Khalid Raza

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Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes. Modeling GRNs is significantly important in order to reveal fundamental cellular processes, examine gene functions and understanding their complex relationships. Understanding the interactions between genes gives rise to develop better method for drug(More)
The main goal of Systems Biology research is to reconstruct biological networks for its topological analysis so that reconstructed networks can be used for the identification of various kinds of disease. The availability of high-throughput data generated by microarray experiments fuelled researchers to use whole-genome gene expression profiles to understand(More)
The high-throughput data generated by microarray experiments provides complete set of genes being expressed in a given cell or in an organism under particular conditions. The analysis of these enormous data has opened a new dimension for the researchers. In this paper we describe a novel algorithm to microarray data analysis focusing on the identification(More)
Inferring gene interaction network from gene expression profiles is an important task in systems biology research. The gene interaction network, especially key interactions, plays an important role in identifying biomarkers for disease that further helps in drug design. Ant colony optimization is a nature-inspired swarm-based optimization algorithm that has(More)
— Reconstruction of gene regulatory networks or 'reverse-engineering' is a process of identifying gene interaction networks from experimental microarray gene expression profile through computation techniques. In this paper, we tried to reconstruct cancer-specific gene regulatory network using information theoretic approach-mutual information. The considered(More)
During a study of spinal cord injury (SCI), mice in our colony were treated with the anthelmintic fenbendazole to treat pinworms detected in other mice not involved in the study. As this was not part of the original experimental design, we subsequently compared pathological and functional outcomes of SCI in female C57BL/6 mice who received fenbendazole (150(More)
Prostate cancer is among the most common cancer in males and its heterogeneity is well known. The genomic level changes can be detected in gene expression data and those changes may serve as standard model for any random cancer data for class prediction. Various techniques were implied on prostate cancer data set in order to accurately predict cancer class(More)