Advances and perspectives in applying deep learning for drug design and discovery
CF Lipinski, VG Maltarollo, PR Oliveira… - Frontiers in Robotics …, 2019 - frontiersin.org
Discovering (or planning) a new drug candidate involves many parameters, which makes
this process slow, costly, and leading to failures at the end in some cases. In the last …
this process slow, costly, and leading to failures at the end in some cases. In the last …
[HTML][HTML] Targeting epigenetic machinery: emerging novel allosteric inhibitors
F Ye, J Huang, H Wang, C Luo, K Zhao - Pharmacology & Therapeutics, 2019 - Elsevier
Epigenetics has emerged as an extremely exciting fast-growing area of biomedical research
in post genome era. Epigenetic dysfunction is tightly related with various diseases such as …
in post genome era. Epigenetic dysfunction is tightly related with various diseases such as …
Deep Learning and Site‐Specific Drug Delivery: The Future and Intelligent Decision Support for Pharmaceutical Manufacturing Science
DU Meenakshi, S Nandakumar… - Deep Learning for …, 2022 - Wiley Online Library
Site‐specific drug delivery [SSDD] is a smart localized and targeted delivery system that is
used to improve drug efficiency, decrease drug‐related toxicity, and prolong the duration of …
used to improve drug efficiency, decrease drug‐related toxicity, and prolong the duration of …
Bioinformatics and in vitro studies reveal the importance of p53, PPARG and notch signaling pathway in inhibition of breast cancer stem cells by hesperetin
Purpose: The failure of chemotherapy in breast cancer is caused by breast cancer stem cells
(BCSCs), a minor population of cells in bulk mammary tumors. Previously, hesperetin, a …
(BCSCs), a minor population of cells in bulk mammary tumors. Previously, hesperetin, a …
Small molecule-mediated regenerative engineering for craniofacial and dentoalveolar bone
J Mitchell, KWH Lo - Frontiers in Bioengineering and Biotechnology, 2022 - frontiersin.org
The comprehensive reconstruction of extensive craniofacial and dentoalveolar defects
remains a major clinical challenge to this day, especially in complex medical cases involving …
remains a major clinical challenge to this day, especially in complex medical cases involving …
Artificial intelligence-guided Approach for Efficient Virtual Screening of Hits Against Schistosoma Mansoni
JT Moreira-Filho, BJ Neves, RA Cajas… - Future Medicinal …, 2023 - Taylor & Francis
Background: The impact of schistosomiasis, which affects over 230 million people,
emphasizes the urgency of developing new antischistosomal drugs. Artificial intelligence is …
emphasizes the urgency of developing new antischistosomal drugs. Artificial intelligence is …
[HTML][HTML] Artificial intelligence systems for the design of magic shotgun drugs
JT Moreira-Filho, MFB da Silva, JVVB Borba… - Artificial Intelligence in …, 2023 - Elsevier
Designing magic shotgun compounds, ie, compounds hitting multiple targets using artificial
intelligence (AI) systems based on machine learning (ML) and deep learning (DL) …
intelligence (AI) systems based on machine learning (ML) and deep learning (DL) …
How can artificial intelligence be used for peptidomics?
L Perpetuo, J Klein, R Ferreira, S Guedes… - Expert Review of …, 2021 - Taylor & Francis
Introduction Peptidomics is an emerging field of omics sciences using advanced isolation,
analysis, and computational techniques that enable qualitative and quantitative analyses of …
analysis, and computational techniques that enable qualitative and quantitative analyses of …
[PDF][PDF] Metal (II) triazole complexes: Synthesis, biological evaluation, and analytical characterization using machine learning-based validation
Metal-based compounds are essential for the normal functioning of living organisms. Zinc
metal plays a role in metabolic pathways in the human body. Its deficiency can cause growth …
metal plays a role in metabolic pathways in the human body. Its deficiency can cause growth …
rECGnition_v1. 0: Arrhythmia detection using cardiologist-inspired multi-modal architecture incorporating demographic attributes in ECG
A substantial amount of variability in ECG manifested due to patient characteristics hinders
the adoption of automated analysis algorithms in clinical practice. None of the ECG …
the adoption of automated analysis algorithms in clinical practice. None of the ECG …