AI Medical Compendium Journal:
Biochimica et biophysica acta. General subjects

Showing 1 to 5 of 5 articles

VotePLMs-AFP: Identification of antifreeze proteins using transformer-embedding features and ensemble learning.

Biochimica et biophysica acta. General subjects
Antifreeze proteins (AFPs) are a unique class of biomolecules capable of protecting other proteins, cell membranes, and cellular structures within organisms from damage caused by freezing conditions. Given the significance of AFPs in various domains ...

ASPTF: A computational tool to predict abiotic stress-responsive transcription factors in plants by employing machine learning algorithms.

Biochimica et biophysica acta. General subjects
BACKGROUND: Abiotic stresses pose serious threat to the growth and yield of crop plants. Several studies suggest that in plants, transcription factors (TFs) are important regulators of gene expression, especially when it comes to coping with abiotic ...

Robosample: A rigid-body molecular simulation program based on robot mechanics.

Biochimica et biophysica acta. General subjects
BACKGROUND: Compared with all-atom molecular dynamics (MD), constrained MD methods allow for larger time steps, potentially reducing computational cost. For this reason, there has been continued interest in improving constrained MD algorithms to incr...

Machine learning and ligand binding predictions: A review of data, methods, and obstacles.

Biochimica et biophysica acta. General subjects
Computational predictions of ligand binding is a difficult problem, with more accurate methods being extremely computationally expensive. The use of machine learning for drug binding predictions could possibly leverage the use of biomedical big data ...

Prediction of peptide binding to MHC using machine learning with sequence and structure-based feature sets.

Biochimica et biophysica acta. General subjects
Selecting peptides that bind strongly to the major histocompatibility complex (MHC) for inclusion in a vaccine has therapeutic potential for infections and tumors. Machine learning models trained on sequence data exist for peptide:MHC (p:MHC) binding...