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

Showing 101 to 110 of 269 articles

Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography.

Methods in molecular biology (Clifton, N.J.)
Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the und...

Turning Failures into Applications: The Problem of Protein ΔΔG Prediction.

Methods in molecular biology (Clifton, N.J.)
After nearly two decades of research in the field of computational methods based on machine learning and knowledge-based potentials for ΔG and ΔΔG prediction upon variations, we now realize that all the approaches are poorly performing when tested on...

Application of Correlation Pre-Filtering Neural Network to DNA Methylation Data: Biological Aging Prediction.

Methods in molecular biology (Clifton, N.J.)
We introduce the CPFNN (Correlation Pre-Filtering Neural Network) for biological age prediction based on blood DNA methylation data. The model is built on 20,000 top correlated DNA methylation features and trained by 1810 healthy samples from GEO dat...

Machine Learning-driven Protein Library Design: A Path Toward Smarter Libraries.

Methods in molecular biology (Clifton, N.J.)
Proteins are small yet valuable biomolecules that play a versatile role in therapeutics and diagnostics. The intricate sequence-structure-function paradigm in the realm of proteins opens the possibility for directly mapping amino acid sequence to fun...

Construction of Molecular Robots from Microtubules for Programmable Swarming.

Methods in molecular biology (Clifton, N.J.)
Swarm robotics has been attracting much attention in recent years in the field of robotics. This chapter describes a methodology for the construction of molecular swarm robots through precise control of active self-assembly of microtubules (MTs). Det...

Genome-Enabled Prediction Methods Based on Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Growth of artificial intelligence and machine learning (ML) methodology has been explosive in recent years. In this class of procedures, computers get knowledge from sets of experiences and provide forecasts or classification. In genome-wide based pr...

Personal Dense Dynamic Data Clouds Connect Systems Biomedicine to Scientific Wellness.

Methods in molecular biology (Clifton, N.J.)
The dramatic convergence of molecular biology, genomics, proteomics, metabolomics, bioinformatics, and artificial intelligence has provided a substrate for deep understanding of the biological basis of health and disease. Systems biology is a holisti...

Development and Applications of Interoperable Biomedical Ontologies for Integrative Data and Knowledge Representation and Multiscale Modeling in Systems Medicine.

Methods in molecular biology (Clifton, N.J.)
The data FAIR Guiding Principles state that all data should be Findable, Accessible, Interoperable, and Reusable. Ontology is critical to data integration, sharing, and analysis. Given thousands of ontologies have been developed in the era of artific...

Automated Classification of Cellular Phenotypes Using Machine Learning in Cellprofiler and CellProfiler Analyst.

Methods in molecular biology (Clifton, N.J.)
Cell images provide a multitude of phenotypic information, which in its entirety the human eye can hardly perceive. Automated image analysis and machine learning approaches enable the unbiased identification and analysis of cellular mechanisms and as...

Machine Learning Prediction of Antimicrobial Peptides.

Methods in molecular biology (Clifton, N.J.)
Antibiotic resistance constitutes a global threat and could lead to a future pandemic. One strategy is to develop a new generation of antimicrobials. Naturally occurring antimicrobial peptides (AMPs) are recognized templates and some are already in c...