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Search · four archives
22 papers · ranked by Valyu relevance
Raheel Asghar, Muhammad Faisal Javed, Raid Alrowais, Alamgir Khalil + 4 more
'Abdeliazim Mustafa Mohamed' 'Abdullah Mohamed' 'Nikolai Ivanovich Vatin' 'Dario De Domenico'] This research presents a novel approach of artificial intelligence (AI) based gene expression programming (GEP) for predicting the lateral load carrying capacity of RC rectangular columns when subjected to earthquake loading.…
Fahimeh Ahmadi, Raouf El-Mallawany, Stefanos Papanikolaou, Panagiotis G. Asteris
'Panagiotis G. Asteris'] The progression of optical materials and their associated applications necessitates a profound comprehension of their optical characteristics, with the Judd-Ofelt (JO) theory commonly employed for this purpose. However, the computation of JO parameters (Ω2, Ω4, Ω6) entails wide experimental and…
Zhimei Zhang, Yinglong Huo, Haohui Xin, Zhihua Xiong
Under fatigue loading, the interfacial fatigue life of fiber-reinforced polymer(FRP)-concrete is an important index for the analysis of the fatigue performance of reinforced concrete beams strengthened with FRP materials and the evaluation of the reinforcement effect. To solve the problems of the inconsistent and…
Kejia Liu, Yiping Teng, Fang Liu, Ziqiang Zeng
The fast developments in artificial intelligence together with evolutionary algorithms have not solved all the difficulties that Gene Expression Programming (GEP) encounters when maintaining population diversity and preventing premature convergence. Its restrictions block GEP from successfully handling high-dimensional…
Jin Ding, Tianyu Jiang, Ping Tan, Yi Wang + 5 more
'Chuyuan Huang' 'Jien Ma' 'Youtong Fang' 'AL MAHFOODH'] Gene expression programming (GEP) is one of the most prominent algorithms in function mining. In order to obtain a more accurate function model in configuration parameters-execution efficiency (CP-EE) of map-reduce job in the high-speed railway catenary monitoring…
Gonzalo Álvarez, Ryan S. Bennink, Stephan Irle, Jacek Jakowski
We introduce QuantumGEP, a scientific computer program that uses gene expression programming (GEP) to find a quantum circuit that either (i) maps a given set of input states to a given set of output states, or (ii) transforms a fixed initial state to minimize a given physical quantity of the output state. QuantumGEP is…
Muhammad Naqeeb Nawaz, Sana Ullah Qamar, Badee Alshameri, Muhammad Muneeb Nawaz + 3 more
'Muhammad Muneeb Nawaz' 'Waqas Hassan' 'Tariq Ahmed Awan' 'Ahmed Mohammed'] This study aims to propose a novel and high-accuracy prediction model of plastic limit (PL) based on soil particles passing through sieve # 200 (0.075 mm) using gene expression programming (GEP). PL is used for the classification of…
Moiz Tariq, Azam Khan, Asad Ullah, Jaroslaw Krzywanski + 8 more
'Marcin Sosnowski' 'Karolina Grabowska' 'Dorian Skrobek' 'Ghulam Moeen Uddin' 'Anna Kulakowska' 'Anna Zylka' 'Bachil El Fil'] Predictive models were developed to effectively estimate the RC exterior joint’s shear strength using gene expression programming (GEP). Two separate models are proposed for the exterior joints…
George Chao, Evan Appleton, Clair S. Gutierrez, Lilia Evgeniou + 4 more
Pluripotent cells specialize into numerous cell types by receiving external signals, making fate decisions, and executing differentiation functions – a paradigm similar to computer algorithms. While advances in biosensor design have enabled cells to respond to diverse stimuli, the ability to maintain a synthetic memory…
Haochen Li, Fabian Waschkowski, Yaomin Zhao, Richard D. Sandberg
Data-driven methods are widely used to develop physical models, but there still exist limitations that affect their performance, generalizability and robustness. By combining gene expression programming (GEP) with artificial neural network (ANN), we propose a novel method for symbolic regression called the gene…
Melinda Pohle, Edward Curry, Suzanne Gibson, Adam Brown
