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Biostatistics with Python

You're reading from   Biostatistics with Python Apply Python for biostatistics with hands-on biomedical and biotechnology projects

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781837630967
Length 374 pages
Edition 1st Edition
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Author (1):
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Darko Medin Darko Medin
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Darko Medin
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Table of Contents (24) Chapters Close

Preface 1. Part 1:Introduction to Biostatistics and Getting Started with Python
2. Chapter 1: Introduction to Biostatistics FREE CHAPTER 3. Chapter 2: Getting Started with Python for Biostatistics 4. Chapter 3: Exercise 1 – Cleaning and Describing Data Using Python 5. Chapter 4: Part 1 Exemplar Project – Load, Clean, and Describe Diabetes Data in Python 6. Part 2:Introduction to Python for Biostatistics – Methodology and Examples
7. Chapter 5: Introduction to Python for Biostatistics 8. Chapter 6: Biostatistical Inference Using Hypothesis Tests and Effect Sizes 9. Chapter 7: Predictive Biostatistics Using Python 10. Chapter 8: Part 2 Exercise – T-Test, ANOVA, and Linear and Logistic Regression 11. Chapter 9: Biostatistical Inference and Predictive Analytics Using Cardiovascular Study Data 12. Part 3:Clinical Study Design, Analysis, and Synthesizing Evidence
13. Chapter 10: Clinical Study Design 14. Chapter 11: Survival Analysis in Biomedical Research 15. Chapter 12: Meta-Analysis – Synthesizing Evidence from Multiple Studies 16. Chapter 13: Survival Predictive Analysis and Meta-Analysis Practice 17. Chapter 14: Part 3 Exemplar Project – Meta-Analysis of Survival Data in Clinical Research 18. Part 4:Biological and Statistical Variables and Frameworks, and a Final Practical Project from the Field of Biology
19. Chapter 15: Understanding Biological Variables 20. Chapter 16: Data Analysis Frameworks and Performance for Life Sciences Research 21. Chapter 17: Part 4 Exercise – Performing Statistics for Biology Studies in Python 22. Index 23. Other Books You May Enjoy

Why do we need biostatistics in life sciences?

Life sciences are some of the most important fields of science today. Throughout the disciplines of biology, biomedicine, and pharmaceutical sciences in pharmaceutical and biotech companies, biostatistics plays a key role. We use it to analyze the data from experiments, improve study designs, interpret the results of studies, and make decisions within all these areas of life science. Biostatistics is applicable in all of these areas, and more, because it allows us to understand the underlying processes that you may be investigating.

While biostatisticians are essential in many areas, from biology and medicine to public health, understanding biostatistics is critical for other professionals in these areas, too.

If you are performing an experiment, conducting a study, or are interested in life science analytics, you will need to analyze the data to make conclusions or get insights from it. Biology and biomedical professionals will encounter biostatistics in most areas of their careers.

When reading almost any life science research publication, you will need to understand how to read biostatistics to understand the results. This is essential for both biologists and biomedical professionals who want to stay current with the latest research statistics for the pharmaceutical industry to discover biomarkers or therapies for patients.

Biostatistics enables us to understand and analyze the data or results we get from experiments, research, or observations. This is one of the reasons why the biostatistical field is important not only for biostatisticians, but also for doctors, biologists, epidemiologists, public health decision-makers, bioinformaticians, health data scientists, and other professionals from most life science branches.

The next subsection will help you understand the specific areas of life science where biostatistics is used. This is very important as every life science area is different and requires a different approach to resolve the research problems

Biostatistics in human life sciences

Biostatistics is essential in many human life sciences. Epidemiologists heavily rely on different types of data to infer their insights. Understanding statistical concepts is essential to understanding population-level biological events and helps both doctors and public health professionals in their work. One such example is the past SARS-CoV-2 pandemic. You must have heard about concepts such as reproductive number (R) or SARS-CoV-2 cumulative incidence of infections, mortality, lethality, excess deaths, and other similar terms. All these concepts are derived using biostatistical concepts and formulas.

Epidemiology is predominantly used in biomedical science areas by public health professionals to make decisions for disease response and to keep the population as safe as possible.

Figure 1.1 – Areas of human life science where biostatistics is used

Figure 1.1 – Areas of human life science where biostatistics is used

Medical doctors need biostatistics, not only for their everyday work but also for publishing their academic work, which generally utilizes statistics to summarize and analyze the data of studies and to understand novel discoveries in their profession by interpreting study results from novel publications.

Biomedical research is one of the areas which is heavily reliant on biostatistics and knowing biostatistics is important, not only for statisticians but also for biomedical researchers. Even with access to expert biostatisticians, it is helpful to understand biostatistical thinking and analysis methodology to help with discussions on study design, analysis, and interpretation.

Pharmaceuticals, research, and the development of medications are among the largest industries today. The majority of advanced research in these areas is vital for the biomedical industry.

Biostatistics for biology

While statistics itself is used in many different areas of science, its application in biology has evolved in a specific way due to the nature of different biological domains. Statistics cannot be effectively applied without knowing the basic principles of these biological disciplines.

The following figure shows biostatistics applications in different areas of biology:

Figure 1.2 – Areas of biology where biostatistics is used

Figure 1.2 – Areas of biology where biostatistics is used

Bioinformatics relies on different statistical methods and algorithms combined with computational tools to process and analyze large amounts of biological data, such as RNA (ribonucleic acid) sequencing data (transcriptomics), DNA (deoxyribonucleic acid) data (genomics), and many other data types. Bioinformatics is specifically focused on genetics and molecular biology but implements methods such as biostatistics and machine learning.

Ecological studies are one of the examples where biostatistics is one of the main biological research drivers. Analyzing plant and animal populations, trends, dynamics, and relations between organisms and their environments would not be possible without biostatistics. Next, we will discuss biostatistics applications in different fields in more detail.

Biostatistics in epidemiology and public health

Epidemiologists and public health professionals answer some of the most important public health questions but also make decisions in different communities. They investigate diseases and events in smaller groups of people, cities, and countries, or even worldwide phenomena, such as pandemics. All this would not be possible without the use of biostatistics facilitating the process of analyzing the biomedical and population data.

Epidemiologists often create different statistical models to try to relate infectious outbreaks to causes and then prevent future infections and isolate the infection source. One such example is studying types of food ingested by infected individuals and identifying a potential bacterial or viral food source, or a location, such as a hotel or restaurant, as a source. Biostatistical models are often used in identifying the sources of infectious agents, which will be discussed in more detail in later chapters.

A few biostatistical concepts used in epidemiology and public health are as follows:

  • Prevalence
  • Cumulative incidence
  • Identifying causes for infectious outbreaks
  • Characteristics of microorganisms causing outbreaks in a population
  • Epidemiological monitoring of populations
  • Decision-making based on biostatistics

Biostatistics in medicine and biomedical research

Medicine and biomedical research are very active sciences today, as they directly or indirectly impact almost everyone’s life today. These two disciplines rely heavily on the use of biostatistics. It is of the essence not only for medical doctors but also for biomedical researchers.

Medical doctors’ understanding of the probability of different diseases or outcomes is highly dependent on understanding the statistical concepts and how these apply to groups of patients.

Here are some of the most important concepts used in biomedical research:

  • Understanding of incidence of safety for treatments
  • Making conclusions about the symptom and disease relations
  • Creating biomedical studies
  • Analyzing biomedical data
  • Interpreting novel research
  • Becoming specialized in biomedical data analysis

Biostatics in zoology and botany

A significant portion of the research in biological disciplines, such as zoology and botany, depends on quantifying different aspects of their behavior, life cycles, relations with their environmental factors, and many other aspects.

Some examples of areas in zoology and botany that apply biostatistical methods are as follows:

  • Animal behaviors
  • Plant growth
  • Relations between animals and their environment
  • Relations between plants and their environment
  • Biochemical composition of different tissues in animals
  • Biochemical composition of different tissues in plants
  • Identifying feeding patterns in animals

Biostatistics in ecology

Ecology is one of the life science disciplines significantly based on biostatistics. Understanding the population’s diversity and the relationships between organisms, as well as the relationships between organisms and their environments, is facilitated using different biostatistical methods.

Some important areas of the use of biostatistics in ecology are as follows:

  • Relationships between animals and their environment
  • Relationships between plants and their environment
  • Studying biochemical and molecular aspects in zoology and botany
  • Studying relations between humans, ecology, and environmental protection

Biostatistics in pharmaceutical research and design

The pharmaceutical industry is one of the main drivers of research and innovation today. Biostatistical analyses enable pharmaceutical companies to design, conduct, and make decisions based on different analyses and insights. In fact, almost any high-quality research project in the pharmaceutical industry consults biostatisticians to make sure that the design is statistically sound and that it can answer the research questions to drive forward the development of assets and to conform with regulatory requirements. Biostatistics is also the key to analyzing adverse events from the data collected during a study, which is essential for any pharmaceutical product. All medications are required to have a list of adverse effects and this is something that can be seen in everyday life. Biostatistical calculation of incidence rates is one of the ways to assess those adverse effects.

Biostatistics is used to assess the efficacy of different therapies and, as such, is a key element in selecting the candidate drugs for diseases such as diabetes or cancer, which are then further evaluated in clinical trials using different biostatistical methods.

Calculating required sample sizes for pharmaceutical studies is a common task of biostatisticians within the pharmaceutical industry, but this is also intertwined with trial design and endpoint selection.

Here is a summary of the uses of biostatistics in pharmaceutical R&D:

  • Creating R&D studies
  • Evaluating drug safety
  • Selecting drug candidates through biostatistical screening
  • Designing clinical trials
  • Evaluating results
  • Research publications
  • Meta-analyses of therapy effects
  • Regulatory submission

Biostatistics in bioinformatics and genetics

Molecular biology is one of the biological branches that is very specific in terms of using statistical analyses. From structural biology to analyzing gene expression, biostatistics plays one of the most important roles in bioinformatics. Statistical bases form many genetics areas, such as inheritance genetics and population genetics. Here are some of the areas of bioinformatics and genetics where biostatistics plays a pivotal role:

  • Differential gene expression
  • Structural biology
  • Mutation biology
  • DNA analytics
  • Mendelian inheritance
  • Mendelian randomization studies
  • Population genetics
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Biostatistics with Python
Published in: Nov 2024
Publisher: Packt
ISBN-13: 9781837630967
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