AIMC Topic: Evolution, Molecular

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The developmental and evolutionary characteristics of transcription factor binding site clustered regions based on an explainable machine learning model.

Nucleic acids research
Gene expression is temporally and spatially regulated by the interaction of transcription factors (TFs) and cis-regulatory elements (CREs). The uneven distribution of TF binding sites across the genome poses challenges in understanding how this distr...

Inpactor2: a software based on deep learning to identify and classify LTR-retrotransposons in plant genomes.

Briefings in bioinformatics
LTR-retrotransposons are the most abundant repeat sequences in plant genomes and play an important role in evolution and biodiversity. Their characterization is of great importance to understand their dynamics. However, the identification and classif...

ATSE: a peptide toxicity predictor by exploiting structural and evolutionary information based on graph neural network and attention mechanism.

Briefings in bioinformatics
MOTIVATION: Peptides have recently emerged as promising therapeutic agents against various diseases. For both research and safety regulation purposes, it is of high importance to develop computational methods to accurately predict the potential toxic...

Learning Retention Mechanisms and Evolutionary Parameters of Duplicate Genes from Their Expression Data.

Molecular biology and evolution
Learning about the roles that duplicate genes play in the origins of novel phenotypes requires an understanding of how their functions evolve. A previous method for achieving this goal, CDROM, employs gene expression distances as proxies for function...

Machine learning-based chemical binding similarity using evolutionary relationships of target genes.

Nucleic acids research
Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional ac...

Predicting reservoir hosts and arthropod vectors from evolutionary signatures in RNA virus genomes.

Science (New York, N.Y.)
Identifying the animal origins of RNA viruses requires years of field and laboratory studies that stall responses to emerging infectious diseases. Using large genomic and ecological datasets, we demonstrate that animal reservoirs and the existence an...

Perspectives and applications of machine learning for evolutionary developmental biology.

Molecular omics
Evolutionary Developmental Biology (Evo-Devo) is an ever-expanding field that aims to understand how development was modulated by the evolutionary process. In this sense, "omic" studies emerged as a powerful ally to unravel the molecular mechanisms u...

Gene multifunctionality scoring using gene ontology.

Journal of bioinformatics and computational biology
Multifunctional genes are important genes because of their essential roles in human cells. Studying and analyzing multifunctional genes can help understand disease mechanisms and drug discovery. We propose a computational method for scoring gene mult...