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Computational approaches streamlining drug discovery
AV Sadybekov, V Katritch - Nature, 2023 - nature.com
Computer-aided drug discovery has been around for decades, although the past few years
have seen a tectonic shift towards embracing computational technologies in both academia …
have seen a tectonic shift towards embracing computational technologies in both academia …
AI-powered therapeutic target discovery
FW Pun, IV Ozerov, A Zhavoronkov - Trends in pharmacological sciences, 2023 - cell.com
Disease modeling and target identification are the most crucial initial steps in drug
discovery, and influence the probability of success at every step of drug development …
discovery, and influence the probability of success at every step of drug development …
A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models
Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high
mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at …
mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at …
Precision treatment in advanced hepatocellular carcinoma
X Yang, C Yang, S Zhang, H Geng, AX Zhu… - Cancer Cell, 2024 - cell.com
The past decade has witnessed significant advances in the systemic treatment of advanced
hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies …
hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies …
Machine learning-aided generative molecular design
Abstract Machine learning has provided a means to accelerate early-stage drug discovery
by combining molecule generation and filtering steps in a single architecture that leverages …
by combining molecule generation and filtering steps in a single architecture that leverages …
AlphaFold2 and its applications in the fields of biology and medicine
Z Yang, X Zeng, Y Zhao, R Chen - Signal Transduction and Targeted …, 2023 - nature.com
Abstract AlphaFold2 (AF2) is an artificial intelligence (AI) system developed by DeepMind
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …
that can predict three-dimensional (3D) structures of proteins from amino acid sequences …
Self-driving laboratories for chemistry and materials science
Self-driving laboratories (SDLs) promise an accelerated application of the scientific method.
Through the automation of experimental workflows, along with autonomous experimental …
Through the automation of experimental workflows, along with autonomous experimental …
Machine learning in preclinical drug discovery
DB Catacutan, J Alexander, A Arnold… - Nature Chemical …, 2024 - nature.com
Drug-discovery and drug-development endeavors are laborious, costly and time consuming.
These programs can take upward of 12 years and cost US $2.5 billion, with a failure rate of …
These programs can take upward of 12 years and cost US $2.5 billion, with a failure rate of …
Chemistry42: an AI-driven platform for molecular design and optimization
YA Ivanenkov, D Polykovskiy, D Bezrukov… - Journal of chemical …, 2023 - ACS Publications
Chemistry42 is a software platform for de novo small molecule design and optimization that
integrates Artificial Intelligence (AI) techniques with computational and medicinal chemistry …
integrates Artificial Intelligence (AI) techniques with computational and medicinal chemistry …
Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice: JACC State-of-the-Art Review
R Khera, EK Oikonomou, GN Nadkarni… - Journal of the American …, 2024 - jacc.org
Artificial intelligence (AI) has the potential to transform every facet of cardiovascular practice
and research. The exponential rise in technology powered by AI is defining new frontiers in …
and research. The exponential rise in technology powered by AI is defining new frontiers in …