AI Medical Compendium Journal:
Methods in molecular biology (Clifton, N.J.)

Showing 31 to 40 of 269 articles

Interpreting Gene Ontology Annotations Derived from Sequence Homology Methods.

Methods in molecular biology (Clifton, N.J.)
The Gene Ontology (GO) project describes the functions of the gene products of organisms from all kingdoms of life in a standardized way, enabling powerful analyses of experiments involving genome-wide analysis. The scientific literature is used to c...

AI-Assisted Processing Pipeline to Boost Protein Isoform Detection.

Methods in molecular biology (Clifton, N.J.)
Proteomics, the study of proteins within biological systems, has seen remarkable advancements in recent years, with protein isoform detection emerging as one of the next major frontiers. One of the primary challenges is achieving the necessary peptid...

Assessment of Protein-Protein Docking Models Using Deep Learning.

Methods in molecular biology (Clifton, N.J.)
Protein-protein interactions are involved in almost all processes in a living cell and determine the biological functions of proteins. To obtain mechanistic understandings of protein-protein interactions, the tertiary structures of protein complexes ...

Machine Learning Methods in Protein-Protein Docking.

Methods in molecular biology (Clifton, N.J.)
An exponential increase in the number of publications that address artificial intelligence (AI) usage in life sciences has been noticed in recent years, while new modeling techniques are constantly being reported. The potential of these methods is va...

Application of Artificial Neural Network and Genetic Algorithm Modeling for In Vitro Regeneration of Seaweed Seedling Production.

Methods in molecular biology (Clifton, N.J.)
Marine macro-algae, commonly known as "seaweed," are used in everyday commodity products worldwide for food, feed, and biostimulant for plants and animals and continue to be one of the conspicuous components of world aquaculture production. However, ...

DeepHLApan: A Deep Learning Approach for the Prediction of Peptide-HLA Binding and Immunogenicity.

Methods in molecular biology (Clifton, N.J.)
Neoantigens are crucial in distinguishing cancer cells from normal ones and play a significant role in cancer immunotherapy. The field of bioinformatics prediction for tumor neoantigens has rapidly developed, focusing on the prediction of peptide-HLA...

Deep Learning-Based HLA Allele Imputation Applicable to GWAS.

Methods in molecular biology (Clifton, N.J.)
Human leukocyte antigen (HLA) imputation is an essential step following genome-wide association study, particularly when putative associations in HLA genes are identified, to fully understand the genetic basis of human traits. Different HLA imputatio...

Machine Learning Methods for the Analysis of the Patch-Clamp Signals.

Methods in molecular biology (Clifton, N.J.)
Patch-clamp technique provides a unique possibility to record the ion channels' activity. This method enables tracking the changes in their functional states at controlled conditions on a real-time scale. Kinetic parameters evaluated for the patch-cl...

Application of Deep Learning for Studying NMDA Receptors.

Methods in molecular biology (Clifton, N.J.)
Artificial intelligence underwent remarkable advancement in the past decade, revolutionizing our way of thinking and unlocking unprecedented opportunities across various fields, including drug development. The emergence of large pretrained models, su...

Deep Learning-Based Cell Tracking in Deforming Organs and Moving Animals.

Methods in molecular biology (Clifton, N.J.)
Cell tracking is an essential step in extracting cellular signals from moving cells, which is vital for understanding the mechanisms underlying various biological functions and processes, particularly in organs such as the brain and heart. However, c...