AIMC Topic: Cheminformatics

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Automated Workflows for Data Curation and Machine Learning to Develop Quantitative Structure-Activity Relationships.

Methods in molecular biology (Clifton, N.J.)
The recent advancements in machine learning and the new availability of large chemical datasets made the development of tools and protocols for computational chemistry a topic of high interest. In this chapter a standard procedure to develop Quantita...

Development of Drug Discovery Platforms Using Artificial Intelligence and Cheminformatics.

Chemical & pharmaceutical bulletin
Recently, remarkable progress has been achieved in artificial intelligence (AI), including machine learning. Various AI models have been proposed for drug discovery, including the design of small molecules, activity prediction, and three-dimensional ...

Exploring Anti-osteoporosis Medicinal Herbs using Cheminformatics and Deep Learning Approaches.

Combinatorial chemistry & high throughput screening
BACKGROUND: Osteoporosis is a prevalent disease for the aged population. Chinese herbderived natural compounds have anti-osteoporosis effects. Due to the complexity of chemical ingredients and natural products, it is necessary to develop a high-throu...

Mol2Context-vec: learning molecular representation from context awareness for drug discovery.

Briefings in bioinformatics
With the rapid development of proteomics and the rapid increase of target molecules for drug action, computer-aided drug design (CADD) has become a basic task in drug discovery. One of the key challenges in CADD is molecular representation. High-qual...

Learning to SMILES: BAN-based strategies to improve latent representation learning from molecules.

Briefings in bioinformatics
Computational methods have become indispensable tools to accelerate the drug discovery process and alleviate the excessive dependence on time-consuming and labor-intensive experiments. Traditional feature-engineering approaches heavily rely on expert...

Artificial Intelligence and Cheminformatics-Guided Modern Privileged Scaffold Research.

Current topics in medicinal chemistry
With the rapid development of computer science in scopes of theory, software, and hardware, artificial intelligence (mainly in form of machine learning and more complex deep learning) combined with advanced cheminformatics is playing an increasingly ...

Deep learning and generative methods in cheminformatics and chemical biology: navigating small molecule space intelligently.

The Biochemical journal
The number of 'small' molecules that may be of interest to chemical biologists - chemical space - is enormous, but the fraction that have ever been made is tiny. Most strategies are discriminative, i.e. have involved 'forward' problems (have molecule...

A Deep Learning Approach to Antibiotic Discovery.

Cell
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to discover new antibiotics. To address this challenge, we trained a deep neural network capable of predicting molecules with antibacterial activity. We performed pr...