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High-performance exploration and querying of selected multi-dimensional spaces in life sciences
Kratochvíl, Miroslav ; Bednárek, David (advisor) ; Glaab, Enrico (referee) ; Svozil, Daniel (referee)
This thesis studies, implements and experiments with specific application-oriented approaches for exploring and querying multi-dimensional datasets. The first part of the thesis scrutinizes indexing of the complex space of chemical compounds, and details a design of high-performance retrieval system for small molecules. The resulting system is then utilized within a wider context of federated search in heterogeneous data and metadata related to the chemical datasets. In the second part, the thesis focuses on fast visualization and exploration of many-dimensional data that originate from single- cell cytometry. Self-organizing maps are used to derive fast methods for analysis of the datasets, and used as a base for a novel data visualization algorithm. Finally, a similar approach is utilized for highly interactive exploration of multimedia datasets. The main contributions of the thesis comprise the advancement in optimization and methods for querying the chemical data implemented in the Sachem database cartridge, the federated, SPARQL-based interface to Sachem that provides the heterogeneous search support, dimensionality reduction algorithm EmbedSOM, design and implementation of the specific EmbedSOM-backed analysis tool for flow and mass cytometry, and design and implementation of the multimedia...
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Scaffold hopping-based exploration of chemical space
Mikeš, Marek ; Hoksza, David (advisor) ; Krivák, Radoslav (referee)
This work is based on the Molpher SW project, which is client-server application aiding exploration of chemical space between two input molecules. Aim of master thesis was modify the current version of program to manage scaffold hopping technique. This technique represents molecule in a simplified way. The simpler molecule is called scaffold. First of all there was need to define seve- ral levels of granularity and for each level define morphing operators. Server was modified with respect for parallelization. Experimental exploration of chemical space with and without the new feature is part of this work too. Powered by TCPDF (www.tcpdf.org)
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High-performance exploration and querying of selected multi-dimensional spaces in life sciences
Kratochvíl, Miroslav ; Bednárek, David (advisor) ; Glaab, Enrico (referee) ; Svozil, Daniel (referee)
This thesis studies, implements and experiments with specific application-oriented approaches for exploring and querying multi-dimensional datasets. The first part of the thesis scrutinizes indexing of the complex space of chemical compounds, and details a design of high-performance retrieval system for small molecules. The resulting system is then utilized within a wider context of federated search in heterogeneous data and metadata related to the chemical datasets. In the second part, the thesis focuses on fast visualization and exploration of many-dimensional data that originate from single- cell cytometry. Self-organizing maps are used to derive fast methods for analysis of the datasets, and used as a base for a novel data visualization algorithm. Finally, a similar approach is utilized for highly interactive exploration of multimedia datasets. The main contributions of the thesis comprise the advancement in optimization and methods for querying the chemical data implemented in the Sachem database cartridge, the federated, SPARQL-based interface to Sachem that provides the heterogeneous search support, dimensionality reduction algorithm EmbedSOM, design and implementation of the specific EmbedSOM-backed analysis tool for flow and mass cytometry, and design and implementation of the multimedia...
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Modeling of fragment-based molecular similarity
Lamprecht, Matyáš ; Škoda, Petr (advisor) ; Mráz, František (referee)
Virtual screening is a part of computer-aided drug design, which aims to identify biologically active molecules. The ligand-based virtual screening employs known bio- logically active molecules and similarity search. A common approach to computation of molecular similarity is to utilize molecular fingerprints. Hashed structural molecular fingerprints hash fragments (subgraphs) of molecular graphs into a bit string reducing the problem of molecular similarity to the bit string similarity. Due to the hashing two distinct fragments may collide, which causes information loss. For this reason collisions are considered unwanted and they are generally believed to decrease a performance. Our goal was, contrary to the general believe, test whether collisions can have positive impact on the performance. For this purpose we designed several similarity models based on fragments. In order to make testing and evaluation easy we implemented testing environ- ment. Results of our experiments prove that some collisions can outperform commonly used methods. Moreover some collisions in a specific model can lead to a performance of AUC over 0.99. 1
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Accelerating structure search in small-molecule databases
Kratochvíl, Miroslav ; Bednárek, David (advisor) ; Hoksza, David (referee)
Structure search is one of the valuable capabilities of small-molecule databases. Available chemical cartridges typically provide acceptable search performance for processing user queries, but do not scale satisfactorily with dataset size. This thesis presents Sachem, a new open-source chemical car- tridge that implements a novel method of substructure search, which em- ploys newly designed fingerprints stored in inverted indexes. The perfor- mance of the method was assessed on datasets that contain tens of mil- lions of molecules. Comparison of the performance to that of other available cartridges revealed improvements in overall search speed, scaling potential and screen-out efficiency. Additionally, the thesis presents an application of Sachem; a SPARQL service that augments existing semantic services by including results of substructure and similarity searches in small-molecule databases. The result offers new possibilities for simpler querying of the interoperable heterogeneous data sources. 1
