Listed python codes of our algorithm with explanations (Python 3.9 recommended). حسب Takayuki Niizato (162226)

Python-based Monte Carlo Simulation Tool حسب Yangfan Jiang (9372782)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results حسب Se-Hee Jo (20554623)

"…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …"

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب Morgan Najera (21540776)

"…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…"

Comparison of algorithms in two cases. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

Flow of the NSGA-II algorithm. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data حسب Anthony S. Barente (14035175)

الموضوعات:

Cellular frustration algorithms for anomaly detection applications حسب Bruno Faria (6928079)

"…Our results demonstrate that more efficient implementations of cellular frustration algorithms are possible and also that cellular frustration algorithms can be advantageous for semi-supervised anomaly detection applications given their robustness and accuracy.…"

An expectation-maximization algorithm for finding noninvadable stationary states. حسب Robert Marsland (8616483)

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements حسب Pascal Wang (10130612)

"…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …"

EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit حسب Gonzalo Colmenarejo (650249)

"…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …"

The optimal solution set of NYN by using different algorithms. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

The optimal solution set of HN by using different algorithms. حسب Yi Tao (178829)

الموضوعات: "…evolutionary genetic algorithm…"

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz حسب Faizan Ali (21689861)

الموضوعات:

Implementation algorithm. حسب Michael A. Colman (7163735)

Python scripts used to model CPU errors by Poisson distribution density mass function and to draw graph of Poisson events (needs Matplot, SciPy, PysimpleGUI and NumPy) حسب Santhosh Kumar Rajamani (13023678)

Analysis pipelines & features. A comparison of features and functions for cellular image analysis software packages. حسب Teresa W. Lo (21440277)

Verification of the in-line PS function. حسب Raul Castañeda (13932971)

Available functions in the utility package. حسب Raul Castañeda (13932971)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data حسب Jean-Christophe Lachance (6619307)

"…GEM-guided predictions of growth phenotypes rely on the accurate definition of a biomass objective function (BOF) that is designed to include key cellular biomass components such as the major macromolecules (DNA, RNA, proteins), lipids, coenzymes, inorganic ions and species-specific components. …"