Statistical results of fitness function acquired by four algorithms in 10 runs (in p.u.). by Junfang Hao (9656905)

Comparison of compression rates of DDQR and Geco3 using simulated data around the region where the performance of DDQR exceeds that of GeCo3. by Yujun Wang (1947196)

Categorization of the iModulons by their biological functions. by Hojun Lee (655617)

Screening of the potential small-molecular compounds for the treatment of NAFLD and AIS by cMAP analysis. by Junjie Su (368807)

Parameters of NSGA-II algorithm. by Shangyang Jin (21772466)

“…Thus, a combination algorithm optimization strategy for metamaterials in terms of multiple structural parameters is proposed in this paper based on a co-simulation approach. …”

Network-aware functional overrepresentation results. by Agatha Treveil (10090931)

HintCO – Hint-Based Configuration of Co-Simulations by Cláudio Gomes (8972050)

Preservation analysis of co-expressed modules of control networks were tested in the stress condition based on the median rank (A) and Zsummary (B) algorithms. by Bahman Panahi (7323578)

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

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SARS-CoV-2 secondary structure predictions via KnotAli. by Luke Trinity (6792770)

Dominant SARS-CoV-2 pseudoknot motif predictions via Shapify. by Luke Trinity (6792770)

Python implementation from Symplectic decomposition from submatrix determinants by Jason L. Pereira (11598632)

“…Python implementation of the algorithm and demonstration of how to use the functions.…”

GraSPy: an Open Source Python Package for Statistical Connectomics by Benjamin Pedigo (6580352)

“…We developed GraSPy, an open-source Python toolkit for statistical inference on graphs. …”

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

Development of the CO₂ Adsorption Model on Porous Adsorbent Materials Using Machine Learning Algorithms by Hossein Mashhadimoslem (11456548)

“…In this research study, we created a data set and collected data points from porous adsorbents (2789) from 21 published papers, including carbon-based, porous polymers, metal–organic frameworks (MOFs), and zeolites, to understand their characteristics for CO₂ adsorption. Different machine learning (ML) algorithms, such as NN, MLP-GWO, XGBoost, RF, DT, and SVM, have been applied to display the CO₂ adsorption performance as a function of characteristics and adsorption isotherm parameters. …”

Disentangling the Contribution of Each Descriptive Characteristic of Every Single Mutation to Its Functional Effects by C. K. Sruthi (5391104)

Disentangling the Contribution of Each Descriptive Characteristic of Every Single Mutation to Its Functional Effects by C. K. Sruthi (5391104)

Analysis of weighted co-expression networks in Parkinson’s disease. by Lixia Chen (614030)

General flow of processing collected data. by Reinhard Chun Wang Chau (12733662)

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System specification of high-performance computer. by Reinhard Chun Wang Chau (12733662)

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