406 research outputs found

    Computational Approaches to Drug Profiling and Drug-Protein Interactions

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    Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a long period of stagnation in drug approvals. Due to the extreme costs associated with introducing a drug to the market, locating and understanding the reasons for clinical failure is key to future productivity. As part of this PhD, three main contributions were made in this respect. First, the web platform, LigNFam enables users to interactively explore similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly, two deep-learning-based binding site comparison tools were developed, competing with the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold relationships and has already been used in multiple projects, including integration into a virtual screening pipeline to increase the tractability of ultra-large screening experiments. Together, and with existing tools, the contributions made will aid in the understanding of drug-protein relationships, particularly in the fields of off-target prediction and drug repurposing, helping to design better drugs faster

    Behavior quantification as the missing link between fields: Tools for digital psychiatry and their role in the future of neurobiology

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    The great behavioral heterogeneity observed between individuals with the same psychiatric disorder and even within one individual over time complicates both clinical practice and biomedical research. However, modern technologies are an exciting opportunity to improve behavioral characterization. Existing psychiatry methods that are qualitative or unscalable, such as patient surveys or clinical interviews, can now be collected at a greater capacity and analyzed to produce new quantitative measures. Furthermore, recent capabilities for continuous collection of passive sensor streams, such as phone GPS or smartwatch accelerometer, open avenues of novel questioning that were previously entirely unrealistic. Their temporally dense nature enables a cohesive study of real-time neural and behavioral signals. To develop comprehensive neurobiological models of psychiatric disease, it will be critical to first develop strong methods for behavioral quantification. There is huge potential in what can theoretically be captured by current technologies, but this in itself presents a large computational challenge -- one that will necessitate new data processing tools, new machine learning techniques, and ultimately a shift in how interdisciplinary work is conducted. In my thesis, I detail research projects that take different perspectives on digital psychiatry, subsequently tying ideas together with a concluding discussion on the future of the field. I also provide software infrastructure where relevant, with extensive documentation. Major contributions include scientific arguments and proof of concept results for daily free-form audio journals as an underappreciated psychiatry research datatype, as well as novel stability theorems and pilot empirical success for a proposed multi-area recurrent neural network architecture.Comment: PhD thesis cop

    Reference Frames in Human Sensory, Motor, and Cognitive Processing

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    Reference-frames, or coordinate systems, are used to express properties and relationships of objects in the environment. While the use of reference-frames is well understood in physical sciences, how the brain uses reference-frames remains a fundamental question. The goal of this dissertation is to reach a better understanding of reference-frames in human perceptual, motor, and cognitive processing. In the first project, we study reference-frames in perception and develop a model to explain the transition from egocentric (based on the observer) to exocentric (based outside the observer) reference-frames to account for the perception of relative motion. In a second project, we focus on motor behavior, more specifically on goal-directed reaching. We develop a model that explains how egocentric perceptual and motor reference-frames can be coordinated through exocentric reference-frames. Finally, in a third project, we study how the cognitive system can store and recognize objects by using sensorimotor schema that allows mental rotation within an exocentric reference-frame

    Crystallographic fragment screening - improvement of workflow, tools and procedures, and application for the development of enzyme and protein-protein interaction modulators

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    One of the great societal challenges of today is the fight against diseases which reduce life expectancy and lead to high economic losses. Both the understanding and the addressing of these diseases need research activities at all levels. One aspect of this is the discovery and development of tool compounds and drugs. Tool compounds support disease research and the development of drugs. For about 20 years, the discovery of new compounds has been attempted by screening small organic molecules by high-throughput methods. More recently, X-ray crystallography has emerged as the most promising method to conduct such screening. Crystallographic fragment-screening (CFS) generates binding information as well as 3D-structural information of the target protein in complex with the bound fragment. This doctoral research project is focused primarily on the optimization of the crystallographic fragment screening workflow. Investigated were the requirements for more successful screening campaigns with respect to the crystal system studied, the fragment libraries, the handling of the crystalline samples, as well as the handling of the data associated with a screening campaign. The improved CFS workflow was presented as a detailed protocol and as an accompanying video to train future CFS users in a streamlined and accessible way. Together, these improvements make CFS campaigns a more high-throughput method, offering the ability to screen larger fragment libraries and allowing higher numbers of campaigns performed per year. The protein targets throughout the project were two enzymes and a spliceosomal protein-protein complex. The enzymes comprised the aspartic protease Endothiapepsin and the SARS-Cov-2 main protease. The protein-protein complex was the RNaseH-like domain of Prp8, a vital structural protein in the spliceosome, together with its nuclear shuttling factor Aar2. By performing the CFS campaigns against disease-relevant targets, the resulting fragment hits could be used directly to develop tool compounds or drugs. The first steps of optimization of fragment hits into higher affinity binders were also investigated for improvements. In summary, a plethora of novel starting points for tool compound and drug development was identified