Control of mammalian recombinant protein expression underpins the in vitro manufacture and in vivo performance of all biopharmaceutical products. However, routine optimization of protein expression levels in these applications is hampered by a paucity of genetic elements that function predictably across varying…
Mohamed Djallel Dilmi, Hanene Azzag, Mustapha Lebbah
Genetic algorithms are a well-known example of bio-inspired heuristic methods. They mimic natural selection by modeling several operators such as mutation, crossover, and selection. Recent discoveries about Epigenetics regulation processes that occur "on top of" or "in addition to" the genetic basis for inheritance…
Laura Weinstock, Jenna Schambach, Anna Fisher, Cameron Kunstadt + 6 more
Understanding and controlling gene expression in organisms is essential for optimizing biological processes, whether in service of bioeconomic processes, human health, or environmental regulation. Epigenetic modifications play a significant role in regulating gene expression by altering chromatin structure, DNA…
Krishna Rijal, Pankaj Mehta
The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the…
Phillip Clauer, Angelina X. Nou, Tyler Toth, Qiguo Yu + 4 more
of Plants and Microbes for Agriculture, Environment, and Future Applications Authors: Phillip Clauer, Angelina X. Nou, Tyler Toth, Qiguo Yu, Yonatan Chemla, Alice Boo, Kwan Yoon, Christopher Voigt Agriculture is under pressure to provide food for a growing population and the feedstock required to drive the bioeconomy.…
Frederick Starkey, Filippo Menolascina
Synthetic Biology aims to rationally engineer biological systems. Current methods often employ an initial human designed circuit topology and utilise iterative approaches, e.g. directed evolution, to fine-tune part function. This approach can be extremely time consuming and resource intensive whilst often reaching…
Fernando Antoneli, Martin Golubitsky, Jiaxin Jin, Ian Stewart
Gene regulatory networks lie at the heart of many important intracellular signal transduction processes. A Gene Regulatory Network (GRN) is abstractly defined as a directed graph, where the nodes represent genes and the edges represent the causal regulatory interactions between genes. It can be used to construct…
Janet Sasso, Barbara Ambrose, Rumiana Tenchov, Ruchira Datta + 3 more
In the last decade, there has been a shift in research, clinical development, and commercial activity to exploit the many roles of RNA in physiology for use in medicine. With the rapid success in the development of lipid-RNA nanoparticles for mRNA vaccines against COVID-19 and with several approved RNA-based drugs, RNA…
Giacomo Mazzotti, Denis Hartmann, Michael Booth
Cell-free expression of a gene to protein has become a vital tool in nanotechnology and synthetic biology. Remote-control of cell-free systems with multiple, orthogonal wavelengths of light would enable precise, non-invasive modulation, opening many new applications in biology and medicine. While there has been success…
Avery Davis Bell, Francisco Valencia, Annalise B. Paaby
An outstanding question in the evolution of gene expression is the composition of the underlying regulatory architecture and the processes that shape it. Mutations affecting a gene’s expression may reside locally in cis or distally in trans; the accumulation of these changes, their interactions, and their modes of…
Mark Kocherovsky, Illya Bakurov, Wolfgang Banzhaf
While crossover is a critical and often indispensable component in other forms of Genetic Programming, such as Linear- and Tree-based, it has consistently been claimed that it deteriorates search performance in CGP. As a result, a mutation-alone (1 + λ ) evolutionary strategy has become the canonical approach for CGP.…
Joe Harrison, Peter A. N. Bosman, Tanja Alderliesten
The goal in Symbolic Regression (SR) is to discover expressions that accurately map input to output data. Because often the intent is to understand these expressions, there is a trade-off between accuracy and the interpretability of expressions. GP-GOMEA excels at producing small SR expressions (increasing the…