DataSheet1_Benefits and Challenges of Pre-clustered Network-Based Pathway Analysis.CSV by Miguel Castresana-Aguirre (12521683)

“…<p>Functional analysis of gene sets derived from experiments is typically done by pathway annotation. …”

Modeling Molecularly Imprinted Nanoparticles with LNKD: A Resource Efficient Algorithm for Polymer Cross-Linking by Emma Stevens (22257358)

“…Here, we propose LNKD (Linking Nodes in KD-trees), a resource-efficient algorithm for predicting pairs of reactive atoms in pre-cross-linked 3D structures of monomers that applies not only to the modeling of MIPs, but also chemical cross-linking in other materials. …”

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.…”

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

“…</li></ul><h3>PEAK FITTING </h3><ul><li>Automated background subtraction using asymmetric least squares fitting</li><li>A new suggested background feature that lets you preview the background that you like best</li><li>Interactive background fitting lets you further tune the background to perfection</li><li>Four choice of peaks: Gaussian, Lorentzian, Pseudo-Voigt, and the new Asymmetric Voigt functions</li><li>Overlapping view of how well the peaks fit with quality metrics</li><li>No need to define regions, the algorithm is smart enough to what a peak looks like.…”

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

Membership function of output for tank 1. by Tamiru Demelash Kassie (20678515)

Membership function of output for tank 2. by Tamiru Demelash Kassie (20678515)

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)

Characterization of the TD² dataset. by Benjamin Gallois (10131683)

Optimization of tracking parameters based on <i>P</i>_<i>swap</i>. by Benjamin Gallois (10131683)

Effect of confinment on <i>p</i>_<i>inc</i>. by Benjamin Gallois (10131683)

Automatic tracking parameters. by Benjamin Gallois (10131683)

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. …”

Application of the algorithm to unseen data. Presynaptic neurons labelled by rabies viral injection into layer 2/3 primary visual cortex in Penk-Cre mice. by Adam L. Tyson (10892822)