A5083979280- Genetics, Aging, and Longevity in Model Organisms
- Machine Learning in Bioinformatics
- Photoreceptor and optogenetics research
- Metaheuristic Optimization Algorithms Research
- Circadian rhythm and melatonin
- Reinforcement Learning in Robotics
- Neural Networks and Applications
- Adaptive Dynamic Programming Control
- Genomics and Phylogenetic Studies
- Fractal and DNA sequence analysis
- Advanced Multi-Objective Optimization Algorithms
- Hydrogen's biological and therapeutic effects
- Origins and Evolution of Life
- Adaptive Control of Nonlinear Systems
- Adversarial Robustness in Machine Learning
- Physiological and biochemical adaptations
- Algorithms and Data Compression
- Expert finding and Q&A systems
- Mobile Crowdsensing and Crowdsourcing
- Machine Learning and Data Classification
- Digital Media Forensic Detection
- Metabolism and Genetic Disorders
- MicroRNA in disease regulation
- Design Education and Practice
- Mitochondrial Function and Pathology
Beijing Normal University
2023-2025
University of Jinan
2017-2022
Beijing Chao-Yang Hospital
2010
Capital Medical University
2010
Genetic information often exhibits hierarchical and nested relationships, achieved through the reuse of repetitive subsequences such as duplicons transposable elements, a concept termed “evolutionary tinkering” by François Jacob. Current bioinformatics tools struggle to capture these, particularly nested, relationships. To address this, we utilized ladderpath, an approach within broader category algorithmic theory, introducing two key measures: order rate <a:math...
Brute force random search, effective in exploring solution spaces, often becomes inefficient or infeasible real-world scenarios with vast spaces. A more method, akin to natural evolution, involves recombining existing modules into new ones, a concept known as “evolution tinkering” introduced by François Jacob. Understanding these mechanisms is crucial for comprehending evolution and designing evolution-inspired algorithms. This study employs genetic algorithms (GAs) quantitatively explore...
Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on neural architectures of male and hermaphrodite C. elegans association with sexually dimorphic behaviors. We applied graph theory computational neuroscience methods to systematically discern features these two networks. Our findings revealed that a small percentage sexual-specific neurons exerted dominance throughout entire net-work,...
Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on neural architectures of male and hermaphrodite C. elegans association with sexually dimorphic behaviors. We applied graph theory computational neuroscience methods to systematically discern features these two networks. Our findings revealed that a small percentage sexual-specific neurons exerted dominance throughout entire net-work,...
Abstract Genetic information often exhibits hierarchical and nested relationships, achieved through the reuse of repetitive subsequences such as duplicons transposable elements, a concept termed ``evolutionary tinkering'' by Fran\c{c}ois Jacob. Current bioinformatics tools struggle to capture these, particularly nested, relationships. To address this, we utilized Ladderpath, new approach within broader category Algorithmic Information Theory, introducing two key measures: order-rate $\eta$...
Classical benchmark problems utilize multiple transformation techniques to increase optimization difficulty, e.g., shift for anti centering effect and rotation dimension sensitivity. Despite testing the invariance, however, such operations do not really change landscape's "shape", but rather than "view point". For instance, after rotated, ill conditional are turned around in terms of orientation still keep proportional components, which, some extent, does create much obstacle optimization....
Abstract Background : In bioinformatics, tools like multiple sequence alignment and entropy methods probe information evolutionary relationships between species. Although powerful, they might miss crucial hierarchical formed by the reuse of repetitive subsequences duplicons transposable elements. Such are governed ''evolutionary tinkering'', as described François Jacob. The newly developed Ladderpath theory provides a quantitative framework to describe these relationships. Results Based on...
<title>Abstract</title> Brute force random search, effective in exploring solution spaces, often becomes inefficient or infeasible real-world scenarios with vast spaces. A more method, akin to natural evolution, involves recombining existing modules into new ones, a concept known as “evolution tinkering” introduced by François Jacob. Understanding these mechanisms is crucial for comprehending evolution and designing evolution-inspired algorithms. This study employs genetic algorithms (GAs)...
This study introduces an artificial neural network (ANN) for image classification task, inspired by the aversive olfactory learning circuits of nematode Caenorhabditis elegans (C. elegans). Despite remarkable performance ANNs in a variety tasks, they face challenges such as excessive parameterization, high training costs and limited generalization capabilities. C. elegans, with its simple nervous system comprising only 302 neurons, serves paradigm neurobiological research is capable complex...
Abstract Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on neural architectures of male and hermaphrodite C. elegans association with sexually dimorphic behaviors. We applied graph theory computational neuroscience methods to systematically discern features these two networks. Our findings revealed that a small percentage sexual-specific neurons exerted dominance throughout entire net-work,...
With the arrival of era "we media", Community Question Answering(CQA) websites become a special media" platforms gradually. In this type platforms, it has evolved as an interesting problem discover most authoritative answer provider in different fields because number providers is key influential factor successful CQA system. Recently, there are some methods mining users who focus on quality answers provided. However, contents vary lot and will complex if they include images or videos, which...
This study introduces an artificial neural network (ANN) for image classification task, inspired by the aversive olfactory learning circuit in Caenorhabditis elegans (C. elegans). Although networks (ANNs) have demonstrated remarkable performance various tasks, they still encounter challenges including excessive parameterization, high training costs and limited generalization capabilities, etc. C. elegans, boasting a simple nervous system consisting of merely 302 neurons, is capable...
Particle swarm optimization (PSO) in recent years has been widely applied to solve various real world problems. However, for ill conditioned problems with largely different sensitivity the objective function, classical PSO cannot search optimal solution efficiently due best position-guided strategy that wastes lots of source searching undesirable areas. Therefore, this paper proposes a novel velocity reinforced mechanism (VR) solving m-conditional Two implementations mechanism, particle and...
This manuscript is engaged in the intricacies of optimizing control conundrums inherent to enigmatic, unknown discrete-time linear systems, underscored by an intractable discounted infinite-horizon value function. To forge a data-driven conductor, we unveil algebraic Riccati equation (D-ARE) and cast analytical gaze upon on-policy reinforcement learning (RL) algorithm. From this springboard, erect two computational scaffoldsnamely, model-based model-free off-policy RL algorithmsto surmount...
Abstract Creating a man‐made life in the laboratory is one of science’s most intriguing yet challenging problems. Advances synthetic biology and related theories, particularly those to origin life, have laid groundwork for further exploration understanding this field artificial or life. But there remains wealth quantitative mathematical models tools that be applied area. In paper, we review two main approaches often employed life: top‐down approach reduces complexity extant existing living...
The discrepancies between the mathematical model of control systems and real dynamical seriously affect performance controller. This paper considers <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$H$</tex> <inf xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> problem for unknown discrete-time linear with time-varying uncertainties. A robust controller is designed using on-policy off-policy reinforcement learning (RL) methods. Interestingly,...
Classical benchmark problems utilize multiple transformation techniques to increase optimization difficulty, e.g., shift for anti centering effect and rotation dimension sensitivity. Despite testing the invariance, however, such operations do not really change landscape's "shape", but rather than "view point". For instance, after rotated, ill conditional are turned around in terms of orientation still keep proportional components, which, some extent, does create much obstacle optimization....