AIMC Topic: Biological Evolution

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Enhancing cryo-EM structure prediction with DeepTracer and AlphaFold2 integration.

Briefings in bioinformatics Mar 27, 2024
Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the ...
Machine Learning Databases, Factual Amino Acid Sequence Cryoelectron Microscopy Biological Evolution
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Inferring Historical Introgression with Deep Learning.

Systematic biology Nov 1, 2023
Resolving phylogenetic relationships among taxa remains a challenge in the era of big data due to the presence of genetic admixture in a wide range of organisms. Rapidly developing sequencing technologies and statistical tests enable evolutionary rel...
Animals Phylogeny Deep Learning Biological Evolution Hybridization, Genetic Gene Flow Butterflies
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Evolving Modularity in Soft Robots Through an Embodied and Self-Organizing Neural Controller.

Artificial life Aug 4, 2022
Modularity is a desirable property for embodied agents, as it could foster their suitability to different domains by disassembling them into transferable modules that can be reassembled differently. We focus on a class of embodied agents known as vox...
Robotics Locomotion Biological Evolution
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How the History of Changing Environments Affects Traits of Evolvable Robot Populations.

Artificial life Jun 28, 2022
The environment is one of the key factors in the emergence of intelligent creatures, but it has received little attention within the Evolutionary Robotics literature. This article investigates the effects of changing environments on morphological and...
Phenotype Robotics Biological Evolution
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Evolving Multimodal Robot Behavior via Many Stepping Stones with the Combinatorial Multiobjective Evolutionary Algorithm.

Evolutionary computation Jun 1, 2022
An important challenge in reinforcement learning is to solve multimodal problems, where agents have to act in qualitatively different ways depending on the circumstances. Because multimodal problems are often too difficult to solve directly, it is of...
Algorithms Learning Robotics Problem Solving Biological Evolution
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How signals interact in multimodal displays: Insights from a robotic frog.

The Journal of animal ecology Apr 1, 2022
Caldart, M. V., M. B. dos Santos & G. Machado (2021). Function of a multimodal signal: a multiple hypothesis test using a robot frog Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13620. Animals can communicate using signals perceived b...
Animals Robotics Robotic Surgical Procedures Anura Biological Evolution
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mCNN-ETC: identifying electron transporters and their functional families by using multiple windows scanning techniques in convolutional neural networks with evolutionary information of protein sequences.

Briefings in bioinformatics Jan 17, 2022
In the past decade, convolutional neural networks (CNNs) have been used as powerful tools by scientists to solve visual data tasks. However, many efforts of convolutional neural networks in solving protein function prediction and extracting useful in...
Humans Neural Networks, Computer Proteins Amino Acid Sequence Electrons Biological Evolution
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Evolutionary artificial intelligence algorithms for the one-way road orientation planning problem with multiple venues: An example of evacuation planning in Taiwan.

Science progress Sep 1, 2021
INTRODUCTION: In large-scale events such as concerts and sports competitions, participants often leave the venue at the same time to return to their respective destinations. Improper traffic planning and traffic light operation usually lead to traffi...
Humans Artificial Intelligence Algorithms Taiwan Biological Evolution
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Predictive Models of Genetic Redundancy in Arabidopsis thaliana.

Molecular biology and evolution Jul 29, 2021
Genetic redundancy refers to a situation where an individual with a loss-of-function mutation in one gene (single mutant) does not show an apparent phenotype until one or more paralogs are also knocked out (double/higher-order mutant). Previous studi...
Machine Learning Models, Genetic Gene Duplication Biological Evolution Arabidopsis
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CATH functional families predict functional sites in proteins.

Bioinformatics (Oxford, England) May 23, 2021
MOTIVATION: Identification of functional sites in proteins is essential for functional characterization, variant interpretation and drug design. Several methods are available for predicting either a generic functional site, or specific types of funct...
Humans Machine Learning Proteins Amino Acid Sequence Biological Evolution
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