The study of viruses and their genetics has been an opportunity as well as a challenge for the scientific community.The recent ongoing SARSCov2(Severe Acute Respiratory Syndrome)pandemic proved the unpreparedness for ...The study of viruses and their genetics has been an opportunity as well as a challenge for the scientific community.The recent ongoing SARSCov2(Severe Acute Respiratory Syndrome)pandemic proved the unpreparedness for these situations.Not only the countermeasures for the effect caused by virus need to be tackled but the mutation taking place in the very genome of the virus is needed to be kept in check frequently.One major way to find out more information about such pathogens is by extracting the genetic data of such viruses.Though genetic data of viruses have been cultured and stored as well as isolated in form of their genome sequences,there is still limited methods on what new viruses can be generated in future due to mutation.This research proposes a deep learning model to predict the genome sequences of the SARS-Cov2 virus using only the previous viruses of the coronaviridae family with the help of RNN-LSTM(Recurrent Neural Network-Long ShortTerm Memory)and RNN-GRU(Gated Recurrent Unit)so that in the future,several counter measures can be taken by predicting possible changes in the genome with the help of existing mutations in the virus.After the process of testing the model,the F1-recall came out to be more than 0.95.The mutation detection’s accuracy of both the models come out about 98.5%which shows the capability of the recurrent neural network to predict future changes in the genome of virus.展开更多
Retromer and sorting nexins(SNXs)transport cargoes from endosomes to the trans-Golgi network or plasma membrane.Recent studies have unveiled the emerging roles for retromer and SNXs in the life cycle of viruses,includ...Retromer and sorting nexins(SNXs)transport cargoes from endosomes to the trans-Golgi network or plasma membrane.Recent studies have unveiled the emerging roles for retromer and SNXs in the life cycle of viruses,including members of Coronaviridae,Flaviviridae and Retroviridae.Key components of retromer/SNXs,such as Vps35,Vps26,SNX5 and SNX27,can affect multiple steps of the viral life cycle,including facilitating the entry of viruses into cells,participating in viral replication,and promoting the assembly of virions.Here we present a comprehensive updated review on the interplay between retromer/SNXs and virus,which will shed mechanistic insights into controlling virus infection.展开更多
基金Taif University Researchers are supporting project number(TURSP-2020/211),Taif University,Taif,Saudi Arabia.
文摘The study of viruses and their genetics has been an opportunity as well as a challenge for the scientific community.The recent ongoing SARSCov2(Severe Acute Respiratory Syndrome)pandemic proved the unpreparedness for these situations.Not only the countermeasures for the effect caused by virus need to be tackled but the mutation taking place in the very genome of the virus is needed to be kept in check frequently.One major way to find out more information about such pathogens is by extracting the genetic data of such viruses.Though genetic data of viruses have been cultured and stored as well as isolated in form of their genome sequences,there is still limited methods on what new viruses can be generated in future due to mutation.This research proposes a deep learning model to predict the genome sequences of the SARS-Cov2 virus using only the previous viruses of the coronaviridae family with the help of RNN-LSTM(Recurrent Neural Network-Long ShortTerm Memory)and RNN-GRU(Gated Recurrent Unit)so that in the future,several counter measures can be taken by predicting possible changes in the genome with the help of existing mutations in the virus.After the process of testing the model,the F1-recall came out to be more than 0.95.The mutation detection’s accuracy of both the models come out about 98.5%which shows the capability of the recurrent neural network to predict future changes in the genome of virus.
基金supported by grants from National Natural Science Foundation of China(81871663 and 82072270)Undergraduate Science and Technology Innovation Plan of International Class of Clinical Medicine in Shandong First Medical University(ZYKC2019-016)Academic promotion programme of Shandong First Medical University(2019LJ001)。
文摘Retromer and sorting nexins(SNXs)transport cargoes from endosomes to the trans-Golgi network or plasma membrane.Recent studies have unveiled the emerging roles for retromer and SNXs in the life cycle of viruses,including members of Coronaviridae,Flaviviridae and Retroviridae.Key components of retromer/SNXs,such as Vps35,Vps26,SNX5 and SNX27,can affect multiple steps of the viral life cycle,including facilitating the entry of viruses into cells,participating in viral replication,and promoting the assembly of virions.Here we present a comprehensive updated review on the interplay between retromer/SNXs and virus,which will shed mechanistic insights into controlling virus infection.