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Agrawal, Isha (author)
Metagenomic Next-Generation Sequencing (mNGS) presents a promising avenue to generate massive volume of sequence reads in a short period of time. This has opened opportunities for disease diagnosis based on individual variations and mutations by considering the microbiome profile of each patient. However, the effective use of this data requires...
master thesis 2023
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d' Abreu de Paulo, Gedeon (author)
Cancer is one of the leading causes of death in the world. While there have been many studies investigating the development and progression of cancer in human tissues using host omics data or microbial data, there is a lack of research combining both types of data, even though both modalities have been shown to affect cancer morphology and...
master thesis 2023
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van Graft, Tijmen (author)
Metabolic engineering is an important field in biotechnology, aimed at optimizing cellular processes to produce desired compounds. In this thesis, we focus on predicting the metabolome from the proteome, as understanding this relationship is crucial for understanding cellular metabolism. We investigate the usage of additional biological...
master thesis 2023
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Cosma, Bianca (author)
<b>Motivation: </b>The development of automated protein function prediction models is essential in closing the gap between the large amount of protein sequence data available and the fraction of validly annotated data. Recent approaches to function prediction rely on unsupervised deep learning models, through which protein sequences are...
bachelor thesis 2022
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van der Toorn, Eric (author)
Next-Generation Sequencing (NGS) has made it possible to perform metagenomic sequencing of environmental microbiome samples. Colorectal cancer (CRC) benefits from early detection, and many studies find correlations between disease presence and abundance of species in samples of the microbiome. However, these studies are hard to reproduce and...
master thesis 2022
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Rosenberg, Jaron (author)
The purpose of this research is to reduce food waste by monitoring the ripening process of strawberries in order to optimize the harvesting time. To improve the moment of harvest, we need to know the ripeness of a strawberry. Using data from different color ranges and spaces we should be able to predict the ripeness of a strawberry on a 1-10...
bachelor thesis 2022
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Buitenweg, Jurriaan (author)
To reduce food waste, the strawberry harvesting process should be optimized. In the modern era, computer vision can provide huge amounts of help. This paper focuses on optimizing pre-trained convolutional neural networks (CNN) to determine the maturity level of strawberries on a 1-10 scale. Here, 1 means unripe and 10 means overripe. Maturity...
bachelor thesis 2022
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Bechtold, Jeroen (author)
This paper tries to combat the food waste of strawberries during the harvesting steps.<br/>An automatic pipeline must be established to combat this food waste.<br/>One of the steps needed in this pipeline is detecting strawberries in images.<br/>Therefore, this paper aims to find out which Convolutional Neural Network (CNN) can be best used to...
bachelor thesis 2022
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van Melis, Kris (author)
To reduce food waste, it is important to know what strawberries to prioritise for harvesting. Size is an important quality attribute for strawberry. In order to know the size, the depth of the strawberry in the image must been known. To estimate the depth, stereovision gets utilized using binocular images. Since classic stereovision methods are...
bachelor thesis 2022
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Narkhede, Rucha (author)
Viral quasispecies refers to viral populations that comprises of numerous viral strains closely related to each other due to within-host evolution or co-infection. The reconstruction of viral strain-specific genomes using sequencing reads is referred to as viral quasispecies assembly, and it is also crucial to determine the relative abundances...
master thesis 2022
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Veldhuis, Marthe (author)
Using machine learning to determine the number of contributors (NOC) in short tandem repeat (STR) mixture DNA profiles has been shown to obtain good accuracy. However, the models used so far are not transparent to users as they only output a prediction without any reasoning for that conclusion. Therefore, we leverage techniques from the field of...
master thesis 2021
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Kuijpers, Jos (author), Quist, Joris (author), Zorgdrager, Wouter (author)
CodeFeedr is a research project at the software engineering division of the Delft University of Technology in collaboration with the Software Improvement Group. The research focuses on a software infrastructure which serves software practitioners in utilizing data-driven decision making. Currently, frameworks like Apache Flink are capable of...
bachelor thesis 2018
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van Dijk, Lucas (author)
Capturing all genetic variation within a polyploid organism is a challenge. Most current de novo assemblers have no notion of the concept “ploidy”. Consequently, when assembling the genome of diploid or higher ploidy organisms, the assembler mixes reads coming from either chromosome copy and builds a single DNA sequence representing an arbitrary...
master thesis 2017
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Mouzos, L. (author)
In recent years, cheap sequencing has resulted in hundreds or thousands of individual genomes available for many species. Therefore, it is logical to rethink the concept of the reference genome; as consisting of a population of genomes rather than being a single one. The term pan-genome describes a population of genomes of the same species or a...
master thesis 2017
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Mouzos, L. (author)
In recent years, cheap sequencing has resulted in hundreds or thousands of individual genomes available for many species. Therefore, it is logical to rethink the concept of the reference genome; as consisting of a population of genomes rather than being a single one. The term pan-genome describes a population of genomes of the same species or a...
master thesis 2017
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Beker, B. (author), Brugsma, R. (author), Offerijns, J.F. (author)
Recommendation systems are algorithms that aim to predict what items are preferred by a user, based on a recorded history of user activity. Magnet.me is a company which recommends companies and opportunities to students. Potential algorithms for recommendation systems are memory-based and model-based coll aborative filtering, graph- based...
bachelor thesis 2017
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Boot, J. (author), Hommes, J. (author), Rijsdijk, J. (author)
In recent days, the products and services provided by banks have moved to the digital domain more and more. Since most people rely on these services in their day to day lives, availability and reliability are very important in the success of a bank. In an effort to increase automation in this regard, ING Bank wants to employ machine learning to...
bachelor thesis 2016
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Van Oorschot, J. (author), Catshoek, T. (author), Brand, S. (author)
bachelor thesis 2016
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Kreynen, B.L.L. (author), Olieman, C. (author), van Doorn, F.A. (author), Spanoghe, M. (author)
For our bachelor project we have been using machine learning to predict account balances for a large Dutch bank holding company. The company’s main interest is the integration of machine learning techniques in their systems. To enable this we have been asked to develop a product to predict account balances for the clients of associated banks....
bachelor thesis 2016
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Bilen, H. (author), Zwart, M.D. (author)
With the current increase of user generated data, the need for tools to process large quantities of data is increasing. One of the courses of the Computer Science BSc curriculum is the Big Data Processing course. The Big Data Processing course teaches students ways of doing so. A popular and teached method is using MapReduce, a programming model...
bachelor thesis 2016
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