AI Medical Compendium Topic

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Models, Molecular

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Analyzing effect of quadruple multiple sequence alignments on deep learning based protein inter-residue distance prediction.

Scientific reports
Protein 3D structure prediction has advanced significantly in recent years due to improving contact prediction accuracy. This improvement has been largely due to deep learning approaches that predict inter-residue contacts and, more recently, distanc...

Low-N protein engineering with data-efficient deep learning.

Nature methods
Protein engineering has enormous academic and industrial potential. However, it is limited by the lack of experimental assays that are consistent with the design goal and sufficiently high throughput to find rare, enhanced variants. Here we introduce...

Using the antibody-antigen binding interface to train image-based deep neural networks for antibody-epitope classification.

PLoS computational biology
High-throughput B-cell sequencing has opened up new avenues for investigating complex mechanisms underlying our adaptive immune response. These technological advances drive data generation and the need to mine and analyze the information contained in...

Dataset Construction to Explore Chemical Space with 3D Geometry and Deep Learning.

Journal of chemical information and modeling
A dataset is the basis of deep learning model development, and the success of deep learning models heavily relies on the quality and size of the dataset. In this work, we present a new data preparation protocol and build a large fragment-based datase...

Improved protein structure refinement guided by deep learning based accuracy estimation.

Nature communications
We develop a deep learning framework (DeepAccNet) that estimates per-residue accuracy and residue-residue distance signed error in protein models and uses these predictions to guide Rosetta protein structure refinement. The network uses 3D convolutio...

CASSPER is a semantic segmentation-based particle picking algorithm for single-particle cryo-electron microscopy.

Communications biology
Particle identification and selection, which is a prerequisite for high-resolution structure determination of biological macromolecules via single-particle cryo-electron microscopy poses a major bottleneck for automating the steps of structure determ...

Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Molecular diversity
Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 re...

Robust principal component analysis-based prediction of protein-protein interaction hot spots.

Proteins
Proteins often exert their function by binding to other cellular partners. The hot spots are key residues for protein-protein binding. Their identification may shed light on the impact of disease associated mutations on protein complexes and help des...