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Utilization of latent semantic analysis in virtual screening
Kolář, Jiří ; Hoksza, David (advisor) ; Škoda, Petr (referee)
Title: Utilization of latent semantic analysis in virtual screening Author: Jiří Kolář Department: Department of Software Engineering Supervisor: RNDr. David Hoksza, Ph.D., Department of Software Engineering Abstract: Aim of this thesis is to investigate utilisation of latent semantic in- dexing in Virtual screening. We have examined existing VS method called lat- ent semantic structural indexing (LaSSI) and compared performance of different structural fingerprints. Additionally, we have developed a new model that com- pare fragments of molecules by usage of latent semantic indexing. Fragments are characterized by formula based counts and descriptors describing the physi- cochemical properties. Results of our methods are compared to VS techniques using directly standard fingerprints. Keywords: virtual screening cheminformatics ligand-based fingerprints ECFP TT latent semantic analysis LaSSI iii
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Využití simulovaného žíhání pro optimalizaci molekulárních otisků ve virtuálním screeningu
Filandr, Adam ; Hoksza, David (advisor) ; Kratochvíl, Miroslav (referee)
Ligand based virtual screening can be realised with various molecular rep- resentations. Fragment-feature representation represents the molecules as a set of fragments, where each fragment receives a set of descriptors. First goal of this thesis is to find suitable similarity function for such represen- tation. This representation can also be improved by assigning a weight for each descriptor, which gives it a priority in a given similarity function. The second goal of this thesis is to examine simulated annealing as an algorithm used to find the weights. We experimentally analysed the influence of various fragment types, descriptor types, similarity functions, correlated descriptors, fragment noise and parameters of simulated annealing. Because the experi- ments are computationally demanding, we also created a tool for large scale computations. 1
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Hierarchical visualization of the chemical space
Velkoborský, Jakub ; Hoksza, David (advisor) ; Škoda, Petr (referee)
The purpose of this thesis was to design and implement a hierarchical approach to visualization of the chemical space. Such visualization is a challenging yet important topic used in diverse fields ranging from material engineering to drug design. Especially in drug design, modern methods of high- throughput screening generate large amounts of data that would benefit from hierarchical analysis. One possible approach to hierarchical classification of molecules is a structure based classification based on molecular scaffolds. The scaffolds are widely used by medicinal chemists to group molecules of similar properties. A few scaffold-based hierarchical visualization methods have been proposed. However, to our best knowledge, there exists no tool that would provide a scaffold-based hierarchical visualization of molecular data sets on the background of known chemical space. In this thesis, such tool was created. First, a scaffold tree hierarchy based on ring topologies was designed. Next, this hierarchy was used to analyze frequency of scaffolds extracted from molecules in PubChem Compound database. Subsequently, the PubChem Compound scaffold frequency data was used as a background for visualization of molecular data sets. The visualization is performed by a client-server application implemented as a part of...
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Scaffold hopping-based exploration of chemical space
Mikeš, Marek ; Hoksza, David (advisor) ; Krivák, Radoslav (referee)
This work is based on the Molpher SW project, which is client-server application aiding exploration of chemical space between two input molecules. Aim of master thesis was modify the current version of program to manage scaffold hopping technique. This technique represents molecule in a simplified way. The simpler molecule is called scaffold. First of all there was need to define seve- ral levels of granularity and for each level define morphing operators. Server was modified with respect for parallelization. Experimental exploration of chemical space with and without the new feature is part of this work too. Powered by TCPDF (www.tcpdf.org)
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Machine learning-based identification of separating features in molecular fragments
Ravi, Aakash ; Hoksza, David (advisor) ; Škoda, Petr (referee)
Chosen molecular representation is one of the key parameters of virtual screening campaigns where one is searching in-silico for active molecules with respect to given macromolecular target. Most campaigns employ a molecular representation in which a molecule is represented by the presence or absence of a predefined set of topological fragments. Often, this information is enriched by physiochemical features of these fragments: i.e. the representation distinguishes fragments with identical topology, but different features. Given molecular representation, however, most approaches always use the same static set of features irrespective of the specific target. The goal of this thesis is, given a set of known active and inactive molecules with respect to a target, to study the possibilities of parameterization of a fragment-based molecular representation with feature weights dependent on the given target. In this setting, we are given a very general molecular representation, with targets represented by sets of known active and inactive molecules. We subsequently propose a machine-learning approach that would identify which of the features are relevant for the given target. This will be done using a multi-stage pipeline that includes data preprocessing using statistical imputation and dimensionality...
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