Transcriptomics: Open Access
Open Access
ISSN: 2329-8936
ISSN: 2329-8936
Baris E. Suzek
Scientific Tracks Abstracts: Transcriptomics
The next generation sequencing technologies are continuously improving and large sets of human mutations are becoming available within institutions and through public resources. A subset of these mutations lead to single amino acid polymorphisms (SAPs). Identifying SAPsā?? disease-causing impact and developing methods to identify SAPs' diseaseassociations are active research areas. In this work, we investigated the link between disease-associated SAPs and their protein sequence context (i.e. sequence features). We have integrated disease-associated SAPs and sequence features from several public bioinformatics resources. The SAPs and sequence features are then mapped to each other using protein resource UniProt Knowledgebase. Based on our initial results, over 39% of disease-associated SAPs are located on functional domains, topological domains and near post translational modifications. Over 19% of them are located on known secondary structures. Our findings will help in better understanding of SAPsā?? disease associations. In the future, the protein sequence context for SAPs can be utilized in development of more accurate computational methods to predict disease-associated SAPs.
Baris E. Suzek has completed MS in Computer Science at Johns Hopkins University and PhD in Bioinformatics and Computational Biology at George Mason University. Currently, he is an Assistant Professor in Computer Engineering Department at Mugla Sitki Kocman University in Turkey and an Adjunct Assistant Professor at Georgetown University in USA. Before 2013, he served as a Research Assistant Professor in Department of Biohemistry and Bioinformatics Team Co-lead in Protein Information Resource at Georgetown University. He has published more than 20 papers in reputed journals, holds one patent and is recipient of several national awards in USA.