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

Showing 111 to 120 of 269 articles

Automated Microscopy Image Segmentation and Analysis with Machine Learning.

Methods in molecular biology (Clifton, N.J.)
The development of automated quantitative image analysis pipelines requires thoughtful considerations to extract meaningful information. Commonly, extraction rules for quantitative parameters are defined and agreed beforehand to ensure repeatability ...

Cloning Strategies for the Generation of Recombinant Capripoxvirus Through the Use of Screening and Selection Markers.

Methods in molecular biology (Clifton, N.J.)
The ability to manipulate capripoxvirus through gene knockouts and gene insertions has become an increasingly valuable research tool in elucidating the function of individual genes of capripoxvirus, as well as in the development of capripoxvirus-base...

Plant Reactome and PubChem: The Plant Pathway and (Bio)Chemical Entity Knowledgebases.

Methods in molecular biology (Clifton, N.J.)
Plant Reactome (https://plantreactome.gramene.org) and PubChem ( https://pubchem.ncbi.nlm.nih.gov ) are two reference data portals and resources for curated plant pathways, small molecules, metabolites, gene products, and macromolecular interactions....

Machine Learning for Image Analysis: Leaf Disease Segmentation.

Methods in molecular biology (Clifton, N.J.)
Plant phenomics field has seen a great increase in scalability in the last decade mainly due to technological advances in remote sensors and phenotyping platforms. These are capable of screening thousands of plants many times throughout the day, gene...

Cell-Free Biosensors and AI Integration.

Methods in molecular biology (Clifton, N.J.)
Cell-free biosensors hold a great potential as alternatives for traditional analytical chemistry methods providing low-cost low-resource measurement of specific chemicals. However, their large-scale use is limited by the complexity of their developme...

Artificial Intelligence for Vaccine Design.

Methods in molecular biology (Clifton, N.J.)
Often likened to "the new electricity," artificial intelligence (AI) has broad and sweeping impact in many areas. Perhaps most exciting among these are in bioinformatics as AI allows for new and increasingly powerful ways of understanding genomics, p...

Artificial Intelligence in Vaccine and Drug Design.

Methods in molecular biology (Clifton, N.J.)
Knowledge in the fields of biochemistry, structural biology, immunological principles, microbiology, and genomics has all increased dramatically in recent years. There has also been tremendous growth in the fields of data science, informatics, and ar...

Using Gene Ontology to Annotate and Prioritize Microarray Data.

Methods in molecular biology (Clifton, N.J.)
The results of high-throughput experiments consist of numerous candidate genes, proteins, or other molecules potentially associated with diseases. A challenge for omics science is the knowledge extraction from the results and the filtering of promisi...

Vaccine Design by Reverse Vaccinology and Machine Learning.

Methods in molecular biology (Clifton, N.J.)
Reverse vaccinology (RV) is the state-of-the-art vaccine development strategy that starts with predicting vaccine antigens by bioinformatics analysis of the whole genome of a pathogen of interest. Vaxign is the first web-based RV vaccine prediction m...

Artificial Intelligence in Drug Safety and Metabolism.

Methods in molecular biology (Clifton, N.J.)
The use of artificial intelligence methods in drug safety began in the early 2000s with applications such as predicting bacterial mutagenicity and hERG inhibition. The field has been endlessly expanding ever since and the models have become more comp...