Zobrazeno 1 - 10
of 99
pro vyhledávání: '"Jian-Yu Shi"'
Publikováno v:
iScience, Vol 26, Iss 11, Pp 108285- (2023)
Summary: It is a critical step in lead optimization to evaluate the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of drug-like compounds. Classical single-task learning (STL) has effectively predicted individual ADM
Externí odkaz:
https://doaj.org/article/6d8c3ae4ce7a4272b36288c532f99bfb
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-13 (2022)
Abstract Background Prediction of drug–drug interactions (DDIs) can reveal potential adverse pharmacological reactions between drugs in co-medication. Various methods have been proposed to address this issue. Most of them focus on the traditional l
Externí odkaz:
https://doaj.org/article/5f02762e0d9f4247baf1f74fbf01c17e
Publikováno v:
Frontiers in Microbiology, Vol 13 (2022)
Externí odkaz:
https://doaj.org/article/2b0cafb7a69e4487873f8f9a0e4d17bd
Publikováno v:
Frontiers in Microbiology, Vol 13 (2022)
Many drugs can be metabolized by human microbes; the drug metabolites would significantly alter pharmacological effects and result in low therapeutic efficacy for patients. Hence, it is crucial to identify potential drug–microbe associations (DMAs)
Externí odkaz:
https://doaj.org/article/becc6ea88e5c474697624744ba14467a
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)
Abstract Background The treatment of complex diseases by taking multiple drugs becomes increasingly popular. However, drug-drug interactions (DDIs) may give rise to the risk of unanticipated adverse effects and even unknown toxicity. DDI detection in
Externí odkaz:
https://doaj.org/article/39c8572784ac4983ab9510e04db8640b
Publikováno v:
Journal of Cheminformatics, Vol 11, Iss 1, Pp 1-16 (2019)
Abstract Background Because drug–drug interactions (DDIs) may cause adverse drug reactions or contribute to complex-disease treatments, it is important to identify DDIs before multiple-drug medications are prescribed. As the alternative of high-cos
Externí odkaz:
https://doaj.org/article/48e7cd1679df4ffc811ee1ee2162a141
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S14, Pp 27-37 (2018)
Abstract Background A significant number of adverse drug reactions is caused by unexpected Drug-drug interactions (DDIs). The identification of DDIs becomes crucial before the co-prescription of multiple drugs is made. Such a task in clinics or in dr
Externí odkaz:
https://doaj.org/article/5feddb5fd5e34e67b034982fb61e008f
Publikováno v:
Frontiers in Oncology, Vol 11 (2021)
Despite extensive research, the exact mechanisms involved in colorectal cancer (CRC) etiology and pathogenesis remain unclear. This study aimed to examine the correlation between tumor-associated alternative splicing (AS) events and tumor immune infi
Externí odkaz:
https://doaj.org/article/6815297353d84ed4b14895323c971827
BMCMDA: a novel model for predicting human microbe-disease associations via binary matrix completion
Publikováno v:
BMC Bioinformatics, Vol 19, Iss S9, Pp 85-92 (2018)
Abstract Background Human Microbiome Project reveals the significant mutualistic influence between human body and microbes living in it. Such an influence lead to an interesting phenomenon that many noninfectious diseases are closely associated with
Externí odkaz:
https://doaj.org/article/78afb2168c2248cba6bc4d24907e4add
Publikováno v:
BMC Medical Genomics, Vol 10, Iss S4, Pp 55-64 (2017)
Abstract Background In human genomes, long non-coding RNAs (lncRNAs) have attracted more and more attention because their dysfunctions are involved in many diseases. However, the associations between lncRNAs and diseases (LDA) still remain unknown in
Externí odkaz:
https://doaj.org/article/50fc2879015e4a0da4788442ee1a9f94