The algorithm is designed to identify patterns in the treatment dataset. by Belén Otero-Carrasco (21262360)

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

Subjects:

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

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

3D modeling qualities of the AS single-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

3D modeling qualities of the AM multiple-template models built by including DOPE in the objective function of MODELLER. by Giacomo Janson (8138517)

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

“…<b>(B)</b> The priority of the top 10 genes was evaluated through MNC, which identifies clusters of protein nodes that are more functionally connected to each other and selects the central proteins within the cluster. …”

Supplementary Tables 1 - 7 from A Meta-analysis of Lung Cancer Gene Expression Identifies <i>PTK7</i> as a Survival Gene in Lung Adenocarcinoma by Ron Chen (14910750)

Subjects:

Table3_Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm.XLSX by Fei Yuan (24924)

“…From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. …”

Table4_Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm.XLSX by Fei Yuan (24924)

“…From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. …”

Table2_Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm.XLSX by Fei Yuan (24924)

“…From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. …”

Table1_Identification of Novel Lung Cancer Driver Genes Connecting Different Omics Levels With a Heat Diffusion Algorithm.XLSX by Fei Yuan (24924)

“…From the driver genes at each level, the Laplacian heat diffusion algorithm was executed on a protein–protein interaction network for discovering latent driver genes at this level. …”

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

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.…”

Unraveling the gender-specific molecular landscape of lung squamous cell carcinoma progression by Ayushi Dwivedi (20658343)

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…”

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

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)