Current progress and open challenges for applying deep learning across the biosciences
Deep Learning (DL) has recently enabled unprecedented advances in one of the grand
challenges in computational biology: the half-century-old problem of protein structure …
challenges in computational biology: the half-century-old problem of protein structure …
Network pharmacology prediction and molecular docking-based strategy to explore the potential mechanism of Huanglian Jiedu Decoction against sepsis
X Li, S Wei, S Niu, X Ma, H Li, M **g, Y Zhao - Computers in biology and …, 2022 - Elsevier
Abstract Background Huanglian Jiedu Decoction (HLJDD) is a classical herbal formula with
potential efficacy in the treatment of sepsis. However, the main components and potential …
potential efficacy in the treatment of sepsis. However, the main components and potential …
The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest
Much of the complexity within cells arises from functional and regulatory interactions among
proteins. The core of these interactions is increasingly known, but novel interactions …
proteins. The core of these interactions is increasingly known, but novel interactions …
Predicting transcriptional outcomes of novel multigene perturbations with GEARS
Understanding cellular responses to genetic perturbation is central to numerous biomedical
applications, from identifying genetic interactions involved in cancer to develo** methods …
applications, from identifying genetic interactions involved in cancer to develo** methods …
New insights into the genetic etiology of Alzheimer's disease and related dementias
Abstract Characterization of the genetic landscape of Alzheimer's disease (AD) and related
dementias (ADD) provides a unique opportunity for a better understanding of the associated …
dementias (ADD) provides a unique opportunity for a better understanding of the associated …
Integrating de novo and inherited variants in 42,607 autism cases identifies mutations in new moderate-risk genes
To capture the full spectrum of genetic risk for autism, we performed a two-stage analysis of
rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new …
rare de novo and inherited coding variants in 42,607 autism cases, including 35,130 new …
Large-scale integration of the plasma proteome with genetics and disease
The plasma proteome can help bridge the gap between the genome and diseases. Here we
describe genome-wide association studies (GWASs) of plasma protein levels measured with …
describe genome-wide association studies (GWASs) of plasma protein levels measured with …
Autism genes converge on asynchronous development of shared neuron classes
Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes
spanning a wide range of biological functions,,,,–. The alterations in the human brain …
spanning a wide range of biological functions,,,,–. The alterations in the human brain …
Graph neural networks: foundation, frontiers and applications
The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …
recent years. Graph neural networks, also known as deep learning on graphs, graph …
Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …