HIGH-THROUGHPUT METHODOLOGIES FOR SYSTEMATIC ENZYME PROFILING - Uttamchandani, Mahesh
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Recent evidence suggests that 18-29% of eukaryotic genomes encode enzymes. However, only a limited proportion of these enzymes have thus far been characterized, and little is understood about the physiological roles, substrate specificity and downstream targets of the vast majority of these important proteins. While advances in sequencing and molecular biology have made it feasible to quickly amass a great wealth of genetic information, sparking the genomic revolution, similar capabilities are severely lacking in the relatively nascent proteomics arena. A key step towards the biological…mehr

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Produktbeschreibung
Recent evidence suggests that 18-29% of eukaryotic genomes encode enzymes. However, only a limited proportion of these enzymes have thus far been characterized, and little is understood about the physiological roles, substrate specificity and downstream targets of the vast majority of these important proteins. While advances in sequencing and molecular biology have made it feasible to quickly amass a great wealth of genetic information, sparking the genomic revolution, similar capabilities are severely lacking in the relatively nascent proteomics arena. A key step towards the biological characterization of enzymes, as well as in their adoption as drug targets, is the development of global solutions that bridge the gap in understanding proteins and their interactions. This thesis examines and addresses these challenges by introducing a series of technologies that span various analytical modes, effectively expanding current capabilities in protein profiling by leveraging on throughput.
Autorenporträt
Mahesh Uttamchandani joined DSO National Laboratories in 2007, after graduating with a PhD in Biology from the National Univeristy of Singapore (NUS). He also concurrently holds an Assistant Professor position at the Departments of Chemistry and Biological Sciences at NUS. His research interests include catalomics, genetics and proteomics.