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). …”

<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.…”

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)

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

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

Algorithm framework. by Zongjin Li (38031)

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

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Performance of ENQUIRE’s gene normalization algorithm. by Luca Musella (19986312)

Identification and functional analysis of hub genes. by Wei Ya Lan (22403712)

“…(E) GO enrichment analysis of shared candidate genes, showing the top three terms for biological process (BP), cellular component (CC), and molecular function (MF).…”

Reward function related parameters. by Honglei Pang (22693724)

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Functional analysis of anoikis-related genes. by Yufeng He (5673119)

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<b>Gene Catalog and Associated Functional Data</b> for BioProject PRJNA1311452 by Satheeswaran Thangaraj (22187269)

WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Cell-type marker genes and functional enrichment analysis. by Hailin Li (453832)

Functional enrichment analyses of Co-genes. by Qingcong Zheng (11169094)

Top-ranked hub genes identified by 5 cytoHubba algorithms. by Jun Li (6494)

Overview of the Cell2Spatial algorithm. by Huamei Li (8815955)

Subjects: “…minimizing assignment algorithm…”

The results of LASSO regression algorithm. by Xue Fu (549661)

Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

Integration of three machine learning algorithms to characterize lipid metabolism-associated hub genes in sepsis and atrial fibrillation. by Changze Ou (22806374)

Identification of hub genes with six different algorithms using the CytoHubba plugin in Cytoscape. by Ramin Yousefpour Shahrivar (20903161)