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

fYear

2014

fDate

2-5 Nov. 2014

Firstpage

107

Lastpage

112

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine (BIBM), 2014 IEEE International Conference on

Conference_Location

Belfast

Type

conf

DOI

10.1109/BIBM.2014.6999137

Filename

6999137