Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 40 for “"Scoring Function"”.
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Revisiting and re-computing the X-score scoring function
Scoring functions seek to compute in different ways protein-ligand binding energies by summing together the individual pairwise atomic interaction energies observed in crystal structures between the protein and the bound ligand. To date though, accurate prediction remains a big challenge since …
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A series of advanced scoring functions in ranking protein structures
Designing an efficient scoring function is one of the most challenging tasks in computational biology. A good potential functions or scoring functions can help rank protein structures models, guide the search and identify possible solutions. This is very important for protein structure prediction. …
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A Qualitative Method for Dynamic Transport Selection in Heterogeneous Wireless Environments
… prioritized soft constraint satisfaction (PSCS) scoring function to ascertain the transport that best meets the user's needs. The second phase, inter-device negotiation, facilitates two QoT-enabled devices in agreeing to a unified selection of the best transport. This phase uses a modified …
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Examination of Molecular Recognition in Protein-Ligand Interactions
… project was the development and validation of a scoring function, PHOENIX, derived using high-resolution structures and calorimetry measurements to predict binding affinities of protein-ligand interactions. Collectively, my thesis research aimed to better understand the underlying driving forces …
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Development of Machine Learning Models for Generation and Activity Prediction of the Protein Tyrosine Kinase Inhibitors
… Learning based approaches for generation and scoring of novel kinase inhibitor molecules. We utilized a binary Random Forest classification model to develop a Machine Learning based scoring function to evaluate the generated molecules on Kinase Inhibition Likelihood. By training the model on …
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Force Field Development With Gomc A Fast New Monte Carlo Molecular Simulation Code
… quantitative fitting process is outlined using a scoring function and heat maps. The presented n-6 force fields include force fields for noble gases and branched alkanes. These force fields are shown to be the most accurate LJ or n-6 force fields to date for these compounds, capable of reproducing …
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The Role of the Horn in Band Music
… Nixon, and Barnes, are considered for their scoring, function, technique, and virtuosity. These examples constitute a representative sample of horn parts depicting the evolution of the horn's role from rhythmic punctuation to featured melodic line. The horn's range and various techniques are …
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DEVELOPMENT OF VIRTUAL SCREENING METHODOLOGIES FOR IDENTIFYING RNA-BASED THERAPIES
… and designing RNA sequences with specific functional outcomes. The research introduces PANTHER (Protein-Affinity for Nucleic Target-binding, Hybridization, and Energy Regression), a novel machine learning-based scoring function that predicts protein-RNA binding affinities through a …
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Recomendr-entity recommendation based on ad-hoc dimensions
… It then rates the textual stream of data using a scoring function and returns the decision based on an aggregate opinion to the user. Evaluation of Recomendr using a data set in the laptop domain shows that it can effectively recommend the best laptop as per user-specified dimensions such as …
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Two Problems in Computational Genomics
… different evolutionary events, and define a scoring function for those graphs. The problem defined is proven to be NP-complete. Two heuristics are presented to solve the problem, one is a dynamic programming approach that is optimal for a class of sequences that we define in this work as …
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Casting Protein Structure Predictors as Energy-Based Models for Binder Design and Scoring
… we introduce pTMEnergy, a statistical energy function over structures that is derived from predicted inter-residue error distributions. We incorporate pTMEnergy into BindEnergyCraft (BECraft), a hallucination-based binder design pipeline that maintains the same optimization framework as …
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Advances in structure and small molecule docking predictions for crystallized G-Protein coupled receptors
… calculations. Two new terms were added to the scoring function, WScore to achieve this, based on a detailed molecular understanding of how the receptor works.
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Development of Computational to ols to Target Microrna
… the binding affinity of miRNA ligands, a new scoring function for molecular docking is devised. RNAs, as negatively charged molecules, tend to be more dependent on electrostatic interaction. To obtain a more accurate predictions, I have introduced the combination of Yukawa and Coulomb …
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Problem dependent metaheuristic performance in Bayesian network structure learning.
… and score algorithms. In these algorithms, a scoring function is introduced and a heuristic search algorithm is used to evaluate each network with respect to the training data. The optimal network is produced according to the best score evaluated. This thesis investigates a range of search and …
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AI-Driven Discovery and Multiscale Computational Frameworks for Carbon-Based Materials
… generative system. Here, an oracle-based scoring function provides feedback from machine learning predicted adsorption metric, dynamically steering the generative model toward desirable regions of the property space. This self-optimizing loop improves both discovery efficiency, physical …
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New Methodology for Measuring Semantic Functional Similarity Based on Bidirectional Integration
… and Statistical Mean (BSM) score to calculate functional similarity between gene products (GPs) that can help to extract biologically relevant and statistically robust information from large-scale biomedical, genomic and proteomic data sources. BSM score is defined by 16 different scoring …
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Structural determinants of cardiac light chain amyloidosis
… frequency overlap information as an additional scoring function in the multi-objective search for optimal assignment solutions.
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Partial compilation of constraint problems
… part of a subset of solutions that optimises a scoring function. Such a scoring function could be maximising the model count of the compilation after assigning the selective backbone, or the ratio between the model count and the compiled representation size. Large selective backbones allow for …
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Leveraging Multimodal Perspectives to Learn Common Sense for Vision and Language Tasks
… approaches, and propose a new goal-driven scoring function for deep VQA models under the Bayesian Neural Network framework. Once trained with a large initial training set, a deep VQA model is able to efficiently query informative question-image pairs for answers to improve itself through …
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Effective semantic-based keyword search over relational databases for knowledge discovery
… curve) the existing state-of-the-art ranking functions by incorporating the query keywords' proximity and query keywords' quadgrams of the text attributes with long string into the scoring function.</p> <p>We have adapted a novel approach in making keyword search recommendations based on the …
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