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Showing result 1 - 5 of 30 essays matching the above criteria.

1. 1. Combining Cell Painting, Gene Expression and Structure-Activity Data for Mechanism of Action Prediction

   University essay from Uppsala universitet/Nationellt resurscentrum för biologi och bioteknik

   Author : Erik Everett Palm; [2023]
   Keywords : bioinformatics; deep learning; machine learning; joint model; tabular data; image data;

   Abstract : The rapid progress in high-throughput omics methods and high-resolution morphological profiling, coupled with the significant advances in machine learning (ML) and deep learning (DL), has opened new avenues for tackling the notoriously difficult problem of predicting the Mechanism of Action (MoA) for a drug of clinical interest. Understanding a drug's MoA can enrich our knowledge of its biological activity, shed light on potential side effects, and serve as a predictor of clinical success. READ MORE

3. 2. Intersecting Graph Representation Learning and Cell Profiling : A Novel Approach to Analyzing Complex Biomedical Data

   University essay from Uppsala universitet/Institutionen för farmaceutisk biovetenskap

   Author : Nima Chamyani; [2023]
   Keywords : Graph representation learning; Cell profiling; Biological systems; Network medicine; Graphs; Machine learning techniques; Graph neural networks GNNs ; Protein-Compound-Pathway interactions; Biomarkers; Drug discovery;

   Abstract : In recent biomedical research, graph representation learning and cell profiling techniques have emerged as transformative tools for analyzing high-dimensional biological data. The integration of these methods, as investigated in this study, has facilitated an enhanced understanding of complex biological systems, consequently improving drug discovery. READ MORE

4. 3. Learning the shapes of protein pockets

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Alejandro Corrochano; Yossra Gharbi; [2022-10-14]
   Keywords : Protein; cavity; ligand-binding; 3D-equivariance; shape; latent space; e3nn; Fpocket; sc-PDB;

   Abstract : The comparison of protein pockets plays an important role in drug discovery. Through the identification of binding sites with similar structures, we can assist in finding hits and characterizing the function of proteins. Traditionally, the geometry of cavities has been described with scalar features, which are not fully representative of the shape. READ MORE

5. 4. Benchmarking Machine Learning Methods for Peptide Activity Predictions

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Boel Knutson; Lida Meskini Moudi; [2022-10-14]
   Keywords : Drug discovery; peptide; classification; molecular representation; Z-scales; pseudo amino acid composition; one-hot representation; random forests; support vector machines;

   Abstract : One of the main challenges in the drug discovery process is to find a suitable compound for further analysis. The compound must affect the target relevant for the specific disease, while at the same time have desired properties to make it a safe and efficient drug candidate. READ MORE

6. 5. Predicting misuse of subscription tranquilizers : A comparasion of regularized logistic regression, Adaptive Bossting and support vector machines

   University essay from Uppsala universitet/Statistiska institutionen

   Author : Ida Norén; [2022]
   Keywords : Adaptive Boosting; Benzodiazepines; classification; lasso regularization; logistic regression; support vector machines;

   Abstract : Tranquilizer misuse is a behavior associated with substance use disorder. As of now there is only one published article that includes a predictive model on misuse of subscription tranquilizers. READ MORE