Presentation 1_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated... by Rachid Tahzima (22106816)

“…<p>The functions of RNA-dependent RNA polymerases (RdRps) in RNA viruses are demonstrably modulated by native substrates of dynamic and interconvertible conformational ensembles. …”

Data Sheet 2_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated f... by Rachid Tahzima (22106816)

“…<p>The functions of RNA-dependent RNA polymerases (RdRps) in RNA viruses are demonstrably modulated by native substrates of dynamic and interconvertible conformational ensembles. …”

Data Sheet 1_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated f... by Rachid Tahzima (22106816)

“…<p>The functions of RNA-dependent RNA polymerases (RdRps) in RNA viruses are demonstrably modulated by native substrates of dynamic and interconvertible conformational ensembles. …”

Data Sheet 3_Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated f... by Rachid Tahzima (22106816)

“…<p>The functions of RNA-dependent RNA polymerases (RdRps) in RNA viruses are demonstrably modulated by native substrates of dynamic and interconvertible conformational ensembles. …”

The information of datasets used in this study. by Kaiyi Zhou (2553352)

“…Both machine learning algorithms identified Ribosomal Protein L22-like 1 (RPL22L1) and Lymphocyte Antigen 96 (LY96) as potential diagnostic markers for PsA and RA. …”

The workflow of the present study. by Kaiyi Zhou (2553352)

“…Both machine learning algorithms identified Ribosomal Protein L22-like 1 (RPL22L1) and Lymphocyte Antigen 96 (LY96) as potential diagnostic markers for PsA and RA. …”

Data for "A multi-objective platform for autonomous property targeting and optimization of colloidal lead halide perovskite quantum dots" by Neal Munyebvu (19690954)

Overview of the research process. by Pedro Fong (2378413)

“…We used the automated docking suite GOLD v5.5 with the genetic algorithm to simulate molecular docking and predict the protein-ligand binding modes, and the ChemPLP empirical scoring function to estimate the binding affinities of 2,115 FDA-approved drugs to the human Ca_v3.1 channel. …”

The overall framework of this study. by Tianbao Feng (21722233)

“…PANoptosis score in SCI samples was significantly higher than in HC samples. Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. …”

PANoptosis related genes. by Tianbao Feng (21722233)

“…PANoptosis score in SCI samples was significantly higher than in HC samples. Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. …”

Primer sequences of <i>Bm</i>x and β-actin. by Tianbao Feng (21722233)

“…PANoptosis score in SCI samples was significantly higher than in HC samples. Additionally, a protein-protein interaction (PPI) network was established to identify hub genes, and 8 machine learning algorithms were used to narrowed down hub genes. …”

Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model by Marina Diachenko (19739092)

“…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”

Dataset for ACPs. by Bangyi Zhang (22232454)

“…The framework leverages the ESMC protein language model to extract comprehensive sequence features and employs a novel adaptive algorithm, ANBS, to mitigate class imbalance at the decision boundary. …”

Framework of HyperACP. by Bangyi Zhang (22232454)

“…The framework leverages the ESMC protein language model to extract comprehensive sequence features and employs a novel adaptive algorithm, ANBS, to mitigate class imbalance at the decision boundary. …”

Models of the ESM series and their parameters. by Bangyi Zhang (22232454)

“…The framework leverages the ESMC protein language model to extract comprehensive sequence features and employs a novel adaptive algorithm, ANBS, to mitigate class imbalance at the decision boundary. …”

Performance of ensemble models on ACP135. by Bangyi Zhang (22232454)

“…The framework leverages the ESMC protein language model to extract comprehensive sequence features and employs a novel adaptive algorithm, ANBS, to mitigate class imbalance at the decision boundary. …”

Performance of ensemble models on ACP 99. by Bangyi Zhang (22232454)

“…The framework leverages the ESMC protein language model to extract comprehensive sequence features and employs a novel adaptive algorithm, ANBS, to mitigate class imbalance at the decision boundary. …”

Pocket clustering statistics. by Hanne Zillmer (21782030)

“…Our study revealed a sub-linear scaling law of the number of unique binding sites relative to the number of unique protein structures per species. Thus, as proteomes increased in size during evolution and therefore potentially diversified, the number of distinct binding sites, reflecting potentially diversifying functions, grew less than proportionally. …”

Fig 4 - by Michael S. Bradshaw (11772750)

RNA microarray analysis in knockdown of STAT1 in primary human hepatocyte HBV infection system and HBV-transfected HepG2 cells. by Takuto Nosaka (4484245)