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

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

Functions of membership for <i>age</i> variable. by José Carlos R. Alcantud (6858155)

Functions of membership for <i>BMI</i> variable. by José Carlos R. Alcantud (6858155)

Functions of membership for <i>FEV1%</i> variable. by José Carlos R. Alcantud (6858155)

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<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. …”

The gene set related to the “Cytotoxicity” and “Progenitor exhaustion” function of T cells. by Yanfeng Xue (465345)

Subjects: “…Cell Biology…”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

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:

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. …”

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

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

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

Subjects:

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.…”

Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

Subjects:

Comparison of PyNoetic’s functionality for BCI design with other existing state-of-the-art frameworks. by Gursimran Singh (575288)

Subjects:

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)

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

“…In this study, a computational investigation was conducted on lung cancer driver genes. Four omics levels, namely, epigenomics, genomics, transcriptomics, and post-transcriptomics, were involved. …”