Computational analysis of Ebolavirus data: prospects, promises and challenges

Area of Science:

• Virology
• Computational Biology
• Genomics

Background:

• The 2014-2016 West Africa Ebola virus (Zaire ebolavirus) outbreak was unprecedented, causing over 28,000 cases.
• Limited wet laboratory capacity for Biosafety Level 4 pathogens necessitates complementary computational approaches.

Purpose of the Study:

• To review computational analyses of Ebola virus genomes from the West Africa outbreak.
• To highlight the potential of computational methods in understanding virus biology and informing preparedness.

Main Methods:

• Analysis of publicly available Ebola virus genome sequences.
• Investigating viral evolution, pathogenicity, microRNA prediction, and signature identification.

Main Results:

• Computational studies have explored various aspects of Ebola virus biology using genomic data.
• Identified potential targets for therapeutic and preventive measures.

Conclusions:

• Computational analyses provide valuable insights but require validation through wet laboratory experiments.
• Enhanced communication between computational and experimental researchers is essential for advancing Ebola virus research and preparedness.