Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …
[HTML][HTML] New opportunities and challenges of natural products research: When target identification meets single-cell multiomics
Y Zhu, Z Ouyang, H Du, M Wang, J Wang, H Sun… - … Pharmaceutica Sinica B, 2022 - Elsevier
Natural products, and especially the active ingredients found in traditional Chinese medicine
(TCM), have a thousand-year-long history of clinical use and a strong theoretical basis in …
(TCM), have a thousand-year-long history of clinical use and a strong theoretical basis in …
DrugBank 6.0: the DrugBank knowledgebase for 2024
C Knox, M Wilson, CM Klinger, M Franklin… - Nucleic acids …, 2024 - academic.oup.com
First released in 2006, DrugBank (https://go. drugbank. com) has grown to become the 'gold
standard'knowledge resource for drug, drug–target and related pharmaceutical information …
standard'knowledge resource for drug, drug–target and related pharmaceutical information …
Drawbacks of artificial intelligence and their potential solutions in the healthcare sector
Artificial intelligence (AI) has the potential to make substantial progress toward the goal of
making healthcare more personalized, predictive, preventative, and interactive. We believe …
making healthcare more personalized, predictive, preventative, and interactive. We believe …
Artificial intelligence and machine learning technology driven modern drug discovery and development
C Sarkar, B Das, VS Rawat, JB Wahlang… - International Journal of …, 2023 - mdpi.com
The discovery and advances of medicines may be considered as the ultimate relevant
translational science effort that adds to human invulnerability and happiness. But advancing …
translational science effort that adds to human invulnerability and happiness. But advancing …
Accelerated antimicrobial discovery via deep generative models and molecular dynamics simulations
The de novo design of antimicrobial therapeutics involves the exploration of a vast chemical
repertoire to find compounds with broad-spectrum potency and low toxicity. Here, we report …
repertoire to find compounds with broad-spectrum potency and low toxicity. Here, we report …
Artificial intelligence in drug discovery and development
KK Mak, YH Wong, MR Pichika - Drug discovery and evaluation: safety …, 2024 - Springer
This chapter comprehensively explores the pivotal role of artificial intelligence (AI) in drug
discovery and development, encapsulating its potentials, methodologies, real-world …
discovery and development, encapsulating its potentials, methodologies, real-world …
Machine learning methods in drug discovery
The advancements of information technology and related processing techniques have
created a fertile base for progress in many scientific fields and industries. In the fields of drug …
created a fertile base for progress in many scientific fields and industries. In the fields of drug …
Blockchain and artificial intelligence technology in e-Health
P Tagde, S Tagde, T Bhattacharya, P Tagde… - … Science and Pollution …, 2021 - Springer
Blockchain and artificial intelligence technologies are novel innovations in healthcare
sector. Data on healthcare indices are collected from data published on Web of Sciences …
sector. Data on healthcare indices are collected from data published on Web of Sciences …
Predicting drug–disease associations through layer attention graph convolutional network
Background: Determining drug–disease associations is an integral part in the process of
drug development. However, the identification of drug–disease associations through wet …
drug development. However, the identification of drug–disease associations through wet …