14 papers · ranked by Valyu relevance
Jialing Yan, Gang Hu, Jiulong Zhang, Heming Jia + 2 more
'Xuewen Xia'] To address the shortcomings of the recently proposed Fick’s Law Algorithm, which is prone to local convergence and poor convergence efficiency, we propose a multi-strategy improved Fick’s Law Algorithm (FLAS). The method combines multiple effective strategies, including differential mutation strategy…
Authors not listed
Accurately predicting the diverse bound-state conformations of small molecules is crucial for successful drug discovery and design, particularly when detailed protein-ligand interactions are unknown. Established tools exist, but efficiently exploring the vast conformational space remains challenging. This work…
Ran Wang, Weiquan Huang, Junyu Wu, Chen Chen + 3 more
To address the rapid population diversity loss and premature convergence of the Artificial Lemming Algorithm (ALA) in complex optimization problems, this paper proposes an Improved Artificial Lemming Algorithm (IALA) with multi-strategy enhancements inspired by lemming behavior. First, a non-uniform mutation operator…
Ali Asghari, Mohammadhossein Mohammadi, Heming Jia
Metaheuristic algorithms are widely used to find optimal or near-optimal solutions for complex problems by taking inspiration from natural behaviors and processes. Although many different methods have been developed, a common problem in many of them is maintaining a good balance between exploration and exploitation and…
Ahmed F. Ali, Mohamed A. Tawhid
Cuckoo search algorithm is a promising metaheuristic population based method. It has been applied to solve many real life problems. In this paper, we propose a new cuckoo search algorithm by combining the cuckoo search algorithm with the Nelder-Mead method in order to solve the integer and minimax optimization…
Bilal Khurshid, Shahid Maqsood, Yahya Khurshid, Khawar Naeem + 1 more
This study investigates the no-wait flow shop scheduling problem and proposes a hybrid (HES-IG) algorithm that utilizes makespan as the objective function. To address the complexity of this NP-hard problem, the HES-IG algorithm combines evolution strategies (ES) and iterated greedy (IG) algorithm, as hybridizing…
Samuel Genheden, Esben Bjerrum
We introduce a framework for benchmarking multi-step retrosynthesis methods, i.e. route predictions, called PaRoutes. The framework consists of two sets of 10,000 synthetic routes extracted from the patent literature, a list of stock compounds, and a curated set of reactions on which one-step retrosynthesis models can…
Yidi Hao, Baodong Qin, Yitian Sun, Jose Manuel Molina López
Due to the rapid development of machine-learning technology, companies can build complex models to provide prediction or classification services for customers without resources. A large number of related solutions exist to protect the privacy of models and user data. However, these efforts require costly communication…
Benjamin Ries, Irfan Alibay, David W H Swenson, Hannah M Baumann + 3 more
Relative binding free energy (RBFE) calculations have emerged as a powerful tool supporting ligand optimization in drug discovery. Despite many successes, the use of RBFEs can often be limited by automation problems, in particular the setup of such calculations. Atom mapping algorithms are an essential component in…
Jonas Verhellen
Computer-assisted design of small molecules has experienced a resurgence in academic and indus- trial interest due to the widespread use of data-driven techniques such as deep generative models. While the ability to generate molecules that fulfill required chemical properties is encouraging, the use of deep learning…
Jan H. Jensen
This paper presents a comparison of a graph-based genetic algorithm (GB-GA) and machine learning (ML) results for the optimisation of logP values with a constraint for synthetic accessibility and shows that GA is as good or better than the ML approaches for this particular property. The molecules found by GB-GA bear…
Morihiro Hayashida, Tatsuya Akutsu
Background Comparison of various kinds of biological data is one of the main problems in bioinformatics and systems biology. Data compression methods have been applied to comparison of large sequence data and protein structure data. Since it is still difficult to compare global structures of large biological networks…
Lionel Zoubritzky, François-Xavier Coudert
We present here an open-source Julia library for the topological identification of crystalline materials, with algorithmic and computational improvements over the previously available software in the field, resulting in a speed increase of one order of magnitude. This new algorithm and implementation can therefore be…
Zhenghao Wu, Tianhang Zhou
In the realm of multiscale molecular simulations, structure-based coarse graining is a prominent approach for creating efficient coarse-grained (CG) representations of soft matter systems such as polymers. This involves optimizing CG interactions by matching static correlation functions of corresponding degrees of…