Knowledgebase of potential multifaceted solutions to antimicrobial resistance

Bhargav, Anasuya; Gupta, Sandeep K.; Seth, Surabhi; James, Sweety; Fatima, Firdaus; Chaurasia, Pratibha; Ramachandran, Srinivasan

doi:10.1016/j.compbiolchem.2022.107772

Cited by 5 publications

(1 citation statement)

References 81 publications

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“…The examples of recent studies that analyzed experimentally observed transcription changes in response to HIV infection include works by Kailash Chand and co-authors [ 25 ], Serena Meraviglia and co-authors [ 26 ], and Francesco Marras and co-authors [ 27 ]. There are several computational and text-mining approaches devoted to the study of individual mechanisms of disease progression [ 10 , 11 , 28 ] and their influence on the outcome [ 12 , 13 , 29 ]. For instance, in the study by Hans Christian Stubbe et al [ 11 ], sex differences in gene expression were investigated using combined microarray data and literature mining.…”

Section: Discussionmentioning

confidence: 99%

Identification of Molecular Mechanisms Involved in Viral Infection Progression Based on Text Mining: Case Study for HIV Infection

Tarasova

Biziukova

Shemshura

et al. 2023

IJMS

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Viruses cause various infections that may affect human lifestyle for durations ranging from several days to for many years. Although preventative and therapeutic remedies are available for many viruses, they may still have a profound impact on human life. The human immunodeficiency virus type 1 is the most common cause of HIV infection, which represents one of the most dangerous and complex diseases since it affects the immune system and causes its disruption, leading to secondary complications and negatively influencing health-related quality of life. While highly active antiretroviral therapy may decrease the viral load and the velocity of HIV infection progression, some individual peculiarities may affect viral load control or the progression of T-cell malfunction induced by HIV. Our study is aimed at the text-based identification of molecular mechanisms that may be involved in viral infection progression, using HIV as a case study. Specifically, we identified human proteins and genes which commonly occurred, overexpressed or underexpressed, in the collections of publications relevant to (i) HIV infection progression and (ii) acute and chronic stages of HIV infection. Then, we considered biological processes that are controlled by the identified protein and genes. We verified the impact of the identified molecules in the associated clinical study.

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