Generative deep learning for targeted compound design
In the past few years, de novo molecular design has increasingly been using generative
models from the emergent field of Deep Learning, proposing novel compounds that are …
models from the emergent field of Deep Learning, proposing novel compounds that are …
[HTML][HTML] Enhancing preclinical drug discovery with artificial intelligence
Artificial intelligence (AI) is becoming an integral part of drug discovery. It has the potential to
deliver across the drug discovery and development value chain, starting from target …
deliver across the drug discovery and development value chain, starting from target …
Ab initio quantum chemistry with neural-network wavefunctions
Deep learning methods outperform human capabilities in pattern recognition and data
processing problems and now have an increasingly important role in scientific discovery. A …
processing problems and now have an increasingly important role in scientific discovery. A …
Artificial intelligence in drug discovery: applications and techniques
Artificial intelligence (AI) has been transforming the practice of drug discovery in the past
decade. Various AI techniques have been used in many drug discovery applications, such …
decade. Various AI techniques have been used in many drug discovery applications, such …
From turing to transformers: A comprehensive review and tutorial on the evolution and applications of generative transformer models
In recent years, generative transformers have become increasingly prevalent in the field of
artificial intelligence, especially within the scope of natural language processing. This paper …
artificial intelligence, especially within the scope of natural language processing. This paper …
Machine learning in drug design: Use of artificial intelligence to explore the chemical structure–biological activity relationship
The paper presents a comprehensive overview of the use of artificial intelligence (AI)
systems in drug design. Neural networks, which are one of the systems employed in AI, are …
systems in drug design. Neural networks, which are one of the systems employed in AI, are …
Generative AI for designing and validating easily synthesizable and structurally novel antibiotics
The rise of pan-resistant bacteria is creating an urgent need for structurally novel antibiotics.
Artificial intelligence methods can discover new antibiotics, but existing methods have …
Artificial intelligence methods can discover new antibiotics, but existing methods have …
A review on generative adversarial networks for image generation
Abstract Generative Adversarial Networks (GANs) are a type of deep learning architecture
that uses two networks namely a generator and a discriminator that, by competing against …
that uses two networks namely a generator and a discriminator that, by competing against …
Machine learning designs non-hemolytic antimicrobial peptides
Machine learning (ML) consists of the recognition of patterns from training data and offers
the opportunity to exploit large structure–activity databases for drug design. In the area of …
the opportunity to exploit large structure–activity databases for drug design. In the area of …
Adsorption enthalpies for catalysis modeling through machine-learned descriptors
Conspectus Heterogeneous catalysts are rather complex materials that come in many
classes (eg, metals, oxides, carbides) and shapes. At the same time, the interaction of the …
classes (eg, metals, oxides, carbides) and shapes. At the same time, the interaction of the …