    Training Manual on Advanced Analytical Tools for Social Science Research Vol.1

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    Applying appropriate analytical techniques form the backbone of any research endeavor in agriculture, fisheries, and allied sciences. Without proper knowledge of applying statistical/econometric tools, software, and derivation of inferences from the same, it would not be possible to gather relevant interpretations of the investigation. Hence, the importance of well-designed data collection protocol, analysis, and interpretation cannot be underestimated. Such inferences form the basis of sound policy planning and resource management. Technology advancements and the development of analytical software have made the data analysis process less laborious. A basic understanding of the application of advanced analytical tools and their interpretation increases the productivity and efficiency of social science researchers engaged in agriculture/animal/fisheries science research. Hence the Winter School on Advanced Analytical Tools for Social Science Research is designed to enhance the analytical skills of social science researchers from NARES by allowing them to familiarize with advanced analytical procedures and their practical applications. This Winter School is a step towards familiarizing recent analytical techniques in social science to derive quality research outputs. The course is designed to acquaint the participants with areas such as exploratory data analysis, sampling techniques, data classificatory techniques, non–parametric methods, econometric analysis, and time series modeling, etc. Lectures on GIS/Spatial modeling, scaling techniques, data mining and big data analytics, machine learning techniques, and ecosystem evaluation have also been touched upon. The course is more practical-oriented, with a greater emphasis on interpreting the results. It employs a combination of lectures and exercises using statistical software

    Accessibility of Health Data Representations for Older Adults: Challenges and Opportunities for Design

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    Health data of consumer off-the-shelf wearable devices is often conveyed to users through visual data representations and analyses. However, this is not always accessible to people with disabilities or older people due to low vision, cognitive impairments or literacy issues. Due to trade-offs between aesthetics predominance or information overload, real-time user feedback may not be conveyed easily from sensor devices through visual cues like graphs and texts. These difficulties may hinder critical data understanding. Additional auditory and tactile feedback can also provide immediate and accessible cues from these wearable devices, but it is necessary to understand existing data representation limitations initially. To avoid higher cognitive and visual overload, auditory and haptic cues can be designed to complement, replace or reinforce visual cues. In this paper, we outline the challenges in existing data representation and the necessary evidence to enhance the accessibility of health information from personal sensing devices used to monitor health parameters such as blood pressure, sleep, activity, heart rate and more. By creating innovative and inclusive user feedback, users will likely want to engage and interact with new devices and their own data

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    Process simulation and optimization of biomass fast pyrolysis

