ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design by Shu-Sen Chen (1777108)

Subjects:

<i>hi</i>PRS algorithm process flow. by Michela C. Massi (14599915)

“…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i>_<i>δ</i>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i>_<i>δ</i>, <i>hi</i>PRS constructs <i>I</i>_<i>K</i>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …”

Optimal 8-mer and 9-mer SARS-CoV-2 epitope identification. by Mariah Hassert (5746874)

“…As controls for strong Kb and Db binders respectively, Ova peptide and ZIKV E294 were input into the same algorithm. Optimal peptide epitopes are highlighted based on functional T cell data in combination with RMA-S stabilization assay data.…”

Cheminformatics-Guided Cell-Free Exploration of Peptide Natural Products by Jarrett M. Pelton (18143785)

“…To assess the peptide NP space that is directly accessible to current cell-free technologies, we developed a peptide parsing algorithm that breaks down peptide NPs into building blocks based on ribosomal translation logic. …”

ECE6327_SmartGrid by Xingpeng Li (11825663)

Phylogenetic history of genes 5 and 11 in three related genomes. by Geleta Dugassa Barka (9099456)

Symmetry test result. by Jiyong Moon (16819302)

Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential by Fengyang Han (14613218)

Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential by Fengyang Han (14613218)

primary ATRT single cell RNA-seq by Mamy ANDRIANTERANAGNA (12913196)

“…</p> <p>scRNA-seq data integration was performed using the CCA-based implemented in Seurat version 3. The clustering was conducted using the graph-based modularity optimization Louvain algorithm implemented in Seurat v3. …”

DataSheet1_Quantum-assisted fragment-based automated structure generator (QFASG) for small molecule design: an in vitro study.docx by Sergei Evteev (18294157)

Data_Sheet_1_Multiclass Classification Based on Combined Motor Imageries.pdf by Cecilia Lindig-León (7889777)

“…And we propose two new multilabel uses of the Common Spatial Pattern (CSP) algorithm to optimize the signal-to-noise ratio, namely MC2CMI and MC2SMI approaches. …”

primary mouse RT single cell RNA-seq by Mamy ANDRIANTERANAGNA (12913196)

“…The clustering was conducted using the graph-based modularity optimization Louvain algorithm implemented in Seurat v3. …”

DataSheet1_Large-Scale Heterogeneous Computing for 3D Deterministic Particle Transport on Tianhe-2A Supercomputer.zip by Biao Li (36684)

Table_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx by Qian Wang (32718)

Image_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg by Qian Wang (32718)

Image_2_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg by Qian Wang (32718)

DataSheet_1_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.docx by Qian Wang (32718)

Image_3_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.jpeg by Qian Wang (32718)

Table_4_G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.xlsx by Qian Wang (32718)