EAT-Rice: A predictive model for flanking gene expression of T-DNA insertion activation-tagged rice mutants by machine learning approaches by Chi-Chou Liao (6680852)

“…<div><p>T-DNA activation-tagging technology is widely used to study rice gene functions. When T-DNA inserts into genome, the flanking gene expression may be altered using CaMV 35S enhancer, but the affected genes still need to be validated by biological experiment. …”

Python code, input data, and outputs of Fourier analysis and Dynamic Time Warping from McGlasson et al. by Riley McGlasson (13876874)

“…</p> <h4><strong>Python Function Files:</strong></h4> <p>radarfuncs.py: Holds three functions used for FFT and DTW analysis.…”

Fitness function over the 50 runs. by Mohammed Alqahtani (2049139)

“…Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. …”

Fitness function over the 50 runs. by Mohammed Alqahtani (2049139)

“…Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. …”

Fitness function over the 50 runs. by Mohammed Alqahtani (2049139)

“…Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. …”

Table_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Table_2_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Image_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Presentation_1_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

Table_3_NeuroRA: A Python Toolbox of Representational Analysis From Multi-Modal Neural Data.pdf by Zitong Lu (9913770)

ClaritySpectra: Raman spectra analysis tool by Aaron Celestian (9395696)

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

Open Binding Pose Metadynamics: An Effective Approach for the Ranking of Protein–Ligand Binding Poses by Dominykas Lukauskis (14143149)

“…OpenBPMD is powered by the OpenMM simulation engine and uses a revised scoring function. The algorithm was validated by testing it on a wide range of targets and showing that it matches or exceeds the performance of the original BPMD. …”

DataSheet1_Multi_Scale_Tools: A Python Library to Exploit Multi-Scale Whole Slide Images.PDF by Niccolò Marini (11247936)

“…<p>Algorithms proposed in computational pathology can allow to automatically analyze digitized tissue samples of histopathological images to help diagnosing diseases. …”

BOFdat Step 3: Identifying species-specific metabolic end goals. by Jean-Christophe Lachance (6619307)

Contrast enhancement of digital images using dragonfly algorithm by Soumyajit Saha (19726163)

“…Comparisons with state-of-art methods ensure the superiority of the proposed algorithm. The Python implementation of the proposed approach is available in this <a href="https://github.com/somnath796/DA_contrast_enhancement" target="_blank">Github repository</a>.…”

Complementary cumulative distribution functions of in degree distribution and fitted power law, lognormal and truncated power law distributions. by Olga Valba (10531121)