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 …
Application of machine learning in spatial proteomics
Spatial proteomics is an interdisciplinary field that investigates the localization and dynamics
of proteins, and it has gained extensive attention in recent years, especially the subcellular …
of proteins, and it has gained extensive attention in recent years, especially the subcellular …
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 developing …
comparative agents and targets. These include poor binders and non-binders for developing …
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 …
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 …
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 …
VARIDT 2.0: structural variability of drug transporter
The structural variability data of drug transporter (DT) are key for research on precision
medicine and rational drug use. However, these valuable data are not sufficiently covered …
medicine and rational drug use. However, these valuable data are not sufficiently covered …
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 …
ConSIG: consistent discovery of molecular signature from OMIC data
The discovery of proper molecular signature from OMIC data is indispensable for
determining biological state, physiological condition, disease etiology, and therapeutic …
determining biological state, physiological condition, disease etiology, and therapeutic …
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 …