AIMC Topic: Software

Clear Filters Showing 3011 to 3020 of 3675 articles

BridgeDPI: a novel Graph Neural Network for predicting drug-protein interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Exploring drug-protein interactions (DPIs) provides a rapid and precise approach to assist in laboratory experiments for discovering new drugs. Network-based methods usually utilize a drug-protein association network and predict DPIs by t...

seqgra: principled selection of neural network architectures for genomics prediction tasks.

Bioinformatics (Oxford, England)
MOTIVATION: Sequence models based on deep neural networks have achieved state-of-the-art performance on regulatory genomics prediction tasks, such as chromatin accessibility and transcription factor binding. But despite their high accuracy, their con...

Chest X-ray Analysis With Deep Learning-Based Software as a Triage Test for Pulmonary Tuberculosis: An Individual Patient Data Meta-Analysis of Diagnostic Accuracy.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: Automated radiologic analysis using computer-aided detection software (CAD) could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence on the accuracy of commercially available deep learning-based CAD...

GMNN2CD: identification of circRNA-disease associations based on variational inference and graph Markov neural networks.

Bioinformatics (Oxford, England)
MOTIVATION: With the analysis of the characteristic and function of circular RNAs (circRNAs), people have realized that they play a critical role in the diseases. Exploring the relationship between circRNAs and diseases is of far-reaching significanc...

PIPENN: protein interface prediction from sequence with an ensemble of neural nets.

Bioinformatics (Oxford, England)
MOTIVATION: The interactions between proteins and other molecules are essential to many biological and cellular processes. Experimental identification of interface residues is a time-consuming, costly and challenging task, while protein sequence data...

DNAcycP: a deep learning tool for DNA cyclizability prediction.

Nucleic acids research
DNA mechanical properties play a critical role in every aspect of DNA-dependent biological processes. Recently a high throughput assay named loop-seq has been developed to quantify the intrinsic bendability of a massive number of DNA fragments simult...

AutoSolvate: A toolkit for automating quantum chemistry design and discovery of solvated molecules.

The Journal of chemical physics
The availability of large, high-quality datasets is crucial for artificial intelligence design and discovery in chemistry. Despite the essential roles of solvents in chemistry, the rapid computational dataset generation of solution-phase molecular pr...

A deep dilated convolutional residual network for predicting interchain contacts of protein homodimers.

Bioinformatics (Oxford, England)
MOTIVATION: Deep learning has revolutionized protein tertiary structure prediction recently. The cutting-edge deep learning methods such as AlphaFold can predict high-accuracy tertiary structures for most individual protein chains. However, the accur...

SSpro/ACCpro 6: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, deep learning and structural similarity.

Bioinformatics (Oxford, England)
MOTIVATION: Accurately predicting protein secondary structure and relative solvent accessibility is important for the study of protein evolution, structure and an early-stage component of typical protein 3D structure prediction pipelines.

BACPI: a bi-directional attention neural network for compound-protein interaction and binding affinity prediction.

Bioinformatics (Oxford, England)
MOTIVATION: The identification of compound-protein interactions (CPIs) is an essential step in the process of drug discovery. The experimental determination of CPIs is known for a large amount of funds and time it consumes. Computational model has th...