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[HTML][HTML] Artificial intelligence in pharmaceutical sciences
Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …
impacts the pharmaceutical market. However, investments in a new drug often go …
The miRNA: a small but powerful RNA for COVID-19
Abstract Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) is a severe and rapidly evolving epidemic. Now …
syndrome coronavirus 2 (SARS-CoV-2) is a severe and rapidly evolving epidemic. Now …
Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents
Drug discovery relies on the knowledge of not only drugs and targets, but also the
comparative agents and targets. These include poor binders and non-binders for develo** …
comparative agents and targets. These include poor binders and non-binders for develo** …
A transformer-based ensemble framework for the prediction of protein–protein interaction sites
The identification of protein–protein interaction (PPI) sites is essential in the research of
protein function and the discovery of new drugs. So far, a variety of computational tools …
protein function and the discovery of new drugs. So far, a variety of computational tools …
DrugMAP: molecular atlas and pharma-information of all drugs
The efficacy and safety of drugs are widely known to be determined by their interactions with
multiple molecules of pharmacological importance, and it is therefore essential to …
multiple molecules of pharmacological importance, and it is therefore essential to …
POSREG: proteomic signature discovered by simultaneously optimizing its reproducibility and generalizability
Mass spectrometry-based proteomic technique has become indispensable in current
exploration of complex and dynamic biological processes. Instrument development has …
exploration of complex and dynamic biological processes. Instrument development has …
NOREVA: enhanced normalization and evaluation of time-course and multi-class metabolomic data
Biological processes (like microbial growth & physiological response) are usually dynamic
and require the monitoring of metabolic variation at different time-points. Moreover, there is …
and require the monitoring of metabolic variation at different time-points. Moreover, there is …
Molecular mechanism for the allosteric inhibition of the human serotonin transporter by antidepressant escitalopram
W Xue, T Fu, S Deng, F Yang, J Yang… - ACS chemical …, 2022 - ACS Publications
Human serotine transporter (hSERT) is one of the most influential drug targets, and its
allosteric modulators (eg, escitalopram) have emerged to be the next-generation medication …
allosteric modulators (eg, escitalopram) have emerged to be the next-generation medication …
PFmulDL: a novel strategy enabling multi-class and multi-label protein function annotation by integrating diverse deep learning methods
Bioinformatic annotation of protein function is essential but extremely sophisticated, which
asks for extensive efforts to develop effective prediction method. However, the existing …
asks for extensive efforts to develop effective prediction method. However, the existing …
DeepM6ASeq-EL: prediction of human N6-methyladenosine (m6A) sites with LSTM and ensemble learning
Abstract N6-methyladenosine (m 6 A) is a prevalent methylation modification and plays a
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …
vital role in various biological processes, such as metabolism, mRNA processing, synthesis …