Various biological databases are available online, which are classified based on various criteria for ease of access and use. All such bioinformatics database resources have been discussed in brief in this book chapter. The major focus is on most commonly used biological/bioinformatics databases. The authors provide an overview of the information provided and analysis done by each database, information retrieval system and formats available, along with utility of the database to its users. Most widely used databases have been covered in detail so as to enhance readers' understanding. This chapter will serve as a guide to those who are new to the field of bioinformatics database resources, or wish to have consolidated information on various bioinformatics databases available.
Various biological databases are available online, which are classified based on various criteria for ease of access and use. All such bioinformatics database resources have been discussed in brief in this book chapter. The major focus is on most commonly used biological/bioinformatics databases. The authors provide an overview of the information provided and analysis done by each database, information retrieval system and formats available, along with utility of the database to its users. Most widely used databases have been covered in detail so as to enhance readers' understanding. This chapter will serve as a guide to those who are new to the field of bioinformatics database resources, or wish to have consolidated information on various bioinformatics databases available.
Brain and CNS cancer are rare in comparison to other types of cancer. Currently there are no effective therapies for their treatment. In this study, meta-analysis of microarray datasets of Brain and CNS cancer was done to obtain significantly upregulated genes with increased statistical power and generalizability. A total of 130 significantly up-regulated genes were obtained. Some of the genes found during analysis have not yet been associated with this cancer. Different biological networks were created and analyzed using the significantly up-regulated genes as input. For each network, the most significant pathways have also been identified computationally.
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