2,848 search results for “data analyse” in the Public website
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A large-scale crop protection bioassay data set
ChEMBL is a large-scale drug discovery database containing bioactivity information primarily extracted from scientific literature.
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Countering Lone Actor Terrorism: Data Collection & Analysis
This project aims to improve understanding of, and responses to, the phenomenon of lone actors through analysis of comprehensive data on cases from across Europe.
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EU Erasmus+ Curriculum Development in Data Science and Artificial Intelligence
LIACS is a partner in the EU Erasmus+ Curriculum Development for the Asian education system. The knowledge available in the field of Data Science and Artificial Intelligence education will be shared and adapted for the Asian market.
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Gender sidestreaming? Analysing gender mainstreaming in national militaries and international peacekeeping
Gender sidestreaming? Analysing gender mainstreaming in national militaries and international peacekeeping
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Cheminformatics: Analyzing small-molecule activity data
While bioinformatics methods deal with the analysis of sequence information (be it proteins or DNA), the field of cheminformatics is concerned with the analysis of small-molecule datasets.
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Leiden University launches Data Science research programme
Leiden University is investing 4 million euros in a new Data Science research programme. This is a joint initiative of all the faculties, headed by Dean Geert de Snoo at the Faculty of Science. The programme will focus on Leiden scientific data.
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Data Atlas of Byzantine and Ottoman Material Culture
Archiving Medieval and Post-Medieval Archaeological Fieldwork Data from the Eastern Mediterranean (600-2000)
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Student for a day Data science & Artificial Intelligence
Study information
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Data use, online consumer needs, business strategies and regulatory response
This project aims to explore and examine the factors that impact upon the efficacy of information disclosure duties pertaining to customer data use in online business.
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Data science and sports: a winning combination
Athletes always strive for the top. How can data scientists assist them in improving their performance? During the seminar Data Science and Sports, the possibilities and challenges of collaboration between these two worlds were discussed.
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How are Big Data, ML and LLM changing Software Engineering?
Lecture
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PhD candidate in GUTS consortium, Data Science for Interdisciplinary Research
Social and Behavioural Sciences, Psychology
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Knowledge Discovery and Data Mining from patient experience repositories
This project develops a scientific method to extract clinically relevant new information from patient forum websites that discuss patient experiences concerning e.g. medication, nutrition, co-morbidities, genetic factors etc.
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Analysing diseases through interactive visual interfaces
Alzheimer’s disease and cancer are two examples of diseases that are related to malfunctioning cellular patterns. The examination of cell tissue, however, takes a lot of time and generates a lot of data. To make the analysis of data easier, Antonios Somarakis of the Data Science Research Programme (DSRP)…
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Frank Takes on NPO Radio 1 about big data
Frank Takes, Assistant Professor at the Leiden Institute of Advanced Computer Science (LIACS), analyses the flow of funds in our economy using big data. With Jort Kelder, he discussed the value and importance of these data on NPO Radio 1.
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Making big data meaningful for a promising start
All children deserve a promising start. Most children are doing fine. But some need extra support, because of problems during pregnancy or because they grow up in disadvantaged circumstances, e.g. due to poverty, parental addictions or psychological problems.
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Accessing End-Of-Supply Risk of Spare Parts Using Big Data
How to access the end-of-supply risk of spare pares using big data analytics
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Deep learning for tomographic reconstruction with limited data
Tomography is a powerful technique to non-destructively determine the interior structure of an object.Usually, a series of projection images (e.g.\ X-ray images) is acquired from a range of different positions.
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Staying healthy with big data
By analysing the metabolism using big data techniques, we can identify health risks at an earlier stage. Thomas Hankemeier, professor of Analytical Biosciences at the Leiden Academic Centre for Drug Research, explains how that works.
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Data Carpentry for Social Sciences
OSCL members, amongst which our representative in the Archaeology faculty, were part of Data Carpentry for Social Sciences. Here's what happened.
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Verandering van geloofsvoorstelling: Analyse van legitimaties door Antony Flew, Cees Dekker en Raymond Bradley
Michiel Pronk defended his thesis on 30 March 2016
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Data-driven Improvement of Hip Fracture Care
PhD defence
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Governments working with one hand tied when it comes to data on vulnerable groups
A new discussion paper published in Policy Sciences by two Leiden researchers claims that governments are working with one hand tied when it comes to data on vulnerable groups. At the core of this paper is the idea that even though the volume of data has increased in recent years, the quality of the…
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Based Clustering of Objects on Subsets of Attributes in High-Dimensional Data
This monograph focuses on clustering of objects in high-dimensional data, given the restriction that the objects do not cluster on all the attributes, not even on a single subset of attributes, but often on different subsets of attributes in the data.
