataset can unlock the mystery of the origin of many dreaded disease like cancer which can subsequently be investigated for its rectification, resulting into search for drug design. A critical challenge of the post-genomic era is to find out the cancer causing genes that induce changes in gene expression profiles in the microarray dataset. Various algorithms based on SVM, Data Mining Techniques, Information theory based investigations, Clustering Techniques etc. were used by previous researchers. In this paper, Rough Set Theory and Bayesian Network based techniques have been applied for the same purpose. Rough Set has been used to isolate genes from microarray dataset responsible for cervical cancer. Bayesian approach has been used for extracting the Gene Regulating Network using the isolated genes. The same has been repeated for a normal healthy person. By superimposing these two networks, it is possible to find out the distinct cellular pathway for development of cancer from the departure of directed edges of the two networks. The results obtained in this work are quite satisfactory.