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    Die intensive Nutzung fossiler Brennstoffe für die Energie-, Kraftstoff- und Rohstoffproduktion hat globale und langanhaltende ökologische, politische und wirtschaftliche Auswirkungen, von denen ärmere Bevölkerungsschichten und Länder ohne einfachen Zugang zu diesen Rohstoffen außerordentlich stark betroffen sind. Jedem ist klar, denn ein Übergang zu erneuerbaren Energiequellen ist notwendig, der keine vollständige Reform des heutigen Energiesystems erfordert. Biomasse, insbesondere forstwirtschaftliche und pflanzliche Rückstände, ist eine wenig erforschte Energiequelle, deren Nutzung zur weiteren Aufwertung der ländlichen Wirtschaft beitragen kann, indem ein Nebenprodukt von geringem wirtschaftlichem Interesse verwendet wird. Unter den konkurrierenden Möglichkeiten ist Schnellpyrolyse ein thermochemischer Umwandlungspfad, der aus biogenem Material energiereiche Produkte und Produkte mit Mehrwert erzeugen kann. Die Pyrolyse kann Produkte in drei verschiedenen Zuständen erzeugen: gasförmig, flüssig und fest. Dies ist ein wichtiger Vorteil gegenüber traditionellen Verfahren, die nur eine oder zwei dieser Phasen oder überhaupt nur Wärme erzeugen. Alle erzeugten Produkte sind sofort für die Energieerzeugung nutzbar und weisen eine vergleichbare oder höhere Energiedichte als Rohbiomasse auf; sie können auch zu höherwertigen Produkten weiterverarbeitet werden, darunter Wasserstoff, Kraftstoffe, Zwischenprodukte und Feinchemikalien. Dies ist die Hauptmotivation für das bioliq®-Projekt. Dieses Promotionsprojekt konzentriert sich auf die Erstellung eines rigorosen und vielseitig verwendbaren Schnellpyrolysemodells, das auf einer realen Materialisation des bioliq®-Projekts im industriellen Pilotmaß- stab basiert. Das Modell basiert auf den Eigenschaften von lignozellulosehaltiger Biomasse, verwendet eine Reihe von Reaktoren zur Abbildung des realen Biomasseabbaus und bietet strenge Simulationen der Abschreckungsschleifen, die für eine zweistufige Flüssigproduktgewinnung verwendet werden. Bei der Initialisierung des Modells wurde Weizenstroh als Modellbiomasse verwendet, eine ungewöhnliche Wahl aufgrund seines hohen Aschegehalts, der katalytische Effekte begünstigt. In diesem Sinne wurde Thermogravimetrie für die Charakterisierung des Biomasseabbaus, die Schätzung des Lignozellulosegehalts und der Pyrolysekinetik für dieses Ausgangsmaterial verwendet. Um die Vielseitigkeit des Modells in Bezug auf die Eingabedaten zu gewährleisten, wurden mehrere in der Literatur verfügbare Reaktionsnetzwerke, die die lignozellulosehaltige Zusammensetzung der Biomasse in die Endprodukte umwandeln, analysiert und angepasst; die Zusammensetzung des erzeugten Kondensats wurde durch Sekundär- und Alterungsreaktionen auf die experimentellen Daten angepasst. Die Zusammensetzung der Kondensate wurde gestrafft, um die Modellierung zu erleichtern, und die definierten chemischen Spezies wurden im Hinblick auf ihre thermophysikalischen Eigenschaften vollständig charakterisiert. Für einige der ausgewählten Spezies mangelt experimentelle Charakterisierung, und es wurden bestehende Schätzmethoden implementiert, deren Ergebnisse in dieser Arbeit zur Verfügung gestellt wurden. Die abschließenden Tests berücksichtigten die Variation des Feuchtigkeitsgehalts im Weizenstroh und ergaben Ergebnisse, die mit den experimentellen Daten übereinstimmen. Nachfolgende Modelle, die verschiedene lignozellulosehaltige Biomassen berücksichtigten, bestätigten die Vielseitigkeit des entwickelten Modells bei der Vorhersage der Produktverteilung und der Zusammensetzung des Kondensats. Das endgültige Modell ist eigenständig voll funktionsfähig und kann im Hinblick auf Prozessspezifikationen und vor- und nachgeschaltete Implementierungen weiter angepasst werden

    Differential evolution of non-coding DNA across eukaryotes and its close relationship with complex multicellularity on Earth

