AIMC Topic: Drug Discovery

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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...

Applications of Machine Learning in Drug Target Discovery.

Current drug metabolism
Drug target discovery is a critical step in drug development. It is the basis of modern drug development because it determines the target molecules related to specific diseases in advance. Predicting drug targets by computational methods saves a grea...

Current Advances and Limitations of Deep Learning in Anticancer Drug Sensitivity Prediction.

Current topics in medicinal chemistry
Anticancer drug screening can accelerate drug discovery to save the lives of cancer patients, but cancer heterogeneity makes this screening challenging. The prediction of anticancer drug sensitivity is useful for anticancer drug development and the i...

Digitizing the Pharma Neurons - A Technological Operation in Progress!

Reviews on recent clinical trials
BACKGROUND: Digitization and automation are the buzzwords in clinical research and pharma companies are investigating heavily here. Right from drug discovery to personalized medicine, digital patients and patient engagement, there is great considerat...

A Drug Decision Support System for Developing a Successful Drug Candidate Using Machine Learning Techniques.

Current computer-aided drug design
BACKGROUND: Virtual screening of candidate drug molecules using machine learning techniques plays a key role in pharmaceutical industry to design and discovery of new drugs. Computational classification methods can determine drug types according to t...

ReSimNet: drug response similarity prediction using Siamese neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: Traditional drug discovery approaches identify a target for a disease and find a compound that binds to the target. In this approach, structures of compounds are considered as the most important features because it is assumed that similar...