AI Medical Compendium Journal:
Bioinformatics (Oxford, England)

Showing 101 to 110 of 847 articles

DDGemb: predicting protein stability change upon single- and multi-point variations with embeddings and deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimen...

Improving generalizability of drug-target binding prediction by pre-trained multi-view molecular representations.

Bioinformatics (Oxford, England)
MOTIVATION: Most drugs start on their journey inside the body by binding the right target proteins. This is the reason that numerous efforts have been devoted to predicting the drug-target binding during drug development. However, the inherent divers...

BetaAlign: a deep learning approach for multiple sequence alignment.

Bioinformatics (Oxford, England)
MOTIVATION: Multiple sequence alignments (MSAs) are extensively used in biology, from phylogenetic reconstruction to structure and function prediction. Here, we suggest an out-of-the-box approach for the inference of MSAs, which relies on algorithms ...

Quantitative analysis of the dexamethasone side effect on human-derived young and aged skeletal muscle by myotube and nuclei segmentation using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Skeletal muscle cells (skMCs) combine together to create long, multi-nucleated structures called myotubes. By studying the size, length, and number of nuclei in these myotubes, we can gain a deeper understanding of skeletal muscle develop...

Ligand identification in CryoEM and X-ray maps using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule li...

DPAM-AI: a domain parser for AlphaFold models powered by artificial intelligence.

Bioinformatics (Oxford, England)
MOTIVATION: Due to the breakthrough in protein structure prediction by AlphaFold, the scientific community has access to 200 million predicted protein structures with near-atomic accuracy from the AlphaFold protein structure DataBase (AFDB), covering...

TPepPro: a deep learning model for predicting peptide-protein interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Peptides and their derivatives hold potential as therapeutic agents. The rising interest in developing peptide drugs is evidenced by increasing approval rates by the FDA of USA. To identify the most potential peptides, study on peptide-pr...

Knowledge mining of brain connectivity in massive literature based on transfer learning.

Bioinformatics (Oxford, England)
MOTIVATION: Neuroscientists have long endeavored to map brain connectivity, yet the intricate nature of brain networks often leads them to concentrate on specific regions, hindering efforts to unveil a comprehensive connectivity map. Recent advanceme...

Improved prediction of post-translational modification crosstalk within proteins using DeepPCT.

Bioinformatics (Oxford, England)
MOTIVATION: Post-translational modification (PTM) crosstalk events play critical roles in biological processes. Several machine learning methods have been developed to identify PTM crosstalk within proteins, but the accuracy is still far from satisfa...

DeepDR: a deep learning library for drug response prediction.

Bioinformatics (Oxford, England)
SUMMARY: Accurate drug response prediction is critical to advancing precision medicine and drug discovery. Recent advances in deep learning (DL) have shown promise in predicting drug response; however, the lack of convenient tools to support such mod...