The everyday life of a doctoral researcher

Would you like to be a researcher?

For a person interested in a career in computational medicine, doctoral studies are a common first step. These studies take about four years to complete, and they culminate in earning a doctoral degree. Although a doctoral researcher must attend some courses, the majority of the time is dedicated to research. Therefore, doctoral research is more like ordinary paid work than studying, at least in our case. Before doctoral studies, candidates usually obtain a master's degree in a relevant field. In the case of computational medicine, that could be genetics, statistics or biochemistry, for example. During their previous studies, students may have gained initial exposure to the field during an internship or master's thesis. During doctoral studies, we deepen the understanding of the knowledge acquired in earlier studies and learn to apply it in daily work. In addition, we develop essential skills, such as critical thining, independent work, and effective scientific communication.

Daily dose of science

A science project can be divided into several phases. The research idea is the basis for a preliminary plan of the analyses. However, the plan is often modified based on the initial findings. The analysis phase usually takes a few months. After that, it is time to write an article to report the discoveries. The article is then submitted for publication to a field-specific journal, where it undergoes a peer review by experts outside the research group. The review phase also takes some time, because the authors of the article may need to address corrections and modifications suggested by the reviewers and editors before publication. Usually, it takes at least a year to turn the preliminary plan into a published article. A typical day of a doctoral researcher is spent performing analyses or writing the manuscript. In the field of computational biology, you can work either remotely or in the office – of course, the office environment provides refreshing coffee break discussions with colleagues. Additionally, university seminars and courses bring variation to the everyday life of a doctoral researcher.

A good scientist always knows their tools

Mastering analytical tools and key methods is crucial for a computational biologist. Proficiency with the methods speeds up the analysis process considerably. Software tools such as R and command line interface (CLI) will become particularly familiar. In our research, the key method is genome-wide association analysis (GWAS). This method tests the association of millions of genetic variants with a studied trait , which could be a disease, height, or coffee consumption, for example. When the association of a variant with the studied trait reaches the threshold of genome-wide significance, it suggests that a gene affecting the trait is located near the variant. The GWAS results can be leveraged, for example, to develop new drugs for diseases, or for further analyses. For example, Mendelian randomization (MR) can be used to investigate causal relationships between different traits.

A spectrum of professionals

Working as a researcher requires the ability to work independently and plan your own schedule, but projects are rarely carried out from A to Z entirely on your own. Research is often a multidisciplinary collaboration - one project may involve a spectrum of people from different professional backgrounds, such as medical doctors, other health care professionals, biologists, mathematicians, physicists, chemists, economists, statisticians - you name it! The author list of the final published paper may include people from several universities all around the world, or even an entire biobank. The research topics of our team are also a spectrum: the authors of this post have worked with musculoskeletal conditions, dermatology, infectious diseases, and gynaecology, for example. In day-to-day interactions, however, the focus is on our own research group, thesis supervisors, and other doctoral researchers. Within this collaborative framework, the role of a computational biologist is to know the contents of the data, process it, and analyze it using the appropriate tools.

How does one prevent a data breach?

Protecting patient privacy is a central ethical concern in medical research. According to Finnish law, information on the patients is always confidential and must not be shared with any third party. So, as computational biologists, we are strictly prohibited from accessing personal diagnoses from databases and forwarding the information to your neighbors – even if they would be paying us well. Jokes aside - fortunately, we even couldn’t, because patient identies are protected by many measures before we get our hands on the data. In healthcare units, patient samples and information are managed with rigorous data protection measures. Once the samples are transferred to a biobank, they are pseudonymized, meaning that personal identity codes are replaced with codes that prevent the identification of individuals. Data handling is performed on secure servers, from which we cannot transfer any raw data to personal computers, for example. Naturally, the servers also require strong passwords - “123123” is not adequate.

Constructive self-criticism

Often, conducting a computational analysis can be a whole lot easier than interpreting the results. For example, MR is a sensitive method, which means that a series of tests must be performed for the results to rule out the effect of any confounding factors. Another challenge is dealing with various data formats. For example, when meta-analyzing results from two biobanks, differences in data formats requires careful handling when combining the data. Being critical of your own results is one of the important skills of a researcher. Especially a result that significantly differs from scientific consensus reported in previous literature must be carefully examined.

Highs and lows of research

As mentioned before, research plans are often broad and subject to change. Oftentimes, one must re-run the analyses, or the project just otherwise changes its direction completely. Amidst the changing plans and re-analyses of re-analyses, the researcher might sometimes find themself in the depths of despair. Luckily, it is not all chaos and misery at all: for example, finding a gene previously unreported in association with the disease is always a joyous moment. Obviously, finalizing a project and getting the article published means it is time for a small celebration. For a doctoral researcher, it is also a milestone on a journey towards earning the doctor’s hat.

Authors

Anni Heikkilä

Jasmin Takala

Ville Salo