22 papers · ranked by Valyu relevance
Kaichen Ouyang, Yu, Mingyang, Ke + 11 more
This paper introduces a novel framework linking evolutionary computation to statistical physics by formulating optimization as a statistical phase transition. We propose Wasserstein Evolution (WE), an algorithm based on the Wasserstein gradient flow of a free energy functional, translating the physical competition…
Leyi Zhao, Weijie Huang, Yitong Guo, Jiang Bian + 2 more
Optimizing scientific computing algorithms for modern GPUs remains a labor-intensive and iterative process, requiring repeated cycles of code modification, benchmarking, and tuning across complex hardware and software stacks. While recent work has explored large language model (LLM)–assisted evolutionary algorithms for…
N. Jayalakshmi, K. Sakthivel
To achieve robust and user friendly software, it is crucial to make sure that Graphical User Interfaces (GUI) is of quality and reliable. The paper suggests a new method of Quasi-Oppositional Genetic Sparrow Search Algorithm (OOGSSA) of generating test cases efficiently in GUI. The ultimate goal is to have…
Innocent Sibanda, Geoff Nitschke
The goal of bioengineering in synthetic biology is to redesign, reprogram, and rewire biological systems for specific applications using standardized parts such as promoters and ribosomes. For example, bioengineered micro-organisms capable of cleaning up environmental pollution or producing antibodies de novo to defend…
Max Foreback, Evan Imata, Vincent R. Ragusa, Jacob Weiler + 16 more
Designing scientific instrumentation often requires exploring large, highly constrained design spaces using computationally expensive physics simulations. These simulators pose substantial challenges for integrating evolutionary computation (EC) into scientific design workflows. Evolutionary computation typically…
Kangbien Park
Directed evolution of asexual populations is expected to offer a wide range of benefits to humanity. Achieving efficient directed evolution (DE) requires a quantitative formulation of the experimental methodologies—or logics—that can address potential challenges throughout the evolutionary process. In this article, I…
João Sartori, Eduardo Krempser, Ana Carolina Ramos Guimarães, Lucas de Almeida Machado
The optimization of protein sequences for enhanced binding and stability remains a formidable challenge in bioengineering due to the vastness of sequence space. Existing state-of-the-art methods, including traditional structure-based design and protein language models, use fitness estimators as objective functions to…
Authors not listed
Finding the most stable adsorption geometry of a flexible molecule on a catalytic surface remains a key challenge due to the high dimensionality and ruggedness of the potential energy surface. We present a Gradient-Enhanced Genetic Algorithm (GE-GA) for the global optimization of adsorbate–surface configurations…
Authors not listed
Designing molecules with specific target properties remains a fundamental challenge in computational chemistry. While existing approaches show promise, most rely on simplified representations like SMILES strings or 2D graphs that lack essential three-dimensional geometric information. We present EvoDiffMol, a…
Kangbien Park
Humans have long employed directed evolution (DE) to engineer desired biological traits. In this paper, I introduce an algebraic framework that provides a quantitative representation of the general phenotypic traits of asexual populations, enabling the systematic modeling of DE processes. Within this framework, key…
Alex Bogdan
Many real-world optimization problems are not naturally homogeneous vectors but composite design objects with heterogeneous parameters: integers, real values, Booleans, categoricals, complex-valued descriptors, and embedding vectors. Standard evolutionary algorithms flatten these into a single chromosome and apply…
Minghao Yan, Bo Peng, Benjamin Coleman, Ziqi Chen + 10 more
Large language models have become drivers of evolutionary search, but most systems rely on a fixed, prompt-elicited policy to sample next candidates. This limits adaptation in practical engineering and research tasks, where evaluations are expensive, and progress depends on learning task-specific search dynamics. We…
Pablo Japón, Jesús Miró-Bueno, Ángel Goñi-Moreno
Gene expression transforms information encoded in DNA into functional protein activity. Although these systems are often assumed to be static-thus enabling the programming of genetic circuits to meet predefined specifications-they are, in fact, dynamic and subject to evolutionary change. As sequences accumulate subtle…
Liudmyla Vasylenko, Adi Livnat
At the fundamental conceptual level, two alternatives have traditionally been considered for how mutations arise and how evolution happens: 1) random mutation and natural selection, and 2) Lamarckism. Recently, the theory of Interaction-based Evolution (IBE) has been proposed, according to which mutations are neither…
Authors not listed
Compositionally complex materials, e.g. high-entropy alloys/oxides, have long been of research interest for their unique mechanical and functional properties thanks to the synergistic effects between the large number of components. More recently, they have emerged as a promising platform for the development of novel…
Peng Chen, Jonathan Asher Pachter, Jacob G. Scott, Michael Hinczewski
Therapeutic resistance, which poses a central challenge in cancer and infectious disease treatment, arises from the evolutionary dynamics of heterogeneous populations as a natural consequence of the evolutionary tendency towards higher fitness. Here we introduce SHEPHERD (Stochastic Heterogeneity–informed Evolutionary…
Na Li, Zi Miao, Sha Zhou, Haoxiang Zhou + 3 more
The Educational Competition Optimizer (ECO) formulates search as a three-stage didactic process-primary, secondary and tertiary learning-but the original framework suffers from scarce information exchange, sluggish late-stage convergence and an unstable exploration-exploitation ratio. We present EECO, which introduces…
Kangbien Park, Jiapeng Liu
Directed evolution of asexual populations is expected to offer a wide range of benefits to humanity. Achieving efficient directed evolution (DE) requires a quantitative formulation of experimental methodologies-or logics-that can address potential challenges throughout the evolutionary process. In this article, ten…
Authors not listed
Machine olfaction—the artificial replication of the sense of smell—faces significant challenges due to the absence of large, standardized training datasets. Unlike vision, language, and audio models, which benefit from extensive corpora such as ImageNet, GLUE, and AudioSet, olfaction lacks scaled equivalents and…
Lewis Grozinger, Jesuś Miró-Bueno, Ángel Goñi-Moreno
The programming of computations in living cells is achieved by manipulating information flows within genetic networks. Typically, gene expression is discretized into high and low levels, representing 0 and 1 logic values to encode a single bit of information. However, molecular signalling and computation in living…
William Dorrell, Peter E. Latham, Timothy E. J. Behrens, James C. R. Whittington
The efficient coding hypothesis presents a compelling success story for theoretical and systems neuroscience. It marshals a unifying idea, that neural codes can be understood as efficient encodings of natural stimuli, to explain phenomena from across sensory systems, sometimes with exquisite precision. However, similar…
Authors not listed
This comprehensive review examines the evolution of autonomous materials synthesis laboratories that integrate artificial intelligence with advanced robotics to accelerate discovery. Traditional materials development pipelines typically require 10-20 years, but self-driving laboratories (SDLs) and Materials…