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 32 for “"Function prediction"”.
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Protein Function Prediction Using Graph Convolutional Network
This project advances protein function prediction by integrating protein language models (PLMs) and graph convolutional networks (GCNs), addressing the limitations of traditional methods that rely heavily on sequence similarity. The proposed model leverages diverse protein features, including …
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Systems Uncertainty in Systems Biology & Gene Function Prediction
… of uncertainty in systems biology, namely gene function prediction, and compare several algorithms designed for that purpose.
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Leveraging expression and network data for protein function prediction
Protein function prediction is one of the prominent problems in bioinformatics today. Protein annotation is slowly falling behind as more and more genomes are being sequenced. Experimental methods are expensive and time consuming, which leaves computational methods to fill the gap. While …
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Accurate Protein Function Prediction with Graph Transformer-Based Function Localization
Protein function prediction is a fundamental challenge in biology, crucial for understanding biological processes, disease mechanisms, and accelerating drug discovery. While computational methods leveraging sequence or structural information have advanced, accurately translating protein structure …
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Applications of Machine Learning in Source Attribution and Gene Function Prediction
… using whole genome sequencing data, and (2) the functional annotation of genes using single- cell RNA sequencing data. This work proposes the development of a bioinformatics pipeline tailored for identifying genomic variants, including gene presence/absence and single nu- cleotide polymorphism. …
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Hierarchical multi-label classification for protein function prediction going beyond traditional approaches
… that are in turn organized in a hierarchy. Functional classification of genes is a challenging problem in functional genomics due to several reasons. First, each gene participates in multiple biological activities. Hence, prediction models should support multi-label classification. Second, …
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Insights into the evolution of protein domains give rise to improvements of function prediction
… sequences in public databases has turned the prediction of protein function into a challenging research field. Traditional annotation methods are often error-prone due to the small subset of proteins with experimentally verified function. Goal of this thesis was to analyse the function and …
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Multi-Modal Protein Function Prediction using a Joint Embedding Space from Two Graph Neural Networks
… and proteomics, determining protein functions experimentally is expensive and slow. There’s a growing need for precise and quick computational prediction methods, filling the gap between sequence discovery and functional understanding. Over recent years there has been an influx of …
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Multi-target Prediction Methods for Bioinformatics: Approaches for Protein Function Prediction and Candidate Discovery for Gene Regulatory Network Expansion
… organisms, in this thesis we focus on their functional analysis and the intrinsic multi-target nature of this task. To this end, we propose different predictive methods, specifically developed to exploit side knowledge among target variables and examples. As a first contribution we face the …
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Improving Profile Similarity Search and Alignment of Protein Sequences
Protein function prediction is one of the most important problems in the field of computational biology. The most reliable method to predict protein function is to detect homologs. Homologous proteins tend to possess conserved sequence motifs, the same structure folds, and similar functional sites. …
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Genome data analysis, protein function and structure prediction by machine learning techniques
… them, and extract useful structure and function information, such as the function of genes, the structure of proteins encoded by gene, and the function of proteins. Understanding these information is crucial for us to improve longevity and quality of life, and has a lot of applications, …
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Assessing the Role of Clusters Derived from Large Sequence Similarity Networks for Gene Function Predictions
… for biological experiments, computational predictions of gene functions can aid in reducing a large list of candidate genes to a few promising targets. Various computational solutions have been proposed and developed for gene function prediction. These solutions utilize various forms of …
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PROTEIN FUNCTION, DIVERISTY AND FUNCTIONAL INTERPLAY
Functional annotations of novel or unknown proteins is one of the central problems in post-genomics bioinformatics research. With the vast expansion of genomic and proteomic data and technologies over the last decade, development of automated function prediction (AFP) methods for large-scale …
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A Thing Is What We Say It Is: Referential Communication and Indirect Category Learning
… lexicon for novel objects and discovering the functional significance of those objects during an indirect category learning activity. During the learning task, participants worked either individually or as cooperative dyads to learn four combinations of orthogonal functional features—nutritive …
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Reconstructing gene function and gene regulatory networks in prokaryotes
… fraction of genes from bacteria have an unknown function. Even the most studied microbe, E. coli, still has around 30 percent of its genes uncharacterised. Using phenotype data and genomic data, a method for gene function prediction is improved and implemented in a tool called GeneTrawler. The …
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Data Mining Algorithms for Classification of Complex Biomedical Data
… Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray classification, samples belong to several predefined categories (e.g., cancer vs. control tissues) and the goal is to build a predictor that classifies a …
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Graph diffusions and matrix functions: fast algorithms and localization results
… in graphs such as webpage ranking, protein-function prediction, and product categorization and recommendation. As real-world networks grow to have millions of nodes and billions of edges, the scalability of network analysis algorithms becomes increasingly important. Whereas many standard …
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Learning the Language of Antibody Hypervariability Through Biological Property Prediction
… to be successful in a variety of structure and function-prediction contexts. However, foundational PLMs (those trained on the corpus of all proteins) rely on evolutionary co-conservation of protein sub-sequences, but this distributional hypothesis does not hold for antibody hypervariable …
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MPrompt: A Pretraining-Prompting Scheme for Enhanced Fewshot Subgraph Classification
… and real-world datasets, including protein function prediction and social network analysis. Our method demonstrated performance improvement under few-shot experiment setting and maintained comparable performance in full-shot settings while requiring less computation.
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Neuropsychological symptoms in the learning disabled child : a symptomology inventory
… of symptomology related to neurological dysfunction has been reported for at least some learning disabled (LD) students. This investigation examined the self-reported neuropsychological symptoms of LD and normal students in grades 3 through 12. Determination of group membership based on the …
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