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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search)
python function » protein function (Expand Search)
algorithm both » algorithm blood (Expand Search), algorithm b (Expand Search), algorithm etc (Expand Search)
both function » body function (Expand Search), growth function (Expand Search), beach function (Expand Search)
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EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit
Published 2025“…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”
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Results of the application of different clustering algorithms to average functional connectivity from healthy subjects.
Published 2023“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”
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Comparison of scores obtained by our interpenetration and scoring algorithm (ISA) and ROSETTA for a subset of structures.
Published 2023“…However, our algorithm was 1000 times faster than pyROSETTA (both algorithms have been parallelized on a per-structure basis using the Python package joblib [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1010531#pcbi.1010531.ref069" target="_blank">69</a>]).…”
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List of Abbreviations
Published 2025“…For advanced users, it facilitates the seamless integration of custom functionalities and novel algorithms with minimal coding, ensuring adaptability at each design stage. …”
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The results of ICA performed using PyNoetic.
Published 2025“…For advanced users, it facilitates the seamless integration of custom functionalities and novel algorithms with minimal coding, ensuring adaptability at each design stage. …”
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DataSheet1_Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.PDF
Published 2021“…The multi-scale CNNs outperform the single-magnification CNN for both classification and segmentation tasks. The code is developed in Python and it will be made publicly available upon publication. …”
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Image_1_KairoSight: Open-Source Software for the Analysis of Cardiac Optical Data Collected From Multiple Species.TIF
Published 2021“…Despite the refinement of software tools and algorithms, significant programming expertise is often required to analyze large optical data sets, and data analysis can be laborious and time-consuming. …”
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S1 Graphical abstract -
Published 2025“…<div><p>Engineered heart tissues (EHTs) have shown great potential in recapitulating tissue organization, functions, and cell-cell interactions of the human heart <i>in vitro</i>. …”
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Brain-in-the-Loop Learning for Intelligent Vehicle Decision-Making
Published 2025“…In this paper, we utilize functional near-infrared spectroscopy (fNIRS) signals as real-time human risk-perception feedback to establish a brain-in-the-loop (BiTL) trained artificial intelligence algorithm for decision-making. …”
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Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat.
Published 2025“…The analysis was conducted in a Jupyter Notebook environment, using Python and libraries such as Scikit-learn and Pandas. …”
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Datasheet1_A Workflow for Rapid Unbiased Quantification of Fibrillar Feature Alignment in Biological Images.zip
Published 2021“…<p>Measuring the organization of the cellular cytoskeleton and the surrounding extracellular matrix (ECM) is currently of wide interest as changes in both local and global alignment can highlight alterations in cellular functions and material properties of the extracellular environment. …”
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Seamless integration of legacy robotic systems into a self-driving laboratory via NIMO: a case study on liquid handler automation
Published 2025“…We developed NIMO (formerly NIMS-OS, NIMS Orchestration System), an OS explicitly designed to integrate multiple artificial intelligence (AI) algorithms with diverse exploratory objectives. NIMO provides a framework for integrating AI into robotic experimental systems that are controlled by other OS platforms based on both Python and non-Python languages. …”
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Code
Published 2025“…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”