An optimal solution for the HFS instance. by Xiang Tian (4369285)

<i>De Novo</i> Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization by Alberga Domenico (9356272)

“…In the present study, we conceived a novel pair-based multiobjective approach implemented in an adapted SMILES generative algorithm based on recurrent neural networks for the automated <i>de novo</i> design of new molecules whose overall features are optimized by finding the best trade-offs among relevant physicochemical properties (MW, logP, HBA, HBD) and additional similarity-based constraints biasing specific biological targets. …”

Train test validation libraries. by Muhammad Usman Tariq (11022141)

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Flat optimization method. by Nisha Ann Viswan (20371285)

Hierarchical Optimization on large models. by Nisha Ann Viswan (20371285)

Schematic diagram of the Dropout optimization. by Peng Yang (296696)

Dropout optimization model framework structure diagram. by Peng Yang (296696)

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

“…In the library, ligands are sorted based on direct ligand-to-metal atomic connections and on denticity. …”

Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

“…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”

Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start by Yifan Wang (380120)

“…In response to these challenges, this work presents a method to fine-tune a genetic algorithm for CAMD. The proposed method builds on the COSMO-CAMD framework that utilizes a genetic algorithm for solving optimization-based molecular design problems and COSMO-RS for predicting physical properties of molecules. …”

Performance of the greedy approximation algorithm. by Virgile Andreani (17087764)

Presentation_1_Calibrating Seed-Based Heuristics to Map Short Reads With Sesame.zip by Guillaume J. Filion (9027317)

SSA4LSMOP by Zongbin Qiao (19814199)

“…<p dir="ltr">SSA4LSMOP is a multi-objective optimization algorithm library, which aims to provide researchers and developers with efficient and easy-to-use multi-objective optimization solutions. …”

Closed search (±5ppm) comparison against Crux and MSFragger using real-world data from PRIDE repository PXD000612 (top), PXD009861 (middle), and PXD001468 (bottom). by Muhammad Usman Tariq (11022141)

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Training parameters for SpeCollate. by Muhammad Usman Tariq (11022141)

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Peptides. by Muhammad Usman Tariq (11022141)

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Fig 9 - by Muhammad Usman Tariq (11022141)

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UMAP. by Muhammad Usman Tariq (11022141)

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Process of generating MS/MS spectra from a protein mixture using mass-spectrometry analysis. by Muhammad Usman Tariq (11022141)

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Modifications and the character values used in the training data. by Muhammad Usman Tariq (11022141)

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