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    Here, I elaborate on the hypothesis that complex multicellularity (CM, sensu Knoll) is a major evolutionary transition (sensu Szathmary), which has convergently evolved a few times in Eukarya only: within red and brown algae, plants, animals, and fungi. Paradoxically, CM seems to correlate with the expansion of non-coding DNA (ncDNA) in the genome rather than with genome size or the total number of genes. Thus, I investigated the correlation between genome and organismal complexities across 461 eukaryotes under a phylogenetically controlled framework. To that end, I introduce the first formal definitions and criteria to distinguish ‘unicellularity’, ‘simple’ (SM) and ‘complex’ multicellularity. Rather than using the limited available estimations of unique cell types, the 461 species were classified according to our criteria by reviewing their life cycle and body plan development from literature. Then, I investigated the evolutionary association between genome size and 35 genome-wide features (introns and exons from protein-coding genes, repeats and intergenic regions) describing the coding and ncDNA complexities of the 461 genomes. To that end, I developed ‘GenomeContent’, a program that systematically retrieves massive multidimensional datasets from gene annotations and calculates over 100 genome-wide statistics. R-scripts coupled to parallel computing were created to calculate >260,000 phylogenetic controlled pairwise correlations. As previously reported, both repetitive and non-repetitive DNA are found to be scaling strongly and positively with genome size across most eukaryotic lineages. Contrasting previous studies, I demonstrate that changes in the length and repeat composition of introns are only weakly or moderately associated with changes in genome size at the global phylogenetic scale, while changes in intron abundance (within and across genes) are either not or only very weakly associated with changes in genome size. Our evolutionary correlations are robust to: different phylogenetic regression methods, uncertainties in the tree of eukaryotes, variations in genome size estimates, and randomly reduced datasets. Then, I investigated the correlation between the 35 genome-wide features and the cellular complexity of the 461 eukaryotes with phylogenetic Principal Component Analyses. Our results endorse a genetic distinction between SM and CM in Archaeplastida and Metazoa, but not so clearly in Fungi. Remarkably, complex multicellular organisms and their closest ancestral relatives are characterized by high intron-richness, regardless of genome size. Finally, I argue why and how a vast expansion of non-coding RNA (ncRNA) regulators rather than of novel protein regulators can promote the emergence of CM in Eukarya. As a proof of concept, I co-developed a novel ‘ceRNA-motif pipeline’ for the prediction of “competing endogenous” ncRNAs (ceRNAs) that regulate microRNAs in plants. We identified three candidate ceRNAs motifs: MIM166, MIM171 and MIM159/319, which were found to be conserved across land plants and be potentially involved in diverse developmental processes and stress responses. Collectively, the findings of this dissertation support our hypothesis that CM on Earth is a major evolutionary transition promoted by the expansion of two major ncDNA classes, introns and regulatory ncRNAs, which might have boosted the irreversible commitment of cell types in certain lineages by canalizing the timing and kinetics of the eukaryotic transcriptome.:Cover page Abstract Acknowledgements Index 1. The structure of this thesis 1.1. Structure of this PhD dissertation 1.2. Publications of this PhD dissertation 1.3. Computational infrastructure and resources 1.4. Disclosure of financial support and information use 1.5. Acknowledgements 1.6. Author contributions and use of impersonal and personal pronouns 2. Biological background 2.1. The complexity of the eukaryotic genome 2.2. The problem of counting and defining “genes” in eukaryotes 2.3. The “function” concept for genes and “dark matter” 2.4. Increases of organismal complexity on Earth through multicellularity 2.5. Multicellularity is a “fitness transition” in individuality 2.6. The complexity of cell differentiation in multicellularity 3. Technical background 3.1. The Phylogenetic Comparative Method (PCM) 3.2. RNA secondary structure prediction 3.3. Some standards for genome and gene annotation 4. What is in a eukaryotic genome? GenomeContent provides a good answer 4.1. Background 4.2. Motivation: an interoperable tool for data retrieval of gene annotations 4.3. Methods 4.4. Results 4.5. Discussion 5. The evolutionary correlation between genome size and ncDNA 5.1. Background 5.2. Motivation: estimating the relationship between genome size and ncDNA 5.3. Methods 5.4. Results 5.5. Discussion 6. The relationship between non-coding DNA and Complex Multicellularity 6.1. Background 6.2. Motivation: How to define and measure complex multicellularity across eukaryotes? 6.3. Methods 6.4. Results 6.5. Discussion 7. The ceRNA motif pipeline: regulation of microRNAs by target mimics 7.1. Background 7.2. A revisited protocol for the computational analysis of Target Mimics 7.3. Motivation: a novel pipeline for ceRNA motif discovery 7.4. Methods 7.5. Results 7.6. Discussion 8. Conclusions and outlook 8.1. Contributions and lessons for the bioinformatics of large-scale comparative analyses 8.2. Intron features are evolutionarily decoupled among themselves and from genome size throughout Eukarya 8.3. “Complex multicellularity” is a major evolutionary transition 8.4. Role of RNA throughout the evolution of life and complex multicellularity on Earth 9. Supplementary Data Bibliography Curriculum Scientiae Selbständigkeitserklärung (declaration of authorship

    Exploring Animal Behavior Through Sound: Volume 1

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    This open-access book empowers its readers to explore the acoustic world of animals. By listening to the sounds of nature, we can study animal behavior, distribution, and demographics; their habitat characteristics and needs; and the effects of noise. Sound recording is an efficient and affordable tool, independent of daylight and weather; and recorders may be left in place for many months at a time, continuously collecting data on animals and their environment. This book builds the skills and knowledge necessary to collect and interpret acoustic data from terrestrial and marine environments. Beginning with a history of sound recording, the chapters provide an overview of off-the-shelf recording equipment and analysis tools (including automated signal detectors and statistical methods); audiometric methods; acoustic terminology, quantities, and units; sound propagation in air and under water; soundscapes of terrestrial and marine habitats; animal acoustic and vibrational communication; echolocation; and the effects of noise. This book will be useful to students and researchers of animal ecology who wish to add acoustics to their toolbox, as well as to environmental managers in industry and government
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