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Sifting through data the smart way
We produce more data than ever before, and researchers gather more and more information. That data contains a wealth of insights and new possibilities. But how do you extract them? In Leiden, statistics and information science come together in innovative multidisciplinary research. Read more in the…
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VODAN Africa – FAIR Covid-19 Data across Africa and Asia
VODAN Africa started as a platform to enable access to critical data needed from Africa to fight the novel COVID-19. The initiative was inspired by the experience from the Liberia Ebola Virus outbreak in 2014: early detection requires contact tracing. Inclusion of the most vulnerable is critical to…
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Causal Discovery from High-Dimensional Data in the Large-Sample Limit
Developing robust algorithms and theory for establishing cause-effect relationships from observational data that scale up to large data sets
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Data Science meets Humanities
Lecture, Seminar
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citizens’ participation in public service delivery: the possibilities of data dashboards
Data science offers exciting new instruments for governments to reach out to citizens, for example by using data-driven information channels, providing real-time simulations, or personalizing services based on citizen data. At the same time, the possibilities and use of data science methods can have…
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Growing super legs for the Tour de France with the aid of Leiden data science
Only the fittest cyclists stand a chance of taking yellow in the brutal Tour de France. Team Jumbo-Visma is working with data scientists from Leiden. They have analysed the stages and performance of Jumbo-Visma’s riders in previous Grand Tours. And they are researching how to determine the fitness level…
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Data-Driven Machine Learning and Optimization Pipelines for Real- World Applications
Machine Learning is becoming a more and more substantial technology for industry.
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From scarcity to abundance: big data in archaeology
New digital methods and a data explosion are radically changing archaeological research. Karsten Lambers, Associate Professor of Archaeological Computer Science, tells us all about it.
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the automated detection of archaeological objects in remotely sensed data
Generally the data from remote sensing surveys - the scanning of the earth by satellite or aircraft in order to obtain information about it - is screened manually in archaeology. However, constant monitoring of the earth's surface causes a huge influx of data of high complexity and high quality. To…
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Design and development of a comprehensive data management platform for cytomics: cytomicsDB
Promotor: J.N. Kok, Co-promotor: F.J. Verbeek
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Integrating data to learn more
Tremendous amounts of data are generated in scientific research each day. Most of this data has more potential than we are using now, says Katy Wolstencroft, assistant professor in bioinformatics and computer science. We just need to integrate and manage it better.
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Stacked Domain Learning for multi-domain data: a new ensemble method
The aim of this project is to develop accurate but interpretable ensemble learning methods for high-dimensional multi-domain data.
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Monitoring drug-related homicides: An assessment of existing data sources and potential for future monitoring
This project’s aim is to critically assess current homicide data sources in order to develop a proposal for long-term EU-level monitoring of DRH.
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Visual analytics for spatially-resolved omics data at single cell resolution: Methods and Applications
The deeper understanding of an organism's pathology is important for developing treatments. Over centuries of systematic research, clinical researchers have demonstrated that the more information they acquire about the cellular properties and their organisation in the tissue, the better they can understand…
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A new era for nature conservation using hyperspectral and lidar data; Oostvaardersplassen as a case study
This project aims to develop advanced data analysis methods for monitoring and increasing our understanding on biodiversity dynamics in nature reserves such as the Oostvaardersplassen.
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Making policy with big data
Governments have increasing amounts of data at their disposal. How can big data be used in policymaking? And are governments ready to deal with all this data? That is what Sarah Giest, Assistant Professor at the Institute of Public Administration, is interested in.
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National Culture and Africa Revisited: Ethnolinguistic Group Data From 35 African Countries
This study seeks to partially fill the knowledge gap about national culture in Africa, basing its research on data on ethnolinguistic groups (instead of administrative regions).
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Post-doctoral Data Scientist Fairness in machine learning for health
Science, Leiden Institute of Advanced Computer Science (LIACS)
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FAIR Surveys Project
This project aims to contribute to the improvement of documentation and archiving standards (conform the FAIR principles) for systematic Mediterranean archaeological field survey.
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machine learning for intervention development from wearable sensors data
Science, Leiden Institute of Advanced Computer Science (LIACS)
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From intuition to data
Dutch speedskaters have been winning the most medals in speed skating at the Winter Olympics for years. How? Based on their intuition. Scientist Jeroen van der Eb of the Data Mining & Sports group of the Leiden Institute of Advanced Computer Science (LIACS) wants speedskaters to adjust their irons based…
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Big data on a small scale
Mirjam van Reisen favours big data built up from local inputs in developing countries and suitable for local use. The new Professor of Computing for Society at Leiden's Faculty of Science connects data science with development sociology. Inaugural lecture 10 March.
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Data science and visualisation by the government
On 20 February 2019, a special meeting on data science took place in the House of Representatives. The aim of the meeting was to start a dialogue with government organisations about data developments within the government.
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Improving football skills using data-mining
Using positional data to determine which tactics lead to a successful attack? Rens Meerhoff, researcher at the Sports Data Center of the Leiden Institute of Advanced Computer Science (LIACS), has been using data-mining to analyse football tactics for several years. In Friesch Dagblad he explains the…
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New paper on: 'Legal Barriers and Enablers to Big Data Reuse: A Critical Assessment of the Challenges for the EU Law'
eLaw colleagues Bart Custers and Helena Ursic have a new publication in the peer-reviewed journal The European Data Protection Law Review.
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Van woord tot akkoord. Een analyse van de partijkeuzes in CPB-doorrekeningen van verkiezingsprogramma's en regeerakkoorden, 1986-2017
This PhD-thesis analyses the relationship between the parties’ choices in the CPB Netherlands Bureau for Economic Policy Analysis’ assessments of the election manifestos and coalition agreements over the period 1986-2017, and tries to explain this relationship.