Obtaining genetics insights from deep learning via explainable artificial intelligence
Artificial intelligence (AI) models based on deep learning now represent the state of the art
for making functional predictions in genomics research. However, the underlying basis on …
for making functional predictions in genomics research. However, the underlying basis on …
Deep learning modelling techniques: current progress, applications, advantages, and challenges
Deep learning (DL) is revolutionizing evidence-based decision-making techniques that can
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
be applied across various sectors. Specifically, it possesses the ability to utilize two or more …
Machine learning in drug discovery: a review
This review provides the feasible literature on drug discovery through ML tools and
techniques that are enforced in every phase of drug development to accelerate the research …
techniques that are enforced in every phase of drug development to accelerate the research …
An introductory review of deep learning for prediction models with big data
Deep learning models stand for a new learning paradigm in artificial intelligence (AI) and
machine learning. Recent breakthrough results in image analysis and speech recognition …
machine learning. Recent breakthrough results in image analysis and speech recognition …
CRISPR–Cas9 gRNA efficiency prediction: an overview of predictive tools and the role of deep learning
The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated
protein 9 (Cas9) system has become a successful and promising technology for gene …
protein 9 (Cas9) system has become a successful and promising technology for gene …
Applications of machine learning in drug discovery and development
Drug discovery and development pipelines are long, complex and depend on numerous
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …
Machine learning in materials science
Traditional methods of discovering new materials, such as the empirical trial and error
method and the density functional theory (DFT)‐based method, are unable to keep pace …
method and the density functional theory (DFT)‐based method, are unable to keep pace …
Deep learning and artificial intelligence methods for Raman and surface-enhanced Raman scattering
Abstract Machine learning is shaping up our lives in many ways. In analytical sciences,
machine learning provides an unprecedented opportunity to extract information from …
machine learning provides an unprecedented opportunity to extract information from …
Review of big data analytics, artificial intelligence and nature-inspired computing models towards accurate detection of COVID-19 pandemic cases and contact tracing
The emergence of the 2019 novel coronavirus (COVID-19) which was declared a pandemic
has spread to 210 countries worldwide. It has had a significant impact on health systems …
has spread to 210 countries worldwide. It has had a significant impact on health systems …
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …