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Integration of Metabolomics and Flux Balance Analysis: Applications and Challenges
This book chapter presents an in-depth analysis of the integration of metabolomics and flux balance analysis (FBA) as powerful tools for...
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Use of Bioinformatics in High-Throughput Drug Screening
Bioinformatics has emerged as a vital component of almost all the fields of biological sciences. Its ability to quickly generate, analyze, and...
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Bioinformatics in Precision Medicine and Healthcare
In today’s healthcare industry, we prefer methods that are highly effective and minimize risks. Precision medicine is a new field that utilizes...
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Bioinformatics in Pathway Identification, Design, Modelling, and Simulation
Bioinformatics plays a crucial contribution in the study of complex biological systems, particularly in the areas of pathway identification, design,...
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Bioinformatics in Drug Discovery
Drug discovery requires high cost and is a time-consuming process, and the facilitation of computer-based drug design methods is one of the most...
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Artificial Intelligence and Machine Learning in Bioinformatics
Artificial intelligence (AI) and machine learning (ML) have emerged over the past decade as the cutting-edge technologies most expected to...
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Bioinformatics in Preventive Medicine and Epidemiology
Bioinformatics is a promising science for the future. Bioinformatics tools help analyze complex computer-based biological data. Currently, scientists...
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Physiological Modeling
This chapter introduces physiological models in sport. Physiological models are primary used to assess the and load of players based on different...
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History
The development of the scientific discipline of sports informatics, which according to Link and Lames (2018) can be understood as multi- and...
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Position Data
The focus of this chapter is on position data, which are already generated by default for practical use in soccer, but only for research purposes in...
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Open-Set Recognition
The focus of this chapter is on open-set recognition (OSR) problems in Sports Sciences. It introduces the OSR concept, and possible application...
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Artificial Neural Networks
This chapter shows the basic structure and function of a simple neural network as well as some examples where Artificial Neural Networks can be...
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Video Data
In this chapter, applications of video data for sports analysis are discussed using examples from the domain of soccer. Videos depict sport-specific...
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Python
This chapter introduces the programming language Python and its relevance for computer science in sport. The need for programming languages in sports...
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Networks Centrality
Identifying key processes and their actors is a task of great importance in enquiring or assessing systems performance. This quest is particularly...
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Simulation
The model-based simulation discussed in this chapter is used to analyze and predict the behavior of complex systems (here: in sports). For this...
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Logistic Regression
With the rise of Big Data in sports performance analysis based on data and a wide variety of possibilities have opened. In the last, 10 years...
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Role of Statistics for Decision-Making in Biostatistics
The purpose of this lesson is to outline a general process for the use of statistics in support of the decision-making process for biostatistics,...
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Putting It All Together – R, the tidyverse Ecosystem, and APIs
The purpose of this lesson is to provide summary information on how R and more specifically R’s tidyverse ecosystem are both used in support of data...
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Data Science and R, Base R, and the tidyverse Ecosystem
The purpose of this chapter is to provide introductory guidance and examples on the issue that quality software is never static but is instead...