Data is the lifeblood of biomedical research: Whether you’re studying genetics, drug development, or disease epidemiology, effective data management is crucial. This blogpost will outline some best practices that can help you not only Read More
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Editor’s Note: This post was originally published in 2017 and has been refreshed for Peer Review Week 2023. When a paper undergoes peer review it is considered reliable. It is no surprise then that a majority Read More
Imagine you have a complex Bayesian model, like predicting the effectiveness of a new drug. The traditional methods may not work very well because they rely on mathematical shortcuts or simplifications. This is where Markov Read More
Editor’s Note: This post was originally published in 2013 and has been refreshed for Peer Review Week 2023. Once you submit your painstakingly written research paper to the journal of your choice, you Read More
Artificial intelligence (AI) is shaking up many industries, with professionals increasingly realizing the benefits of using AI to improve efficiency and productivity. Academic research is no exception – whether it is used for writing, editing, or Read More
Biomedical research can be a complex puzzle, and sometimes, finding the right answer requires a bit of statistical magic. Enter bootstrapping! Bootstrapping is like making a lot of mini-teams from one big team. Imagine you Read More
The publication of an academic research paper requires the expertise of two different professionals: the author and the copyeditor. While their roles are complementary, their approaches to the paper are quite different. To capture the Read More
Selecting the right journal to publish your research is a critical decision that can shape the trajectory of your academic career as an early career researcher. With a multitude of journals available, each with its Read More
Accuracy and integrity matter a lot in biomedical research, especially when you’re collecting and analyzing data. Biases in data can lead us astray and waste time and resources on flawed inferences. Here are seven Read More
Imagine you’re studying the relationship between a specific gene and cancer risk, using data from a large patient cohort. You don’t want your conclusions to rely solely on chance, do you? That’s Read More