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Phylogeny

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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...

DeePVP: Identification and classification of phage virion proteins using deep learning.

GigaScience
BACKGROUND: Many biological properties of phages are determined by phage virion proteins (PVPs), and the poor annotation of PVPs is a bottleneck for many areas of viral research, such as viral phylogenetic analysis, viral host identification, and ant...

EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.

Nucleic acids research
Discovering rare cancer driver genes is difficult because their mutational frequency is too low for statistical detection by computational methods. EPIMUTESTR is an integrative nearest-neighbor machine learning algorithm that identifies such marginal...

A LASSO-based approach to sample sites for phylogenetic tree search.

Bioinformatics (Oxford, England)
MOTIVATION: In recent years, full-genome sequences have become increasingly available and as a result many modern phylogenetic analyses are based on very long sequences, often with over 100 000 sites. Phylogenetic reconstructions of large-scale align...

Morphological Development at the Evolutionary Timescale: Robotic Developmental Evolution.

Artificial life
Evolution and development operate at different timescales; generations for the one, a lifetime for the other. These two processes, the basis of much of life on earth, interact in many non-trivial ways, but their temporal hierarchy-evolution overarchi...

EMBER: multi-label prediction of kinase-substrate phosphorylation events through deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Kinase-catalyzed phosphorylation of proteins forms the backbone of signal transduction within the cell, enabling the coordination of numerous processes such as the cell cycle, apoptosis, and differentiation. Although on the order of 105 p...

Machine Learning Prediction of Non-Coding Variant Impact in Human Retinal cis-Regulatory Elements.

Translational vision science & technology
PURPOSE: Prior studies have demonstrated the significance of specific cis-regulatory variants in retinal disease; however, determining the functional impact of regulatory variants remains a major challenge. In this study, we utilized a machine learni...

AniAMPpred: artificial intelligence guided discovery of novel antimicrobial peptides in animal kingdom.

Briefings in bioinformatics
With advancements in genomics, there has been substantial reduction in the cost and time of genome sequencing and has resulted in lot of data in genome databases. Antimicrobial host defense proteins provide protection against invading microbes. But c...

The accurate prediction and characterization of cancerlectin by a combined machine learning and GO analysis.

Briefings in bioinformatics
Cancerlectins, lectins linked to tumor progression, have become the focus of cancer therapy research for their carbohydrate-binding specificity. However, the specific characterization for cancerlectins involved in tumor progression is still unclear. ...

Using graph convolutional neural networks to learn a representation for glycans.

Cell reports
As the only nonlinear and the most diverse biological sequence, glycans offer substantial challenges for computational biology. These carbohydrates participate in nearly all biological processes-from protein folding to viral cell entry-yet are still ...