Sökning: "Novel Drug"

Visar resultat 1 - 5 av 90 uppsatser innehållade orden Novel Drug.

  1. 1. Machine learning for molecular property prediction and drug safety

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :Kinga Jenei; [2023-10-23]
    Nyckelord :Molecular property prediction; Acid dissociation constant; pKa; Machine learning; Graph Neural Networks; Molecular descriptors; Drug Discovery;

    Sammanfattning : Utilizing machine learning methods for the prediction of acid dissociation (pKa ) values of compounds holds great significance, as pKa is an important parameter, optimized frequently in drug discovery. Accurate prediction of pKa values could potentially provide valuable insights on other molecular properties and thereby support compound design. LÄS MER

  3. 2. Establishing novel approaches for assessing safety of genome-editing-based therapeutics

    Master-uppsats, Uppsala universitet/Institutionen för biologisk grundutbildning

    Författare :Noorul Shaheen Sheikh Farid; [2023]
    Nyckelord :;

    Sammanfattning : Genome editing based medicines are a new therapeutic modality being developed. They show great promise for a spectrum of genetic diseases lacking conventional treatment strategies. A major obstacle that prevents such therapies to reach the clinic is their safety. LÄS MER

  4. 3. A novel approach for functionalising and separating Tröger's Base Analogues

    Master-uppsats, Lunds universitet/Centrum för analys och syntes

    Författare :Emil Jakobsson; [2023]
    Nyckelord :Tröger s Base; Synthesis; Chromatography; Supramolecular chemistry; Diastereomers; Organic chemistry; Chemistry;

    Sammanfattning : Tröger’s Base (TB) is a bicyclic compound containing a methanodiazocine group between two aromatic rings. The methylene bridge forces the molecule to have a bent formation; thus, the aromatic rings are close to 90 degrees relative to each other, resulting in a rigid concave aromatic cavity. LÄS MER

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

    Master-uppsats, Uppsala universitet/Institutionen för farmaceutisk biovetenskap

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

    Sammanfattning : 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. LÄS MER

  7. 5. Predicting morphological effect of compounds on COVID-19 infected cells

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Läkemedelsdesign och läkemedelsutveckling

    Författare :Viktor Öhrner; [2023]
    Nyckelord :QSAR; ML; AI; bioinformatics; COVID-19; morphological profiles;

    Sammanfattning : The cost of developing new drugs is high and the aim of computer-assisted drug discovery is to reduce that development cost, either through virtual screening or generating novel compounds. System biology is one approach to drug discovery where the response of a biological system is the subject of study, instead of drug target interaction. LÄS MER