<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by 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.…”

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

“…<i>(c)</i> Pseudocode for self-consistently computing <b>R</b>* and , which is identical to standard expectation-maximization algorithms employed for problems with latent variables in machine learning.…”

Procedure of the DCT-based EIT algorithm. by Rongqing Chen (249906)

Subjects:

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

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

Core genes were selected through PPI analysis based on three algorithms. by Dong-Hee Han (140305)

“…<p>Among 46 DEGs whose expression significantly changed in A549 and BEAS-2B cell lines, the core genes were selected using three algorithms: MCC, MNC, and DEGREE. <b>(A)</b> The top 10 genes were prioritized using MCC analysis, which identifies the largest clique within the PPI network and selects the central proteins within the clique. …”

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by 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). …”

Data_Sheet_1_Unsupervised clustering algorithms improve the reproducibility of dynamic contrast-enhanced magnetic resonance imaging pulmonary perfusion quantification in muco-obstr... by Marilisa Konietzke (13999845)

“…Quantifying the extent of abnormalities using unsupervised clustering algorithms in residue function maps leads to intrinsic normalization and could reduce variability.…”

Multimodal reference functions. by Ruiyu Zhan (21602031)

“…-led initiative conducting in-depth molecular research to elucidate the causative mechanisms of cancer — this study focuses on three specific cancer types within the dataset: lung, breast, and esophageal cancers. …”

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

Subjects: “…evolutionary genetic algorithm…”

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

Subjects: “…evolutionary genetic algorithm…”

gmxapi usage examples. by M. Eric Irrgang (4487278)

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

Subjects:

The convergence curves of the test functions. by Ruiyu Zhan (21602031)

“…-led initiative conducting in-depth molecular research to elucidate the causative mechanisms of cancer — this study focuses on three specific cancer types within the dataset: lung, breast, and esophageal cancers. …”

Single-peaked reference functions. by Ruiyu Zhan (21602031)

“…-led initiative conducting in-depth molecular research to elucidate the causative mechanisms of cancer — this study focuses on three specific cancer types within the dataset: lung, breast, and esophageal cancers. …”

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements by 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. …”

Function graph and algorithm iterative graph. by WanRu Zhao (18980374)

Subjects:

Fitting results of the different optimization algorithms applied. by Sonja Langthaler (6069149)

Test results of multimodal benchmark functions. by Ruiyu Zhan (21602031)

“…-led initiative conducting in-depth molecular research to elucidate the causative mechanisms of cancer — this study focuses on three specific cancer types within the dataset: lung, breast, and esophageal cancers. …”