AI Medical Compendium Journal:
Molecular biology and evolution

Showing 1 to 10 of 21 articles

MEGA-GPT: Artificial Intelligence Guidance and Building Analytical Protocols Using MEGA Software.

Molecular biology and evolution
Over the past three decades, the Molecular Evolutionary Genetics Analysis (MEGA) software has evolved into a powerful tool with an ever-expanding suite of functionalities. Yet, despite its user-friendly design and widespread adoption by researchers a...

Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning.

Molecular biology and evolution
Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data ha...

Phyloformer: Fast, Accurate, and Versatile Phylogenetic Reconstruction with Deep Neural Networks.

Molecular biology and evolution
Phylogenetic inference aims at reconstructing the tree describing the evolution of a set of sequences descending from a common ancestor. The high computational cost of state-of-the-art maximum likelihood and Bayesian inference methods limits their us...

Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.

Molecular biology and evolution
Phylodynamics is central to understanding infectious disease dynamics through the integration of genomic and epidemiological data. Despite advancements, including the application of deep learning to overcome computational limitations, significant cha...

Tree Sequences as a General-Purpose Tool for Population Genetic Inference.

Molecular biology and evolution
As population genetic data increase in size, new methods have been developed to store genetic information in efficient ways, such as tree sequences. These data structures are computationally and storage efficient but are not interchangeable with exis...

Computationally Efficient Demographic History Inference from Allele Frequencies with Supervised Machine Learning.

Molecular biology and evolution
Inferring past demographic history of natural populations from genomic data is of central concern in many studies across research fields. Previously, our group had developed dadi, a widely used demographic history inference method based on the allele...

Simulations of Sequence Evolution: How (Un)realistic They Are and Why.

Molecular biology and evolution
MOTIVATION: Simulating multiple sequence alignments (MSAs) using probabilistic models of sequence evolution plays an important role in the evaluation of phylogenetic inference tools and is crucial to the development of novel learning-based approaches...

Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data.

Molecular biology and evolution
Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involve...

Inference of Coalescence Times and Variant Ages Using Convolutional Neural Networks.

Molecular biology and evolution
Accurate inference of the time to the most recent common ancestor (TMRCA) between pairs of individuals and of the age of genomic variants is key in several population genetic analyses. We developed a likelihood-free approach, called CoalNN, which use...

The Statistical Trends of Protein Evolution: A Lesson from AlphaFold Database.

Molecular biology and evolution
The recent development of artificial intelligence provides us with new and powerful tools for studying the mysterious relationship between organism evolution and protein evolution. In this work, based on the AlphaFold Protein Structure Database (Alph...