Title :
Heavy path mining reveals novel protein-protein associations in the malaria parasite plasmodium falciparum
Author :
Xinran Yu ; Korkmaz, Turgay ; Lilburn, Timothy G. ; Hong Cai ; Jianying Gu ; Yufeng Wang
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas at San Antonio (UTSA), San Antonio, TX, USA
Abstract :
Malaria is one of the most deadly infectious diseases in the world. The malaria burden is characterized by 207 million cases and over 627,000 deaths annually. The consistent morbidity and mortality underscore an urgent need for the development of next-generation antimalarials. In this paper, we propose a network mining approach to uncover the protein-protein associations that are implicated in important cellular processes including DNA repair, genome integrity, transcriptional regulation, and pathogenesis.
Keywords :
DNA; bioinformatics; cellular biophysics; data mining; diseases; genomics; microorganisms; molecular biophysics; proteins; DNA repair; cellular processes; deadly infectious diseases; genome integrity; heavy path mining; malaria parasite Plasmodium falciparum; morbidity; mortality underscore; network mining approach; next-generation antimalarial development; pathogenesis; protein-protein associations; transcriptional regulation; Bioinformatics; DNA; Diseases; Genomics; Immune system; Proteins; Plasmodium falciparum; heavy path mining; malaria; protein association network; systems biology;
Conference_Titel :
Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on
Conference_Location :
Belfast
DOI :
10.1109/BIBM.2014.6999137
