The 10 features captured by persistence fingerprint. by Yuxi Long (11024307)

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^aTwo HIV-1 protease mutants bound to inhibitor darunavir (G48V: PDB ID 3cyw [81] & L90M: PDB ID 2f81 [82]). by Yuxi Long (11024307)

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Scatter plots of PATH⁺ and our implementation of TNet-BP’s predictions on a held-out, test subset of PDBBind v2020 refined set for one run (90:10 train:test split ratio,... by Yuxi Long (11024307)

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Two protein-ligand complexes shown with their persistence fingerprint. by Yuxi Long (11024307)

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PATH⁺ correctly predicted a weaker binding affinity for HIV-1 protease with the drug-resistant G48V mutation (right, experimental kcal/mol, PDB ID: 3cyw [81]) bound to d... by Yuxi Long (11024307)

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PATH (with persistence fingerprint) runs significantly faster than TNet-BP, a representative binding affinity prediction algorithm that uses persistent homology, on larger protein-... by Yuxi Long (11024307)

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Visualization by PaCMAP [52] shows that persistence fingerprint clusters protein-ligand complexes with similar binding affinity reasonably well, even beyond the training dataset (P... by Yuxi Long (11024307)

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Performance of TNet-BP and PATH⁺ on the PDBBind v2020 refined set shows that PATH⁺ achieves similar performance with TNet-BP while having three orders fewer f... by Yuxi Long (11024307)

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Construction of internuclear persistence contours (IPCs). by Yuxi Long (11024307)

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Comparison of PATH⁺ with TNet-BP [43]. by Yuxi Long (11024307)

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This figure shows a non-exhaustive representation of the main models reported in our discussion, for illustrative purpose only. by Giuseppe Agapito (104634)

Classification Report for the proposed model. by Khondokar Oliullah (21553289)

Python code for a rule-based NLP model for mapping circular economy indicators to SDGs by Zahir Barahmand (18008947)

“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”

Comparison of different algorithms for worm tracking. All methods were executed on identical hardware (as detailed in Section 2.2) and evaluated on the same dataset using an image... by Xiaoke Liu (11388323)

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

MGVB: a New Proteomics Toolset for Fast and Efficient Data Analysis by Metodi V. Metodiev (6089009)

Subjects: “…probabilistic scoring function…”

Sponge construct of SKINNY-Hash. by Sonal Arvind Barge (20454967)

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