Why our brains are wired to be wrong, even when we’re trying to be right.
We like to think of scientists as super-rational beings who follow evidence wherever it leads, immune to the mental shortcuts and biases that trip up the rest of us.
Delving into the tools, techniques, and analytical approaches that drive modern research and innovation. This category covers everything from algorithm design and data analysis pipelines to computational modelling, helping researchers turn complex datasets into meaningful insights.
Why our brains are wired to be wrong, even when we’re trying to be right.
We like to think of scientists as super-rational beings who follow evidence wherever it leads, immune to the mental shortcuts and biases that trip up the rest of us.
As you might have noticed, bioinformatics is a vast field. However, there is one common analysis which you can encounter quite frequently and can help you get started: the raw sequencing data analysis. As all these steps can be confusing sometimes, I propose a generic walkthrough in order to give you a few basics to start your project.
Computational science is rapidly becoming one of the most transformative disciplines of the 21st century, driving progress in a wide array of fields. From climate modeling to genomics, and artificial intelligence to quantum computing, computational methods are reshaping the way scientists tackle complex problems. As the demand for data-driven solutions continues to grow, the global advancement of computational science promises to unlock unprecedented opportunities for research, innovation, and collaboration.