Computational tools applied to biology are revolutionizing the study of what happens inside cells during an infection, helping scientists to understand disease mechanisms and contributing to the identification of potential therapeutic targets. An example is a study published online on June 18, 2019 in PLOS Pathogens describing how Brazilian researchers analyzed blood cells from patients infected with chikungunya virus (image). With the aid of techniques such as complex network analysis, artificial intelligence, and machine learning, the group identified gene signatures associated with the disease - sets of genes whose expression is altered by interaction with the virus. They then investigated the role played in cells by the involved genes and determined the importance of these genes to efforts to combat the virus. The open-access article is titled “Systems Analysis of Subjects Acutely Infected with the Chikungunya Virus.” Conducted in Brazil, the research was supported by São Paulo Research Foundation (FAPESP). The principal investigator was Helder Nakaya, PhD, a professor at the University of São Paulo's School of Pharmaceutical Sciences (FCF-USP). Researchers at the same university's Biomedical Science Institute (ICB-USP) and its Ribeirão Preto Medical School (FMRP-USP), as well as colleagues at Butantan Institute and the Public Health Central Laboratory of Sergipe, among others, also contributed. "We also identified a set of genes that show during the acute phase whether the patient is likely to develop chronic arthralgia [joint pain and inflammation], a relatively common condition in people infected with chikungunya. However, this finding has yet to be confirmed by future research based on a larger number of samples," Dr. Nakaya said.
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